University of Bremen - Data Science Center

The DSC Supports The Development of an Artificially Intelligent Fence For Automated Wolve Detection

Svenja Goers — Mon, 08 May 2023 12:00:00 +0200

The planned stay is part of the research project mAINZaun (more about mAInZaun ) which is developing a pasture fence that uses artificial intelligence (AI) to detect and drive away wolves. The system is not only learning to distinguish wolves from other animals. Moreover, it is being trained to recognize and ward off each wolve individually. In this way, the ‘intelligent’ fence can contribute to the protection of farm animals and improves the coexistence of people, livestock, and predators.

However, the automated detection of wildlife animals using recorded images comes with a lot of challenges. Often, wolves are captured by the cameras from faraway. Or the animals are only partly visible, hidden behind trees and bushes. In addition, problems like dirty lenses, blurred images or the changing weather conditions of the different environments make automated image detection more difficult.

The research stay at SUPSI (Scuola universitaria professionale della Svizzera italiana) in Lugano aims to tackle these challenges and further advance the research project. SUPSI is one of the leading institutes in computer vision, machine learning and big data. The goal of the international collaboration is to gain new insights into the field of computer vision and further improve the developed ML models and algorithms for automated wolve detection.

Funding recipient:

Dipl.-Ing. Jens Dede (Faculty 01 – Physics/ Electrical Engineering, ComNets)

Funding period:

09th May 2023 - 17th Mai 2023

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links

Information about the DSC Seed Grant

DSC Seed Grant Flyer

The DSC Supports a Data Science Project About a Novel Recruitment Method in Social Scientific Survey Research

Svenja Goers — Mon, 26 Jun 2023 12:00:00 +0200

Large-scale cross-national surveys in the social sciences are normally run as face-to-face surveys which makes them extremely resource-intensive. Online surveys, on the other hand, can significantly reduce the costs. However, they are usually not representative of populations and make the targeting of possible participants more difficult. Thus, researchers have started to implement a new sampling approach which is referred to as advertisement-based survey recruitment. This new method is based on social media adverts that are displayed to users and ask them to partake in an online survey. Since the online advertising industry is highly globalised and pervasive, this approach can facilitate a relatively random and cross-national sampling of survey participants.

The goal of this project is to advance this new survey approach by using data science methods. As part of a research collaboration between Dr. Dennis Redeker (ZeMKI, Centre for Media, Communication and Information Research, University of Bremen) and data scientist Ingmar Sturm (University of California, Santa Barbara ), two bilateral in-person workshops are going to take place at the University of Bremen. Together, the two researchers are going to further develop advertisement-based survey recruitment through automation and optimization.

The first research-based workshop aims to establish a strong conceptual framework and develop a blueprint for an R package which enables the automatization of online advertisement-based survey recruitment. The second workshop will be training-focused and is designed for PhD students from different disciplines that are based at the University of Bremen. The project will also be supported by a student research assistant.

The long-term goal of the project is to use data science methods in order to significantly scale existing survey-based projects at the University of Bremen while saving a significant amount of resources.

Funding recipient:

Dr. Dennis Redeker (Faculty 09 – Cultural studies, ZeMKI, Centre for Media, Communication and Information Research)

Funding period:

1st June 2023 - 30th November 2023

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links

Information about the DSC Seed Grant

DSC Seed Grant Flyer

A New Way Towards Performance Prediction of ML Accelerators

Svenja Goers — Fri, 02 Jun 2023 10:00:00 +0200

Convolutional Neural Networks (CNNs) can handle huge amounts of unstructured data and are widely used to perform various tasks such as image and video recognition, classification, and natural language processing. Moreover, CNNs are one of the most popular deep learning algorithms used for emerging technologies such as autonomous driving. They are highly complex algorithms that consist of multiple types of layers and thus require high computational resources. Consequently, designers often use Machine learning (ML) accelerators like General Purpose Computation on Graphics Processing Units (GPGPUs) to improve and speed-up their performance.

Hence, selecting the right ML accelerator is of great importance. This process, however, comes with challenges and can be very time-consuming as well as cost-intensive. To overcome this issue, a fast and automated approach is needed which allows finding the right accelerator without the need to build several prototypes and test different hardware platforms.

Together with Mehran Goli (DFKI) and under the direction of Rolf Drechsler, DSC research associate Christopher Metz has a developed a novel approach which enables fast and accurate performance estimation of CNNs for GPGPUs during the early stages of the design process. This new method is discussed in the paper “Fast and Accurate: Machine Learning Techniques for Performance Estimation of CNNs for GPGPUs” and is linked to previous studies of the authors which focused on the determination of GPGPUs’ power consumption (we reported »here).

The study compared five different ML algorithms to obtain the most accurate predictive performance model. In addition, the developed approach was evaluated by estimating the performance of several CNNs for different GPGPUs (NVIDIA V100S and NVIDIA GTX 1080iT). The results show that the proposed prediction model can determine a CNNs performance with an absolute percentage error of 5,73% compared to real GPGPUs. The new method also is significantly faster than the execution time of previous approaches which enables the performance estimation of CNNs at the early stages of the design process. In contrast to many comparable approaches, this method does not require a prior execution of the neural networks. Furthermore, the model is not limited to a single GPGPU because it considers hardware features and thereby supports cross-platform prediction.

The work was presented on May 19th (4:10 pm (MEZ)) at the PAISE 2023 workshop on “Parallel AI and Systems for the Edge” in St. Petersburg, Florida. The interaction-focused workshop took place for the fifth time and was co-conducted with IPDPS 2023.

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

Participate in The First Bremen-Cardiff Data Science Workshop!

Svenja Goers — Fri, 17 Mar 2023 10:00:00 +0100

The workshop will feature different presentations held by researchers from both, Bremen and Cardiff Universities. The talks are going to address current research in the field of data science and AI. These include interesting topics such as data science in the high-hazard industry and the application of analytics and data science methods in healthcare systems.

The event will also serve as a forum for open discussion and networking and offers the opportunity to meet and connect with experts from both universities. The workshop is going to take place next Tuesday, March 21 from 3 pm to 5 pm and will be held virtually via Zoom. For more detailed information on the workshop agenda (schedule, abstracts, etc.) please visit the website (»here).

Have we sparked your interest in this upcoming event? You can register for the Bremen-Cardiff Data Science Workshop »here (registration is necessary).

The DSC looks forward to meeting you at the event!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

We Are Looking For Student Support For Our IT!

Fri, 16 Jun 2023 12:00:00 +0200

The DSC is looking for a student assistant (m/f/d) for support in the area of hardware-infrastructure development. We offer you exciting insights into the development of a modern Data Science computing infrastructure.

The DSC Supports a Project That Aims to Extract Inequality-relevant Information From Online Job Advertisements

Svenja Goers — Wed, 01 Mar 2023 14:00:00 +0100

The project’s main aim is the computational extraction of information about requested qualifications and skills in online employment advertisements. In the next step, the collected data can serve as a basis to carry out analyses regarding gender inequalities as well as inequalities based on educational backgrounds.

The study will draw on a database which consists of online job advertisements that were published by the Federal Employment Agency (BA – Bundesagentur für Arbeit) and are available to the Federal Institute for Vocational Training (BIBB – Bundesinstitut für Berufsbildung).

The research project combines the investigation of socio-economic inequalities with data science methods to explore the potential of online employment advertisements as a source for inequality research.

Funding recipient:

Prof. Dr. Wiebke Schulz (Faculty 08 – Social Sciences)

Funding period:

1st March 2023 - 30th June 2023

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC Supports The Further Development of The Local News Platform molo.news

Svenja Goers — Thu, 01 Dec 2022 11:00:00 +0100

The app molo.news is a local platform that has been publishing news and events from Bremen and its surroundings since 2020. In addition to important news from local media outlets, the app also encompasses contributions from different associations, cultural institutions, social movements and other local groups.

On the app, the contents of the platform are not sorted by different news departments, but according to interests and place of residence of the users. This is implemented by assigning thematic key words and location tags to each post that is added to the platform. Currently, news entries are manually tagged either by employees of the editorial hub department or the contributors themselves. Since the news platform has been growing constantly and several hundreds of articles are added to the backend each day, the pilot study is going to test the automation in this area.

The aim is to develop a curation algorithm that enables the automatic tagging of news posts. Thus, new entries in the backend will automatically be provided with certain key words and location tags. The algorithm will be based on automated content analysis as well as machine learning. News which have been manually curated by the editorial team in the past will serve as training data. The goal will be reached when at least 80 percent of the articles can be tagged automatically. The interdisciplinary study hereby combines the fields of media and communication studies and computer science. Moreover, the project is supposed to examine to what extent tagging systems can contribute to the prevention of polarisation.

Funding recipient:
Prof. Dr. Andreas Hepp (Faculty 09 – Cultural Studies, ZeMKI – Centre for Media, Communication and Information Research)

Funding period:
1st December 2022 - 30th June 2023

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

E-Science-Days 2023

Svenja Goers — Mon, 06 Mar 2023 10:00:00 +0100

The E-Science Days are an interdisciplinary conference series focusing on the topics of research data management and open science. This year, the E-Science Days took place under the motto ‘Empower Your Research – Preserve Your Data’.

Together, participants discussed how to ensure the sustainable storage, management, availability, and accessibility of research data over its entire life-cycle. Efficient research data management is not only essential for individual research projects, but also for interdisciplinary and international collaboration. Moreover, it fosters the advancement of scientific knowledge and the development of new research questions.

The E-Science Days combined a variety of event formats to enable a lively exchange surrounding the topics of research data management and open science. From March 1st till 3rd, different panel discussions, workshops, talks, and technical presentations took place. Another part of the programme was a poster session that was held on Thursday afternoon. DSC coordinator Lena Steinmann also attended the event. With the poster ‘The Data Science Center of the University of Bremen – Interdisciplinary Hub and Service Infrastructure for Dataintensive Research’, she represented the DSC, giving an insight into its work in the field of research data management and data science.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

Let’s love our data! Oder: Love Data Week 2023

Lena Steinmann — Wed, 22 Feb 2023 10:00:00 +0100

The Love Data Week is an international week of events around research data and aims to draw attention to sustainable data management and good scientific practice. Under the motto “Data: Agent of Change”, this week 2023 is celebrated worldwide from 13 to 17 February and offers numerous events on a wide range of topics related to research data. As Data Science Center of the University of Bremen, we are pleased to offer two workshops and a social event for researchers of the University of Bremen and other institutes of the U Bremen Research Alliance during this week.

Git for Dummies | 15 Feb 2023 ** already fully booked **
We will provide an easy entry for you to learn how to keep track of changes in your documents, code and projects with the version control software git. (in English language)
Introduction to Research Data Management for Social Scientists | 16 Feb 2023
We will discuss the basics of research data management (e.g. research data lifecycle, data management planning, FAIR principles) – and how and why it is relevant for funding, for your project members and for yourself. (in English language)
In Love With Data – A Coffee and Cake Get-Together of the Data Steward Network Bremen | 16. Feb. 2023
Everyone interested in data and data management is invited to this social event with coffee and cake! (in German and English language)

Interested in other data topics? There are many workshops, coffee lectures, panels, and more offered by other institutions during this week. Check out the corresponding websites on the right or look for #LoveData23 on social media.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

Data Science Center And Mahidol University AI Center Lay Foundation For Future Collaboration

Lena Steinmann — Thu, 12 Jan 2023 10:00:00 +0100

The two institutions plan to collaborate on a range of activities, including joint trainings and course materials, sharing of computing resources, joint research projects and publications, and jointly seeking research funding. Additionally, the institutions plan to hold joint workshops and seminars on various topics in the field of data science.

The memorandum was signed on 10th January 2023 by Prof. Dr. Rolf Drechsler and Dr. Lena Steinmann representing the DSC and University of Bremen and by Dr. Pattanasak Mongkolwat and Prof. Dr. Peter Haddawy representing the Mahidol University. The signing ceremony was attended by Dr. Marejke Baethge - Assenkamp (Director International Office), Dr. Mandy Boehnke (Vice President for International Affairs, Academic Qualification, and Diversity), Prof. Dr. Michal Kucera (Vice President for Research and Transfer), and Prof. Dr. Gabriel Zachmann (Mahidol Cooperation Representative).

“We are delighted to start this collaboration with the Mahidol University AI Center. The Memorandum of Understanding lays the foundation for the two institutions to work together to create high quality research and academic value,” said Prof. Dr. Rolf Drechsler, Dean of the Faculty of Mathematics and Informatics and spokesperson of the DSC at the University of Bremen.

Prof. Dr. Dr. Peter Haddawy, Deputy Dean for Research Development at the Faculty of Information and Communication Technology at Mahidol University, added, “We look forward to working with the Data Science Center. Our joint commitment to advancing the field of data science will serve to enhance the research and academic exchange between our institutions.”

This Memorandum of Understanding represents an expansion and strengthening of the existing partnership between the University of Bremen and Mahidol University (more information here ). It will open up new opportunities for both institutions to collaborate, share knowledge, and develop new skills in the field of data science. Both universities welcome this opportunity and look forward to future collaboration.

Data Stewardship Goes Germany

Svenja Goers — Wed, 12 Oct 2022 10:00:00 +0200

This week the Technische Universität Braunschweig is going to host the ‘Data Stewardship goes Germany’ event. On 13 and 14 of October, a two-day workshop on research data management (RDM) in natural sciences and engineering is going to take place. The event will serve as a networking opportunity for data stewards and experts from a variety of different universities and institutes. Participants will present and discuss ideas, challenges and best practices surrounding the topic of RDM.

Data stewards have subject matter expertise in the field of research data management. They provide specialist advice and trainings for researchers, develop sustainable solutions for handling research data and promote the application of the FAIR principles. More and more institutions are in need of data stewardship in order to establish an efficient RDM-infrastructure and raise awareness on the topic. Since the field of data stewardship is a relatively new community, the ‘Data Stewardship goes Germany’ event aims to provide a platform of exchange for data stewards from all over the country.

The first day of the workshop will comprise different key notes and talks addressing subjects such as data management case studies, the application of the FAIR principles and RDM plans and tools. In addition, participants are going to present and discuss their experiences as data stewards during a poster session. On the second day of the workshop, the data stewards are going to attend a so-called bar camp. This is an open and interactive conference format. It is characterised by an agenda that will be developed and determined by the participants themselves.

Data steward Dr. Sandra Zänkert is going to represent the DSC at the upcoming event. During the poster session on the first day, Sandra will contribute to the discussion with a poster that gives an overview over the DSC data stewards’ activities during their first months at the DSC. Sandra’s presentation will thus provide an exemplary insight into the process of establishing domain-specific data stewardship from scratch.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

On The Search For The Right ML-Accelerator

Mon, 12 Sep 2022 10:00:00 +0200

In cooperation with Mehran Goli (DKFI) under the direction of Rolf Drechsler, our research associate Christopher Metz has developed a new approach enabling a more precise determination of the power consumption of GPGPUs when running Convolutional Neural Networks (CNNs) in early phases of development. The authors discuss this new method in their paper titled “Towards Neural Hardware Search: Power Estimation of CNNs for GPGPUs with Dynamic Frequency Scaling”.

The method is based on earlier works of the authors (DDECS we reported »hier, CODES+ISSS we reported »hier, DATA Friday Workshop SLOHA we reported »hier) and enhances previous approaches regarding the dynamic scaling of a graphic card’s frequency. Usually, power consumption can be reduced by lowering the frequency of computing units. With this approach, however, the expected electricity consumption can be estimated in advance. Here an error of only 5,03% is achieved.

Over the last years the power consumption of graphic cards has been increasing steadily. While the Nvidia P100 only required 200 Watt (W), newer models like the V100 and A100, for instance, need 250 and 350 W. This trend is continuing. The upcoming Nvidia H100 can require up to 700 W. Regarding the use of machine learning (especially deep learning) in IoT and Edge Computing, limited electricity consumption plays an important role during the design of these systems. In order to automatise future design processes the authors introduce the concept of “Neural Hardware Search” (NHS), a term that describes the search for the best hardware for neural networks. In contrast to already existing approaches of Software/Hardware-Co-Designs, Neural Hardware Search does not design new hardware. Instead, the most cost-efficient ML-accelerators (e.g. graphic cards) from an already existing set are being selected. The approach of power consumption estimation is combined with other prediction models (e.g. for performance, storage, etc.), to test different graphic card configurations without having to build a large number of prototypes.

Moreover, this approach can also be utilised to efficiently reduce the power consumption when working with cloud providers. For this purpose, the electricity consumption for a CNN is estimated for different frequencies, to determine the frequency with the lowest usage. Afterwards, the previously determined frequency can then be set for all CNNs in the cloud.

This approach was developed in cooperation with the working group Cyber-Physical Systems of the DFKI in Bremen. It was presented during the 4. ACM/IEEE Workshop on Machine Learning for CAD on the 12th and 13th of September in Snowbird Utah.

About the MLCAD Workshop:

The workshop dealt with machine learning, focusing on aspects of CAD as well as the design of electronic systems. It was sponsored by the ACM Special Interest Group on Design Automation (SIGDA) as well as the IEEE Council on Electronic Design Automation (CEDA). The workshop was comprised of different presentations as well keynotes.

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

Meet The DSC at The Open Science Festival!

Svenja Goers — Mon, 29 Aug 2022 11:00:00 +0200

Under the motto “Meet. Share. Inspire. Care.” the first German Open Science Festival will take place. The event will be hosted by the Leibniz University of Hannover and Leibniz Information Centre for Science and Technology. For two days, scientists and international experts will exchange ideas and discuss about open science practices.

Open science aims to practice science in a way that makes research and knowledge more transparent, accessible and collaborative. It encompasses practices such as the publication of open research, open access to academic literature, open peer reviews, and open data which can be shared, reused und redistributed. Another important principle of open science is concerned with transparent and effective science communication. In this context not only expert to expert communication, but also the exchange with the general public is of great importance. The goal of open science is to present scientific results and research in a comprehensible and transparent way to familiarise the public with the principles of science and thus strengthen the credibility of research findings and scientific expertise.

All of these aspects will be in the focus of the upcoming Open Science Festival. The DSC Data Stewards Dr. Julian Lilkendey, Dipl.-Soz. Heike Thöricht, and Dr. Sandra Zänkert are also going to attend the festival. Together with other experts they will participate in various events discussing ideas, concepts and challenges connected to open science. Part of the festival’s programme is, for instance, the panel “Open Science: just done right!” which engages with the question how open science can support scientific integrity. Furthermore, international experts will discuss the increasing commercialization of research publication infrastructure and its affects on open science in a panel titled “Who owns Science?”.

Next to different panels, the festival’s pr ogramme also includes different workshopssuch as the workshop “Transparency and Openness in Peer Review” or a reproducibility hackathon during which participants re-run code from published data with the aim to reproduce the scientific results of the publication.

In addition to participating in panels and workshops, the data stewards will also introduce the DSC and its Data Stewardship services. At the Open Science Marketplace in the Leibniz Universität atrium, they will have their own booth ("Data Stewards at the University of Bremen - Roles and Perspectives") to interact with other participants. The market will be located at the Lichthof of the Leibniz University Hannover and will function as a place for exchange between the festival’s participants. The team is looking forward to networking, discussing open science and presenting the DSC on a national level.

If you would like to find out more about the DSC and its data stewardship services, visit our Data Stewards at booth 17 at the Open Science Festival Marketplace.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

Sketchnote Event on the Topic Data Science

Svenja Goers — Mon, 15 Aug 2022 11:00:00 +0200

As part of the summer holiday programme of the “Haus der Wissenschaft” (House of Science), pupils could learn how to produce podcasts and make sketchnotes. Under the motto “Learn new formats – Structure Thinking – Share and Spread Content” various events took place from July 26 to August 11. Part of the programme were several workshops titled “Creative Doodles” during which the students learned how to draw so-called sketchnotes. Each of the workshops consisted of an introduction to drawing sketchnotes, followed by a short scientific lecture. This enabled participants to directly apply their newly learned skills.

Part of this year’s programme was a lecture by DSC spokesperson Prof. Dr. Rolf Drechsler. As part of a “Creative Doodles” workshop for advanced students on August 11, he gave a talk on data science. During his lecture he discussed the issue “Data is everywhere! But how can we generate knowledge from it?”. Inspired by Rolf Drechsler’s presentation, the workshop participants then prepared sketchnotes on the topic of data science. So-called sketchnotes are a creative tool that combines words and images. They thereby make it possible to illustrate complex matters in a simple manner that makes them easy to comprehend. Consequently, the workshop participants used their newly acquired skills to create interesting and creative sketchnotes that give an insight into the diverse field of data science (see photo).

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

International Data Power Conference 2022

Svenja Goers — Thu, 07 Jul 2022 11:00:00 +0200

This year the Data Power Conference was hosted at three different locations (Sheffield, Bremen and Ottawa). For the first time, the conference was organised in a hybrid format, enabling participants to either attend online or in person at one of the three locations (University of Sheffield, ZeMKI University of Bremen and Carleton University).

While the last Data Power Conference at the University of Bremen (2019) was centred around the theme of global data (in)securities, this year’s focus was placed on critical discussions and dialogues around the topic of data power. Various lecturers and panels critically addressed social, political, economical and cultural consequences connected to the increasing prominence of data in our societies and daily lives. The conference was especially concerned with the question of how stakeholders can be involved in important discussions around data power. Moreover, aspects such as suitable methods for research surrounding data power were discussed.

This year 180 scientists attended the conference, with more than half of them participating online. Bremen was able to welcome 40 scientists, who presented and critically discussed their research in eight panels. The organisation of the Data Power conference in Bremen was supported by the ZeMKI as well as the ifib and the Data Science Center of the University of Bremen. Co-organiser and DSC member Dr. Juliane Jarke received the DSC Seed Grant to support the implementation of the Data Power conference (we reported here).

Furthermore, each conference day included a keynote event discussing data power related issues. The keynote event at the University of Bremen took place in the form of an interdisciplinary dialogue, which addressed possible points of contact between computer science, social sciences and philosophy. Another key speaker was Irene Fubara-Manuel with “Leave to Remain: The Biopower of Migration Algorithms and Data Structures”, a talk discussing issues related to data-based visa regimes. Moreover, key speaker Jonathan Dewar gave a talk titled “Data Sovereignty”, addressing the concept of First Nations data sovereignty in Canada.

According to the organizers, a particular success of the conference was the successful execution of the hybrid format of the event which enabled an intensive and lively exchange between scientists. In her welcome address co-organiser Jo Bates commented on the hybrid form of the conference: “We calculated that compared to if we had held the conference only in person in Sheffield and everyone was flying in, we have saved ~125 tonnes of carbon just on flights.”

The next Data Power Conference is expected to take place in 2024.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

Welcome to The DSC, Heike!

Svenja Goers — Mon, 04 Jul 2022 11:00:00 +0200

Heike Thöricht received her pre-diploma is sociology at the University of Bamberg in 2005, followed by a diploma in sociology at the University of Hamburg in 2008. Subsequently, she worked as a Consultant and Consumer Insight Manager. During that time, she also engaged with data-driven projects and topics from the field of social sciences. Before Heike joined the DSC, she worked at the University of Innsbruck where she was involved in a variety of research data management (RDM) initiatives such as “e-Infrastructures Austria Plus”, “Austrian Data Lab and Services” and “FAIR Data Austria”. There she contributed to work packages focused on topics like data life cycles, RDM-policies, data repositories, data management plans and data trainings. Since March 2020 she also worked as a coordinator and adviser for digital research services, supporting scientists with RDM topics and developing systems and tools for researchers.

From now on Heike will work as one of three Data Stewards who have joined the DSC this summer. Together they will support researchers from the University of Bremen and the U Bremen Research Alliance Institutes with implementing the FAIR principles. Here, Heike’s focus will lie on social sciences and humanities. Her tasks will include activities such as providing specialist advice to scientists and assisting them with the handling of research data, planning and conducting targeted Data Literacy Trainings as well as developing efficient data management processes.

We are happy to welcome Heike to our team at the DSC and look forward to working with her!

Contact:

Dipl.-Soz. Heike Thöricht
Data Steward
E-mail: thoerich@uni-bremen.de

Click here to visit Heike's Profile

Contribution to The SKILL 2022 Student Conference

Christopher Metz — Mon, 20 Jun 2022 11:00:00 +0200

With his submission “Automatic transformation of multilingual language input into database queries” Marcel Franzen published the research results from his bachelor thesis, which was conducted as joint project at the Working Group Computer Architecture at Faculty 3 (AGRA ) and the Data Science Center in the winter semester 2021/2022 (We reported here).

His results are now accepted in edited form at the Student Conference on Computer Science (SKILL) 2022 (https://skill.gi.de/) and will be presented there by Mr. Franzen on September 29/30, 2022. The SKILL is organized for the 12th time by the “Gesellschaft für Informatik” and addresses all computer science students. Theses, projects or seminar papers can be submitted as short papers (4-6 pages) or full papers (10-12 pages). The selection process is done by peer review, as usual in science.

We congratulate Marcel on his first scientific contribution.

Are you interested in writing a thesis with us?

Please contact:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Welcome to The DSC, Sandra!

Svenja Goers — Wed, 01 Jun 2022 11:00:00 +0200

Sandra Zänkert completed her Diploma in Psychology at the Technical University of Dresden. Subsequently, she worked at the Chair of Medical Psychology, Psychological Diagnostics and Research Methodology at the University of Regensburg. There she was involved both in research and university teaching activities in the fields of medicine and psychology. In her area of expertise, psychobiological stress research – an interdisciplinary field combining natural, social and health sciences – Sandra has worked with a variety of different data formats. These include, for instance, questionnaire research data as well as data from fields such as physiology, genetics and endocrinology. Most recently, she was involved in a DFG project investigating psychobiological stress regulation in aggression during which she contributed data to a research project investigating language-based detection of physiological markers of stress using machine learning. In 2022 Sandra completed her PhD in Biological Psychology on methodological aspects of two standardized laboratory paradigms applied in stress and anxiety research.

As an early career researcher, Sandra is actively involved in the German Society for Psychology (DGPs). Here, due to the so-called replication crisis in psychology, open science, as well as reproducibility and sustainability in the research process, have been a major topic over the past few years. Moreover, Sandra is also a member of the Society for the Improvement of Psychological Science (SIPS) and the Interest Group for Open and Reproducible Science (IGOR).

From now on, Sandra will work as one of three Data Stewards joining the DSC this summer. Together they will support researches from the University of Bremen and the U Bremen Research Alliance Institutes with implementing the FAIR principles. Here, Sandra’s focus will lie on natural sciences and especially health science. Her tasks will include activities such as providing specialist advice to scientists and assisting them with the handling of research data, planning and conducting targeted Data Literacy Trainings as well as developing efficient data management processes.

We are happy to welcome Sandra to our team at the DSC and look forward to working with her!

Contact:

Dr. Sandra Zänkert
Data Steward
Tel. +49 (421) 218 - 63957
E-Mail: sandra.zaenkert@uni-bremen.de

Click here to visit Sandra's Profile

RDM-Special Edition in The Data Science Forum

Lena Steinmann — Tue, 31 May 2022 11:00:00 +0200

With the RDM-Special Edition of our seminar series, we would like to show researcher the various services and activities at the University of Bremen that can help to implement a sustainable, FAIR data management during the proposal as well as research phases. Moreover, CRC 1342 is going to present its RDM activities as an example for other collaborative research projects. We would also like to take the opportunity to introduce the new RDM-services offered by our three new data stewards, who will have joined the DSC by the beginning of July.

All Events

12-12:30 pm via Zoom, 12-13 pm on Campus

09.06.2022 | Dr. Martin Blenkle (Staats- und Universitätsbibliothek)
Bibliothekar:innen lesen gar nicht den ganzen Tag über! FDM in der Staats- und Universitätsbibliothek Bremen
16.06.2022 | Dr. Björn-Oliver Schmidt (Referat 12, U Bremen)
Wohin mit meinen Daten? FDM an der Universität Bremen – Unterstützungsangebote und Rahmenbedingungen
23.06.2022 | Dr. Nils Düpont (SOCIUM & CRC 1342)
Getting Social Scientists Onboard – Co-Creating an Information System (and Doing RDM) in the CRC 1342 “Global Dynamics of Social Policy”
14.07.2022 | Dr. Julian Lilkendey, Heike Thöricht, Dr. Sandra Zänkert (Data Stewards, DSC)
What can a data steward do for you? Discipline-specific RDM support and training

Why an RDM Special Edition?

FDM is important for all data-intensive researchers, as it is the foundation for data science. Also, more and more funding agencies require concrete information on data management in third-party funding applications. The DFG has also recently specified its requirements in this regard and is now making information on the handling of research data in collaborative and individual proposals mandatory (see DFG-news item from March 14 ). A sustainable RDM strategy is thus crucial for the success of proposals and research projects, and the U Bremen offers various support services.

Where and When?

The lunch-and-learn event will take place in hybrid format from 12-12:30pm at MZH and via Zoom. There will be a 20-minute keynote presentation followed by an open forum for questions and discussion. We have planned an extra half hour on site (i.e. until 1 p.m.) for personal exchange on the talk, general data science aspects or our services. If you would like to be present on site at the MZH, just write us a short EMAIL for better planning. We look forward to exciting discussions!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

Welcome to The DSC, Julian!

Svenja Goers — Mon, 16 May 2022 11:00:00 +0200

As the first of three Data Stewards, Dr. Julian Lilkendey will from now on support scientists with the management of research data. Julian Lilkendey completed his pre-diploma in biology at the Ludwig-Maximilian University of Munich (2009), followed by a diploma in biology at the Christian-Albrechts University of Kiel in 2013. In 2018 he received his doctorate from the Leibniz Center for Tropical Marine Research (ZMT) at the University of Bremen. In his dissertation, he investigated the reproductive adaptations of a tropical herring species (Ethmalosa fimbriata) to hydrographic changes in their spawning habitats in the context of climate change. After the completion of his doctorate, he stayed at the ZMT for several years, during which he worked as a coordinator for the DatAlumni project and as a project manager for the AANChOR project.

From now on, Julian will work as one of three Data Stewards who will complement the DSC this summer. Together they will support researchers from the University of Bremen and the U Bremen Research Alliance Institutes with implementing the FAIR principles. Julian’s tasks will include activities such as providing specialist advice to scientists and assisting them with the handling of research data, planning and conducting targeted data literacy trainings, as well as developing efficient data management processes.

We are happy to welcome Julian to our team at the DSC and look forward to working with him!

CRC 1342 is Looking For a Software Developer (f/m/d) in Close Cooperation With The DSC

Lena Steinmann — Mon, 25 Apr 2022 10:00:00 +0200

The University of Bremen invites applications for the following position – under the condition of job release –

Software Developer (f/m/d) for Research Software

To be filled as soon as possible. This is a full-time permanent position (TV-L 13).

The University of Bremen is committed to a policy of providing equal employment opportunities for both men and women alike, and therefore strongly encourages women to apply for the position offered.

Job Description

Developing software to support scientific research processes and making research data available long-term are core tasks at the University of Bremen. The position is initially part of the Collaborative Research Center CRC 1342 (Global Dynamics of Social Policy) for continuing the development of the leading Global Welfare State Information System (WeSIS).

In the past four years, the web-based information system was designed and developed to help social policy researchers organize their data collection and analyses. The system is tailored to the needs of a large and very diverse group of researchers and is planned to be released to the scientific community in 2024.

Based on the elicited design requirements, the system includes algorithmic solutions that support the researchers in semi-automatic data validation, storage, exploration, and sharing (socialpolicydynamics.de/projects/information-management-project/en/).

The project in the CRC 1342 is currently organized until 2025 and there is an extension planned until 2029, to be focused on research transfer and the release of the system to the general public. Afterward, the position will be taken over by the central IT-service area of the University of Bremen.

Your Tasks

Your tasks will be improving and extending the existing web-based information system. The main goal will be working towards the system launch to the scientific community in 2024. In addition, you will implement new system features, with a focus on data analysis and visualization tools, as well as maintain and improve the existing features. The web-based information system is already being used by the social science researchers and stores more than a thousand datasets collected by them.

What do we offer? You will work in an interdisciplinary and international team of scientists and technicians. You will work closely with the leading professors of the team. Moreover, you will work on innovative topics to support scientific work in cooperation with software developers from other faculties and with the Data Science Center of the University of Bremen. In doing so, you will have contact with diverse scientific topics from the social policy and computer science fields.

Your Profile

You have a completed university degree (Master, Diplom or comparable degree) preferably in computer science, business informatics or in a related field with proven expertise in web software development.
You have experience working with HTML, CSS and JavaScript.
You have experience working with relational databases (PostgreSQL or equivalent).
You have experience on the fields of data science or information visualization.
You have a very good command of spoken and written English (C1).
You have knowledge in participative software development.

In addition to the ability to work constructively in a team, you place particular value on user-centered work. You work independently, in a structured and problem-solving manner. Furthermore, you bring along communicative skills as well as the ability to think conceptually and analytically.

General Hints

The University of Bremen offers a family-friendly working environment. Disabled applicants will be given priority if their professional and personal qualifications are fundamentally equivalent. Applications from persons with migration background as well as international applications are expressly welcomed.

If you have any questions regarding the position, please contact Prof. Dr. Andreas Breiter (abreiter@uni-bremen.de).

Applications should be submitted up until May 17th, 2022 with the reference number A126/22 to the following address:

Universität Bremen
Dezernat 2 Personalangelegenheiten
Postfach 33 04 40
28334 Bremen

We ask you to please send us document copies only because we cannot return anything.

Kontakt

Prof. Dr. Andreas Breiter
+49 (421) 218 - 56571
E-Mail: abreiter@uni-bremen.de

We Are Looking For Student Support in Our IT!

Lena Steinmann — Thu, 10 Mar 2022 12:00:00 +0100

Only available in German.

Kontakt

Fragen beantwortet:
Christopher Metz
+49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

Link Job Offer

The DSC Funds a Data Science Project in The Social Sciences

Thu, 10 Mar 2022 10:00:00 +0100

The goal of the project “The origins of expertise: Where does IO-knowledge originate from?” is to understand the origins of expertise of education-related international organizations, taking the Organization for Economic Co-operation and Development (OECD) as an example. This will enable an examination of the hitherto unchallenged expert status of international organizations with regard to education reforms. More specifically, the aim is to identify the source of the knowledge base for the expertise of these influential organizations. For instance, do they use results from current research or do they repeatedly refer to their own research results or use only few central documents?

To understand this, an automated text analysis method for extracting citation information from PDF documents will be developed and initially apllied to the OECD. This procedure will be standardized and serve as a basis for follow-up studies in which other international organizations shall be analyzed and compared.

The study is linked to the Project A05: The Global Development of Coverage and Generosity in Public Education (project directors: Kerstin Martens, Michael Windzio) of CRC 1342: Global Dynamics of Social Policy .

Funding recipient:

Dr. Helen Seitzer
Faculty 8 – Social Sciences
SOCIUM – Research Center on Inequality and Social Policy
seitzer@uni-bremen.de

Funding period:

1st June 2022 - 31st December 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC supports the technical advancement of the “Platform Governance Archive”

Mon, 17 Jan 2022 11:00:00 +0100

The first DSC Seed Grant in 2022 goes to Christian Katzenbach and Dennis Redeker for the advancement of the Platform Governance Archive (PGA) data repository. The PGA enables users (researchers, regulators, journalists) to critically examine rules and policies of social media platforms (e.g. community guidelines, terms of service, privacy policy) via an appealing interface and the possibility to view substantial changes of the rules and policies over time.

As part of the project, a technical and organizational modification of the techniques for detecting changes in the rules of social platforms (Facebook, Twitter, YouTube, Instagram) will be carried out in close cooperation with the Open Terms Archive (OTA). The goal is to ensure sustainable collection and preservation of the data.

Funding recipients:

Prof. Dr. Christian Katzenbach (Faculty 9 – Cultural studies, ZeMKI – Centre for Media, Communication and Information Research)

Dr. Dennis Redeker (Faculty 9 – Cultural studies, ZeMKI – Centre for Media, Communication and Information Research)

Funding period:

1st February 2022 - 31st January 2023

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC Supports The Organization of The Hybrid “Interactive Sonification Workshop” (ISon 2022)

Mon, 20 Dec 2021 12:00:00 +0100

The Interactive Sonification Workshop (ISon 2022) takes place on September 22-23 as hybrid event at the Hanse-Wissenschaftskolleg (HWK) in Delmenhorst. Sonification is the presentation of data using intelligible sound, e.g., for monitoring complex processes, or assisting exploration of and navigation through data spaces; i.e., it is a sub-discipline of data science. Tim Ziemer is the main organizer of the ISon 2022 co-organized by Thomas Hermann and Roberto Bresin.

The DSC Seed Grant will be used to organize and implement hands-on tutorials at ISon 2022 on Sonic-Tilt , the open-source version of Tiltification , the impactful spirit level sonification app for Android and iOS developed by the students of the masters project “Sonification Apps”.

Funding recipient:

Dr. Tim Ziemer (Faculty 3 – Mathematics and Computer Science; Bremen Spatial Cognition Center (BSCC))

Funding period:

1st April 2022 - 31st October 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC Supports The Hybrid Data Power Conference 2022

Mon, 13 Dec 2021 10:00:00 +0100

The DSC Seed Grant was awarded for the ninth time. In this project, we support the implementation of the fourth Data Power Konferenz , an international conference bringing together scientists from various disciplines to discuss issues of socially responsible datafication. The conference will take place online and on-site in Sheffield, Carleton, and Bremen from June 22-24, 2022. DSC member Juliane Jarke is part of the six-member Data Power Conference Management Team.

Funding recipient:

Dr. Juliane Jarke (Faculty 03 – Mathematics and Computer Science)

Funding period

1st December 2021 to 24th June 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC Funds a Study to Develop an App That Helps People With Cognitive Impairments

Tue, 26 Oct 2021 10:00:00 +0200

In the data-driven pilot study “Accessible Text App”, the team around Hendrik Heuer will further develop a prototype smartphone app. The central function of this app is the summary of texts and explanation of terms for people with impairments and non-native speakers, thus enabling more accessibility in everyday life for the affected people.

The project uses various data science techniques such as machine learning or web scraping to address an important societal challenge. In addition, the focus on cognitive impairments addresses a key research gap in the field of human-computer interaction.

Funding recipients:

Dr. Hendrik Heuer (Faculty 3 – Mathematics and Computer Science)

Prof. Dr. Andreas Breiter (Faculty 3 – Mathematics and Computer Science)

Funding period:

1st January 2022 - 31st July 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

With Machine Learning to Green IT

Tue, 08 Mar 2022 10:00:00 +0100

In the paper “ML-based Power Estimation of Convolutional Neural Networks on GPGPUs”, our research associate Christopher Metz, in cooperation with Mehran Goli (DFKI), has developed an approach to determine the power consumption of GPGPUs, when running Convolutional Neural Networks (CNNs) in early stages of development.

The work improves on the methodology of previous studies published by the authors at the DATE Friday Workshop System-level Design Methods for Deep Learning on Heterogeneous Architectures (we reported »here) and the International Conference on Hardware/Software Codesign and System Synthesis (we reported »here).

With the new approach it is possible to determine the power consumption of a Convolutional Neural Network on a General Purpose Computing on Graphics Processing Unit (GPGPU) using “only” seven predictors. This makes it possible to determine the power consumption without having to run the neural network on a real graphics card.

The work was done in cooperation with the Cyber-Physical Systems group of DFKInBremen and will be presentedat the 25th IEEE International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS) (ddecs2022.fit.cvut.cz) held in Prague from 06.04. to 08.04.2022. Other authors are Dr.-Ing. Mehran Goli (DFKI/University of Bremen) and Prof. Rolf Drechsler (University of Bremen/DFKI).

About DDECS:

The International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS) provides a forum for exchanging ideas, discussing research results, and presenting practical applications in the areas of design, test, and diagnosis of microelectronic digital, analog, and mixed-signal circuits and systems.

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

We are looking for student support!

Wed, 23 Feb 2022 10:00:00 +0100

Only available in German.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Christopher Metz on his research at the DSC

Thu, 06 Jan 2022 12:00:00 +0100

What topics are you currently working on in your research?

I am interested in building data science and machine learning systems. One major challenges is to pick the right device for applying trained AI models. It becomes critical in the areas of edge computing and IoT (Internet of Things) were tight power and performance constrains exists.
Furthermore, I am also interested in the topic of High-Performance Computing (HPC) systems for training such algorithms. I always try to improve the infrastructure of the Data Science Center. However, in my PhD research I am focusing more in the power and performance estimation on edge and IoT devices than on the High-Performance Computing for training.

How important is data to your research?

In general data is very important for me because I am using most time machine learning methods. Unfortunately, there are no public research data I can use. Hence, I need to create my own training data. This is often a time intensive process. I am looking forward to the development of open data and FAIR research data management to solve this kind of issues.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

Most time I am using machine learning methods which are a subclass of data science techniques. So, I would say data science is important to my research. Moreover, I am working on hardware and IT architectures for data science/ML. I would call myself more of a Data/System Engineer who builds infrastructures and supportive platforms for data scientists.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

Currently, I am focusing on power and performance estimation for neural networks on different devices. This makes – obviously – neural networks important to me. Moreover, I am applying methods like regressions or clustering methods on my data. This makes algorithms like K-Means, K-Nearest Neighbors and many more also important.

What are your main challenges in dealing with data?

My main challenge is to get the data. Due to the fact, that there are no available public data I need to execute benchmarks on different devices and create my own data. This is time and cost intensive. We do not have all devices available and it is not manageable to buy a device only for this purpose.
Another challenge is to get the data into a good shape and find the important features for training. We can collect dozens of attributes during our benchmarks but do not know which have a high impact to our output.

And finally, what is your personal motivation for joining the Data Science Center?

I applied for the role at the Data Science Center because I saw the opportunity to build a whole new platform and infrastructure for researchers. In my former job, I have always told people we need a group of experts to handle infrastructure and services for data science/AI applications for other researchers who are not into computer science. Since this is one of the things we do at DSC, I am very happy to be a part of it for almost two years now!
Furthermore, the DSC offers the opportunity to work on my PhD thesis which was not that easily possible at my former job.
I am looking forward to work in interesting and highly innovative projects at the DSC with all the different researcher of the Uni Bremen.

You can learn more about Christopher’s activities and the DSC infrastructure in his talk “Do you pick the right device for data science?“ in the Data Science Forum on 13.01.2022.

Interviewee:

Christopher Metz, M.Sc.
Research Associate at DSC
FB 03 – Mathematics and Computer Science
cmetz@uni-bremen.de

Additional links:

Christopher Metz’ DSC Profile

Christopher Metz in the Data Science Forum (13.01.22)

We Are Hiring!

Lena Steinmann — Tue, 04 Jan 2022 10:00:00 +0100

As part of the Data Science Center, you will support researchers at the University of Bremen and in the U Bremen Research Alliance in research data management following the FAIR principles (link to full job advertisement ). We offer three positions as Data Stewards (m/f/d; 13 TV-L, 100%) or a period of 3 years starting as soon as possible who will work closely together, each focusing on supporting one of the following research areas:

(1) Natural sciences and engineering
(2) Social sciences and humanities
(3) Health sciences and marine sciences

Your application should clearly indicate which of the three research areas aligns best with your interests and competencies.

The opportunity to acquire scientific skills in the areas of project management, science management and data management is given.

If you are keen to work as part of an interdisciplinary team on innovative topics and to actively shape the data culture of tomorrow, , then apply here by 16.02.2022.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

A New Approach to Simplify The Use of Databases For Everyone

Christopher Metz — Wed, 22 Dec 2021 12:00:00 +0100

In the past decades, large amount of data has been generated that needs to be stored. For this reason, modern databases are a fundamental innovation to store data, and easily read and then use them profitably. However, since most people lack knowledge of database languages such as SQL, a barrier exists that prevents them from fully harnessing the potential of databases. In a bachelor thesis at the DSC, an approach was developed that is based on the use of natural language processing and machine learning to enable the use of databases for everyone.

In Marcel Franzen’s bachelor thesis “Implementation of an automatic transformation of multilingual language input into database queries” (original title “Implementierung einer automatischen Transformierung multilingualer Spracheingaben in Datenbankabfragen”), a novel approach is presented that extends already existing approaches with respect to multilingual usage, so that input in different languages achieves the same results. Accordingly, end users with little or no knowledge of SQL can generate database queries.

Mr. Franzen uses word embeddings for natural language processing (NLP) in his work, which are words encoded as vectors. The vectors from different languages are arranged in their own vector space. The vector spaces are transferred into a common vector space. Thus, on the one hand, the vectors of words are close to each other, which have a high semantic similarity. On the other hand, the same words in different languages also have a high similarity with respect to their word embeddings.
With the help of these properties, questions can be addressed to a database in German as well as in English, which are then converted into corresponding SQL queries. For this purpose, the question as well as the names of the table columns are transformed into a corresponding vector representation by word embeddings, which are then further processed by neural networks. Various smaller models are used to predict individual parts of the SQL query, resulting in a complete SQL query. Due to multilingualism, the language of the queries, may differ from the language of the table columns. Furthermore, this makes the language of the dataset used to train the models irrelevant.

Question: What is Terrence Ross nationality?

Tabelle: player, nationality, position, years in Toronto, team

SQL-Query: SELECT nationality FROM table WHERE player = ‘terrence ross’

This research is a joint work with the AGRA group of Department 3, as well as the Data Science Center. It was submitted as a bachelor thesis at the University of Bremen.

We congratulate Mr. Franzen on passing his colloquium and wish him continued success in his professional and private life!

Are you interested in writing a thesis with us?

Please contact:
Dr. Lena Steinmann
DSC Koordinatorin
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

New Publication by Two DSC Team Members

Katharina Soemer — Fri, 31 Dec 2021 10:00:00 +0100

Following the DINI/nestor workshop „Data Stewardship in Research Data Management – What is it? Roles, task profiles, areas of application“, which took place virtually on November 16 and 17, 2020, Lena Steinmann and Rolf Drechsler published an article on the linkage of data science and data stewardship in the journal Baussteine Forschungsdatenmanagement. The article was published in German.

Translated abstract: Data science allows us to extract knowledge from complex, high-dimensional data and is therefore regarded as a key discipline of our time and a central element of data-intensive research. Well-curated, FAIR data, form the basis for this, ensured by sustainable research data management and data stewardship. Accordingly, a close coordination and systematic interlinking of data science and data stewardship in the research process promises a significant increase in efficiency and maximum added value from data. The Data Science Center (DSC@UB) of the University of Bremen, which supported by the State of Bremen, offers ideal boundary conditions for this. As a central, interdisciplinary infrastructure for data-intensive research, it serves as a place for interdisciplinary exchange and provides essential services to support researchers. In addition, at the DSC data scientists and data stewards can can work closely together to jointly support scientists throughout the entire data life cycle and in close cooperation. This should ensure (1) the availability of FAIR data, (2) maximum knowledge gain from data, and (3) the sustainable optimization of data-handling processes and procedures, thereby creating new opportunities for innovation in the research process.

In that context, we are very happy to announce that we are now hiring three data stewards at the Data Science Center in close collaboration with the U Bremen Research Alliance to further advance the integration of data science and data stewardship. You can find the job advertisement here .

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Michael Windzio on His Data-Based Research in Sociology

Mon, 13 Dec 2021 10:00:00 +0100

What topics are you currently working on in your research?

I am working on social networks of adolescents in school classes, in particular on the integration of immigrants into these networks, and on social cohesion and social milieus. Another focus is on global networks of migration and student mobility, and diffusion of education policy. Moreover, I work on juvenile delinquency, adolescents’ gender role orientations, residential relocations of families and residential segregation, and on global educational inequalities

How important is data to your research?

Data is crucial for my research.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

I am still wondering what “Data Science” actually means. Is it limited to Bayesian approaches and machine learning? Or does it also include the standard approach to quantitative analysis in the social sciences? Does it include generalised regression, cross-sectional and longitudinal, as well as econometrics? If so, then data science is at the core of my work.
Anyway, I am definitely a user.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

I use longitudinal methods for network analysis, event history analysis (= hazard models), panel regression, multilevel analysis (= mixed models), but also models for causal inference for observational data, such as propensity score matching. In my field, sociology, “computational social science” is rapidly growing, but again, this label is rather vague. But methods of text analysis, such as topic modelling, will certainly become more important also in my work.

What are your main challenges in dealing with data?

I currently do some time-consuming analyses, e.g. a Bayesian model for network evolution over time. Maybe the Data Science Center can provide a better hardware infrastructure to reduce computation time.

And finally, what is your personal motivation for joining the Data Science Center?

It is interesting to see which methods people from other disciplines apply. Hopefully, there will be some dissemination of knowledge, e.g. by workshops on methods we are interested in.

Mehr zu Michaels Tätigkeiten erfahren Sie am 16.12.2021 in seinem Beitrag „Global cultures and the world-wide gender gap in education – Fuzzy clusters and multilevel data structures“ im Data Science Forum.

Interviewee

Prof. Dr. Michael Windzio
Professor of Sociology of Migration and Urban Research
FB 08 – Sociology
Head of the department „Methods Research“ at SOCIUM
E-Mail: mwindzio@uni-bremen.de

Hedrik Heuer on Machine Learning And Human-Computer-Interaction

Thu, 25 Nov 2021 12:00:00 +0100

What topics are you currently working on in your research?

I’m a computer scientist working at the intersection of machine learning and human-computer interaction. In my dissertation, I provide a socio-technical perspective on ML-based curation systems like YouTube’s recommendation system. My thesis examines how users and practitioners make sense of such ML systems. In the thesis, I provide actionable insights on how ML-based curation systems can and should be explained and audited. As a Postdoc, I now examine how algorithmic regimes shape science. I also develop tools against disinformation and leverage ML techniques to help people with disabilities.

How important is data to your research?

For me, machine learning is a novel programming paradigm in which decisions are inferred from data. In almost all of my work, I either study or apply such machine learning. Therefore, data is central to my research. In an upcoming paper, we will even argue why data-based automation is a much more precise term than machine learning because neither the term machine nor the term learning really captures how ML algorithms leverage data to infer decision rules.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

I see myself primarily as an HCI researcher. As the title of my dissertation “Users & Machine Learning-based Curation Systems” illustrates, I investigate the whole socio-technical system. On the technical side, this includes input data, ML algorithms, inferred models, and output data. On the social side, I study providers of data, ML practitioners, auditors, the organizations that operate a system as well as the primary, secondary, and tertiary users of a system. Im inspired by Adrian Mackenzies wonderful book “Machine Learners – Archeology of a Data Practice”.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

In the past, I have been primarily interested in supervised machine learning. Before I started my doctoral studies in Bremen, I worked as a deep learning researcher in Amsterdam. Thanks to a grant awarded by the Data Science Center, I will be able to apply data science techniques to automatically recognize text in images and to summarize this text for people with disabilities. I am also interested in using these techniques to help people recognize misinformation and fake news. I do not necessarily think that such tasks can be fully automated, but I think better tools to search and analyze text are needed.

What are your main challenges in dealing with data?

The biggest problem is finding enough time for all my ideas. Apart from that, obtaining high-quality labeled data is a big challenge.

And finally, what is your personal motivation for joining the Data Science Center?

I had the pleasure of working closely with my colleagues in the CRC 1342 on WeSIS, the Welfare State Information System. Our goal is to empower social scientists to use machine learning and other data science techniques to their advantage. During that time, I saw how much exciting work in this space is already happening in Bremen. The Data Science Center is the place where all these researchers come together to discuss data science and machine learning.

You can learn more about Hendrik’s activities in his talk “A Socio-Technical Perspective on the Potentials and Perils of Machine Learning“ in the Data Science Forum on 02.12.2021.

Interviewee

Interviewpartner:
Dr. Hendrik Heuer
Postdoc @ Information Management WG & ifib
FB 03 – Mathematics and Computer Science
ZeMKI Member
E-Mail: hheuer@uni-bremen.de

The Application of Data Science Methods in Material Sciences

Wed, 10 Nov 2021 10:00:00 +0100

What topics are you currently working on in your research?

I am using quantum chemical atomistic simulations in order to understand catalytic reactions at surfaces, to predict promising new functional materials or to determine the atomic structure of new unknown compound.

How important is data to your research?

Data is very important in my field. First of all, a lot of calculations are needed e.g. when the catalytic mechanisms of a chemical reaction needs to be understand. These calculations will generate terabytes of output data. The benefit of the renewed interest in Machine Learning is that the community now starts to utilize this data in order to speed up calculations or make predictions in complementary research.
I am currently working on a new method, where we in cooperate experimental data to our quantum chemical calculations. For this project, we are dependent on experimental data from others.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

I am a mix of a user and a method developer. I want to answer questions that arise from some experimental findings. If a helpful code is already available, I am using this instead of spending time to develop something similar. Nevertheless, in most cases one has to modify an existing code in order to be able to use it probably. In addition, I am writing my own codes or parts of the code, if needed.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

Currently I am using and working on two different projects were we develop and use on-the-fly trained machine learning (ML) models to drastically speed up our quantum chemical calculations. Currently we are focusing on using a Gaussian Process but might use neural networks in the near future. In one project the ML model is used to speed up a global optimization in the framework of an evolutionary algorithm. In the second project we are using the ML model in order to speed up calculations of numerical second, third and fourth derivatives.

What are your main challenges in dealing with data?

Since I am mostly preparing the data myself, the main challenge is to have access to computational resources. A few hundred to a few thousand CPU cores are needed on a daily basis.
In addition, the in cooperated experimental data needs to have a high quality and “noise” needs to be avoided.

And finally, what is your personal motivation for joining the Data Science Center?

I am a quantum chemist/material scientist that had the opportunity to learn a little bit about machine learning. I am able to develop new codes, but of course a person who learned data science already as a student might have a deeper knowledge and complementary ideas of how an effective code could look like. Therefore, I was joining the Data Science Center in order to find potential cooperation partners that would be interested in starting research projects together.

Thank you very much for the insights into your research in this interview, Wilke!

Interviewee

Dr. Wilke Dononelli
Senior Postdoc @ Hybrid Materials and Interfaces AG
Early Career Investigator @ MAPEX
FB 04 – Production Engineering
E-Mail: wido@uni-bremen.de

We're looking for student support!

Mon, 15 Nov 2021 15:00:00 +0100

Still looking for a student job to kick off the semester? 🚀👀

We are hiring a motivated student assistant (m/f/d) to start as soon as possible, for up to 38 hours per month.

The position is flexible, long-term, and offers insight into an exciting working environment. (Please note: German skills are required)

We look forward to receiving your application!

You can find all details on how to apply here

If you have questions about the position, please contact:

Dr. Lena Steinmann
DSC coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Online Discussion Round: "NFDI - Neue Perspektiven in der kooperativen Wissenschaft!"

Fri, 10 Jul 2020 12:00:00 +0200

On September 9th at 6 pm, the U Bremen Research Alliance (UBRA) will host a moderated online discussion on the topic "Nationale Forschungsdateninfrastruktur (NFDI) - Neue Perspektiven in der kooperativen Wissenschaft!". Together with the participants, the panel will discuss the activities of the NFDI as well as the opportunities and challenges that arise for science through sustainable research data management. The discussion will be driven by the question:

Is data archiving and availability in a national and international context going to lead to more cooperative science and an increase in knowledge?

The panel is composed of research experts, former members of the "Rates für Informationsinfrastrukturen" (RfII) and representatives of the NFDI. The Data Science Center will be represented by our spokesperson Prof. Dr. Rolf Drechsler, who will participate in the discussion together with Prof. Dr. York Sure-Vetter, Prof. Dr. Iris Pigeot, Prof. Dr. Frank-Oliver Glöckner, Sabine Grünger-Weilandt, and Jan-Martin Wiarda as moderator. The discussion will take place online via zoom. Questions and contributions to the discussion can be submitted via a chat system.

Current Research at DSC: Early Estimation of Power Consumption of Neural Networks on GPUs

Mon, 11 Oct 2021 15:00:00 +0200

In the paper “Work-in-Progress: Early Power Estimation of CUDA-based CNNs on GPGPUs”, our research associate Christopher Metz in cooperation with Mehran Goli (DFKI) developed an approach to estimate the power consumption of GPGPUs when executing Convolutional Neural Networks (CNNs), in early phases of development.

In their study, the authors provide first results on their method presented in the previous paper “Pick the Right Edge Device: Towards Power and Performance Estimation of CUDA-based CNNs on GPGPUs” (we reported »here). They managed to predict the power consumption with an absolute error of up to less than 1%. The best result was obtained for a RESNET variation with an absolute error of 0.73%. This compares to the worst result with an absolute error of 15.75% for the Densenet201. This results in an average absolute error of 8.3%. The large variation can be attributed to an unbalanced training data set. This contains more variations of the RESNET than for the Densenet. To improve the results, the authors are working on optimizing the training data set.

To estimate the power consumption, they trained a simple neural network. The neural network receives the instructions that the GPGPU executes as well as important hardware components of the GPGPU as input. The output of the neural network is the power consumption. One aim is to integrate the completed model into a compiler extension so that system designers in the future can determine the power consumption of artificial neural networks at an early stage. This could make the selection process more cost effective and environmentally friendly in the future.

The work was done in cooperation with the Cyber-Physical Systems group of DFKI at Bremen and was submitted and presented at the International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) (esweek.org/codes-isss/). Further authors are Dr.-Ing. Mehran Goli (DFKI/University of Bremen) and Prof. Rolf Drechsler (University of Bremen/DFKI).

About CODES+ISSS:

The International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS) is the premier event in system-level design, hardware/software co-design, modeling, analysis, and implementation of modern Embedded Systems, Cyber-Physical Systems (CPS), and Internet-of-Things (IoT), from system-level specification and optimization to system synthesis of multi-processor hardware/software implementations. The conference is a forum bringing together academic research and industrial practice for all aspects related to system-level and hardware/software co-design.

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

DSC Seed Grant Paves The Way For New Third-Party Project

Fri, 01 Oct 2021 13:00:00 +0200

The Hans Böckler Foundation supports Prof. Dr. Lars Hornuf’s and Dr. Ass. Jur. Sonja Mangold’s new research project on „Platform work and data protection in a national and international perspective: market players, problem areas, regulatory requirements“ with more than 200,000 euros. The duration of the project, which is carried out in cooperation with the Hugo Sinzheimer Institute for Labor and Social Law, is 36 months. As part of the project, the scholars conduct joint empirical and legal research on how data protection issues are dealt with in the crowdworking and gig working market in China, Germany, and the USA. Based on the findings, policy proposals on data protection for platform work are developed, which address in particular national and European legislators.

The funding of a book project on the analysis of selected data protection issues in crowdsourcing transactions through the DSC Seed Grant in winter 2020 provided the foundation for the approved third-party project (learn more »here; only available in German).

We congratulate Lars Hornuf and Sonja Mangold and are looking forward to the results of the project!

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The Practical Application of Autoencoder in Modern Dimension Reduction of Data

Thu, 30 Sep 2021 12:00:00 +0200

In the bachelor thesis of Kien Vinh Luc “Autoencoder for dimension reduction of data in empirical asset pricing model ”, under supervising from Prof. Dr Rolf Drechsler and M. Sc Christopher Metz from Data Science Center, and PD. Dr Christian Fieberg in the field of empirical capital market research, a new practical approach that optimizes the efficiency and improves the performance of the machine learning model by representing the original high dimensional data space in a simplified, lower-dimensional subspace but still maintain its informative pattern was presented.

The full big data explosion has provided us with more and more information about every problem in our society and industries, especially in finance. The global financial crisis and European debt crisis have highlighted the importance of understanding the rich and multivariate underlying in the financial entities, economies and markets. While it is true that the collected high dimensional data will help the machine learning model to learn more and explore patterns in generalizing the data, it also leads to an indiscriminate problem of low-quality data and input, highly complex and correlated, which results in a significant amount of redundancy in data and may expose the risk of anomalous predictability, identifiability, instability and overfitting. Therefore, it is crucial to reduce the data dimensionality to estimate how informative each feature in the dataset is and if needed, to remove it but still maintain the structure of the data.

Mr. Luc used Autoencoder (AE) in his work to reduce the dimension of a stock asset dataset. An Autoencoder learns an approximation to identify function so that the output is similar to the input. With the following property, the AE will compress the input X to a smaller latent space representation and then reconstructs the output from the latent space again, in this way we can control and minimize the loss of information as much as possible. We extract the first component of Autoencoder, called Encoder, then integrate it with the empirical asset pricing model to create a new model. By doing so, coming input will be first compressed to a smaller dimension, before feeding into the empirical asset pricing model to perform the machine learning training and prediction as usual. The new transform input in the new proposed structure is the extraction of the most valuable information while eliminating the undesirable redundancy that reduces the efficiency of the model, resulting in improving the prediction performance and also computational time.

The research is a joined work with AGRA Group of Faculty 3, empirical capital market research of Faculty 7 and the Data Science Center. It is submitted as bachelor thesis for the University of Bremen. This new approach of this thesis may be useful and can be applied to solve many types of problems in other industries. The results will be processed for research and might be used in future publications.

We congratulate Mr. Luc for passing his thesis and wish him continued success in his private and professional career.

Are you interested in writing a thesis with us?

Please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC Funds a Project For Exploring Effects of Social Media on Cryptocurrency Markets

Mon, 16 Aug 2021 10:00:00 +0200

The DSC Seed Grant was awarded for the seventh time for a pilot project at the interface of computer science and economics. The aim is to investigate the influence of online discussions on social media platforms on cryptocurrency markets.In particular, the influence of activities of fringe groups, e.g. on Reddit, will be examined, as these serve as incubation chambers for the subsequent dissemination of information in larger mainstream communities such as Twitter, Instagram or Facebook.

To better understand the role of social media platforms and the dissemination of information on cryptocurrencies, the pilot study will include the development of a novel sentiment analysis tool to examine online discussions. The large amount of social media data and its interdisciplinary nature require an interdisciplinary approach. This includes Big Data analysis, Natural Language Processing for sentiment extraction, financial and economic jargon, and complexity theory methods.

Funding recipient:

Muhammad Hassan (Faculty 03 – Mathematics and Computer Science)

Collaboriation Partner: Dr. Muhammad Naiman Jalil (United Arab Emirates University)

Funding period:

1 October 2021 - 30 September 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Services For Teaching And Research at The DSC

Thu, 05 Aug 2021 12:00:00 +0200

The ongoing Corona pandemic has significantly increased the need for online-based services for research and teaching. The courses of Data Train , a central training program for PhD students in research data management and data science offered by the U Bremen Research Alliance, which is supported by the DSC, are also affected by the pandemic. Therefore, the events are currently held in virtual form. In order to ensure a smooth process, the DSC provides the lecturers with three services to facilitate e-learning. All students in a course have access to a browser-based integrated development environment that is independent of the resources of their end devices and has been tested by the lecturers.

The first service is Jupyterhub , which is a server variant of Jupyter . The interface is almost identical to the local Jupyter installation on a notebook and its simple and intuitive working environment makes it particularly user-friendly and easy to learn. Jupyterhub supports a variety of programming languages. The DSC currently providing Python and R.

The second service is Rstudio Server , which is a web version of R Studio. It provides a browser-based integrated development environment for the R programming language, offering a clear user interface with practical functions for easier coding.

The third and last service is Cocalc . Cocalc is a comprehensive development platform designed specifically for collaborative work and educational use. It supports Python, R, Latex, and other languages. In addition, Cocalc includes a chat facility that allows students and teachers to interact, making it particularly interactive.

The virtualization environment of the DSC makes it possible to dynamically adapt the resources for the individual services to the requirements of the users. For example, additional processor cores or memory can be allocated, which increases efficiency compared to working on a personal computer. In lectures, it can also be guaranteed that the same computing capacity is available to every student, almost regardless of the performance of their own device.

The services are currently being tested by lecturers and students. First courses were successfully conducted with Cocalc.

Would you like to learn more about our services or do you already have specific needs?

Then please feel free to contact us:

Dr. Lena Steinmann
DSC Koordinatorin
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

The DSC Funds Interdisciplinary Research Project on Media Usage

Katharina Soemer — Mon, 26 Jul 2021 10:00:00 +0200

The DSC Seed Grant was awarded for the sixth time, this time to the interdisciplinary research team of Prof. Dr. Cornelius Puschmann, Prof. Dr. Andreas Breiter, Patrick Zerrer and Dr. Philipp Krieter. They will conduct a pilot study on the digital media usage behavior of young climate activists of the Fridays for Future (FFF) movement.

As part of the study, the participants install an app, which continuously records the media usage on their smartphone. The participants (N=100) represent the supporters of the FFF movement in terms of age, gender and income. A data-saving sceen tracking app records the usage behavior. The methodological goal of the is to combine a minimally invasive intrusion into privacy with a data collection that has scientific value and to test it in practice.

A key aspect of the project is the combination of traditional methods of empirical social research with novel data science methods. The establishment of the tracking approach as a way of measuring actual media use represents a methodological innovation at the interface of computer science and communication science. The methodological weaknesses of the tracking approach (e.g. a lack of knowledge of the reasons that motivate certain usage patterns) are overcome by applying a mixed-method design. This involves the combination of different methodological approaches (tracking, online questionnaire, automated content analysis and scraping) to gain more detailed insights into the participants behavior. This approach will provide a better understanding of the connection between media use and political action, for example, whether the reception of news on social media mobilizes participation in protests. Data science methods are not only used during data collection but also for data analysis, for example by using text mining methods and innovative statistical approaches.

Funding recipients:

Prof. Dr. Cornelius Puschmann (Faculty 9 – Cultural studies, ZeMKI – Centre for Media, Communication and Information Research)

Prof. Dr. Andreas Breiter ( Faculty 3 – Mathematics and Computer Science, Ifib – Institute for Information Management Bremen, ZeMKI – Centre for Media, Communication and Information Research)

Patrick Zerrer (Faculty 9 – Cultural studies, ZeMKI – Centre for Media, Communication and Information Research)

Dr. Philipp Krieter (IIfib – Institute for Information Management Bremen)

Funding period:

1 October 2021 - 30 September 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links

Information about the DSC Seed Grant

DSC Seed Grant Flyer

The DSC Funds a Data Science Project in Geosciences

Katharina Soemer — Sun, 18 Jul 2021 12:00:00 +0200

The DSC Seed Grant was awarded for the fifth time. The aim of the internationally integrated project led by Dr. Alice Lefebvre from MARUM is to develop a Bedform Analysis Toolbox (BAT). Bedforms – ripples, dunes, sandwaves – are ubiquitous features in sandy subaqueous settings. They exert a major influence on a range
of processes, from small-scale turbulence and sediment transport to large-scale coastal geomorphology.

The open source BAT will combine already available methods to analyse bedforms into one easy-to-use software. In collaboration with international geoscientists and a data scientist, this MATLAB toolbox will be created in the coming months. The toolbox will enable the bedform research community itself, but also non-experts, to examine large bathymetic datasets to characterize bedform properties.

Funding recipient:

Dr. Alice Lefebvre (MARUM – Center for Marine Environmental Sciences)

Funding period:

1st October 2021 - 31st January 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC Funds a Project in Marine Fungi Research

Katharina Soemer — Thu, 01 Jul 2021 11:00:00 +0200

The DSC Seed Grant was awarded for the fourth time for an interdisciplinary project in the fields of chemistry and biology to study marine fungi and their function in the ocean. The aim of the project is to investigate the genetic regulation of degradation processes of two marine fungal isolates and to integrate them into the existing picture of the complex mechanisms of the microbial pump. For this purpose, genome and transcriptome sequencing will be performed.

The generated data will not only provide important new insights into the microbial pump, which has a profound impact on the global carbon cycle and climate, but also enrich existing reference datasets through the quality of the annotated sequences, allowing for higher resolution of further data-based studies.

Funding recipients:

Dr. Marlis Reich (Faculty 02 – Biology/Chemistry)

Prof. Jan-Hendrik Hehemann (Faculty 02 – Biology/Chemistry)

Funding period:

1st July 2021 - 30th June 2022

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Data Science and Research Data Management in Transdisciplinary Physics

Mon, 28 Jun 2021 13:00:00 +0200

What topics are you currently working on in your research?

We focus on structure formation in living matter. We observe single cells of mouse fibroblasts during cell movement as well as the transport network dynamics of the slime mold Physarum polycephalum during foraging. The latter species has become famous in recent years for its problem solving capabilities despite lacking a brain. Physarum and other comparatively simple species, like Hydra or C. elegans, have ignited a new field called basal cognition. We study similarities in collective oscillation patterns in animal brains and the tubular network of Physarum with its peristaltic waves.

How important is data to your research?

As a biological physicist, I’m interested in new physical phenomena and principles of nature from cells to agents and populations or societies. Experimental data are the starting point of our scientific work. They feed our workflows which feedback via theoretical analysis and model building onto experimental design.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

I am speaker of the consortium NFDI4Phys. We develop innovative research data management and provide related services to our communities. Work in the National Research Data Infrastructure has fascinated me and fostered our research. My group members are using artificial intelligence methods in our daily research routines. It has been a rewarding process to align several domains of physics behind the common goal to make data FAIR.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

NFDI4Phys is concentrating on heterogenous data sets. The future standard of the data net will be FAIR digital objects which are kind of digital twins of objects in the real space. FDOs and canonical workflows of research will help us to get our jobs done in all disciplines. I am a member of the semantic working group of the international FAIR DO forum. The advent of Quantum Computing will boost Data Science enormously. However, we need to understand the physics of artificial intelligence and learn to use quantum computers. NFDI4phys has a particular focus in this respect.

What are your main challenges in dealing with data?

The main challenge is to do research data management (RDM) without being a burden to the researcher. RDM needs to become helpful to researchers at all stages of a particular project in order to be accepted by research groups.

And finally, what is your personal motivation for joining the Data Science Center?

It is the principle of Transdisciplinary Physics to engage in deep discussion with colleagues from other disciplines in order to learn their language. DSC Bremen is an ideal platform to foster scientific exchange. I’m most fascinated about the prospects of semantic analysis with AI methods. We will eliminate the qualitative by quantifying it with semantic metrics to boldly go where no own has gone before.

Interview Partner:

Prof. Dr. Hans-Günther Döbereiner
Professor of Biological Physics
FB 01 – Physics and Electrical Engineering
Spokesperson NFDI4Phys
E-Mail: hgd@uni-bremen.de

Juliane Jarke on Data Science in Education And The Public Sector

Thu, 10 Jun 2021 10:00:00 +0200

What topics are you currently working on in your research?

I am currently working on a number of projects that examine the increasing importance of data and data science for decision- and meaning-making in education and the public sector. For example, in the public sector data science is used for prediction, pattern recognition, and scoring across a variety of domains such as social benefit fraud, social work, taxation, policing, job seeker training or immigration. In education, data science is used in educational data mining and learning analytics to predict learning outcomes and student retention. It is important to examine how systems based on data science are embedded in decision-making processes because they co-construct educational futures or the social realities that the public sector seeks to govern and administer.

How important is data to your research?

The increasing importance of data (or so-called datafication of social life) has fuelled utopian visions about societal progress featuring open and transparent societies that strengthen grassroots movements and democratic processes. At the same time, fears associated with increased surveillance and control as well as reinforced inequalities and systemic discrimination have emerged. Our research demonstrates that it is important to pay attention to the ways in which the data that decision-support systems use are produced, interpreted, used, and visualised.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

I am conducting basic and design-oriented research on the use and application of data science in different social domains. Therefore, I am not so much a user or method developer, but in the tradition of science and technology studies, a researcher who is interested in the ways in which data science is practiced, its imaginaries and the ways in which data science may be used to create more inclusive digital futures.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

In one of my next projects, we will use data science methods for participatory urban planning. Text summarisation, argumentation mining, machine translation or clustering will be used for structuring and organising textual input and proposals from citizens to make them available for further collaboration.

What are your main challenges in dealing with data?

My interest, also methodologically, is to research how data move between and across different organisations and contexts. For example, educational data that are produced in schools travel to school authorities, ministries, and may end up in international organisations that compare educational systems. Another example from my research is data on deforestation in the Amazon that is used by environmental NGOs but also different governments to determine funding or trade agreements. In order for these data to travel, they need to shape shift and transform, they need to be translated from one context to another. One methodological challenge in my research is to trace those “data journeys” and make them visible.

And finally, what is your personal motivation for joining the Data Science Center?

The Data Science Center offers the opportunity to examine and challenge some of the basic assumptions of and about data science across disciplinary boundaries and research foci.

Interview Partner:

Dr. Juliane Jarke
Senior researcher at the Institute for Information Management Bremen (ifib)
FB 03 – Mathematics and Computer Science
E-Mail: jarke@uni-bremen.de

Vanessa Didelez on a Core Element of Data Science: Statistics

Thu, 27 May 2021 12:00:00 +0200

What topics are you currently working on in your research?

I am working on a number of – applied and theoretical – projects on causal inference from observational (epidemiological) data where “time” plays a key role. For instance we are developing algorithms for causal discovery from cohort data, such as BIPS’ children’s cohort “IDEFICS/I.Family”; or we are advancing statistical methods to evaluate cancer screening programmes which have time-to-event outcomes; theoretical questions concern inference based on causally meaningful (as opposed to mathematically convenient) parameterisations of models.

How important is data to your research?

While part of my research focusses on investigating the theoretical properties of statistical methods, which does not in itself involve any data, I aim at considering and developing methods that are useful and targeted towards addressing practically relevant questions with real – and often in many ways imperfect – data.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

My research deals with (statistical) methods for analysing data – I would say that this is certainly a core element of data science. I develop methods for real & challenging applications in the context of epidemiological studies. In this work it quickly becomes clear that understanding where the data comes from, what its limitations are and to some extend understanding the domain of application is crucial.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

It will become more and more important to combine methods for causal inference (which was an early part of artificial intelligence in the 90s) with machine learning and related approaches. This will allow us to deal with large and heterogenous data, reduce reliance on parametric assumptions, as well as exploit and combine new sources of data.

What are your main challenges in dealing with data?

A key challenge when addressing a substantive research question using available real-world data are the many limitations and imperfections: observational data contains numerous sources of potential bias. Developing methods that overcome these problems is of paramount importance.

And finally, what is your personal motivation for joining the Data Science Center?

This is a highly interdisciplinary field and we can learn so much from each other!

Interview Partner

Prof. Dr. Vanessa Didelez
Professor of Statistics and Causal Inference
FB 03 – Mathematics and Computer Science
Leibniz Institute for Prevention Research and Epidemiology – BIPS
E-Mail: vdidelez@uni-bremen.de

“The Brain is the Ultimate Data Scientist”

Wed, 19 May 2021 10:00:00 +0200

What topics are you currently working on in your research?

One of the major themes in our group is to try to understand signal routing in the brain. A typical neuron in the brain is connected to about 1000 other neurons. How can a neuron block incoming signals that are not relevant at the moment and preferentially process more important information? It seems that the dynamics of the interactions between groups of neurons play a crucial role in selective signal gating: a neuron that receives multiple inputs will rather process the inputs coming from sender neurons that are rhythmically active in a coherent manner with the receiver. We try to understand this rhythmic synchrony between sender and receiver in more detail: how is it controlled? How generalizable is it to different brain areas and different layers of the cortex? Can we manipulate it?

How important is data to your research?

Very important because we generate a lot!
We record the signals of single brain cells and large groups of them simultaneously. All of these are basically continuous electrical time series. Continuous for the duration of the session of course. We record such time series with high temporal and spatial resolution (up to 500 contact points). Because we record every day a few hours, we generate a few GB a day. Each day.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

I would describe myself definitely as a user. Or maybe not even a real user yet. In fact, we are so far applying rather classical inferential statistical methods to our data. This is partly related to the questions we are interested in in systems neuroscience: we want to know how the brain mechanistically implements the processes that we humans with a brain describe as cognitive processes. We want to understand how the brain “really” does it. When applying data science to neuroscience we often see interesting ideas develop about how the brain potentially might do it, but not how it is mechanistically implemented in the brain.
Another reason is that I am simply not trained in it. So it is great that the Data Science Center started with courses as well!

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

Since I focus on the visual system in my work there is an almost natural link to image processing, object recognition, eye gaze analyses, etc. We can for example present a lot of images and record the eye gaze signal or the brain signal simultaneously. Machine learning techniques can be applied to that data, for example to extract features in the brain signals that lead to recognition of the object.
I think that vice versa understanding the brain better can inspire data science. The brain is the ultimate data scientist, it continuously tries to extract useful knowledge from the information, the data, that it is given. Maybe understanding the brain better can help us towards explainable AI as well.

What are your main challenges in dealing with data?

The human brain consists of about 86 000 000 000 neurons, each connects to about 1000 others. Although it is definitely not possible yet to measure them all at the same time, even not in smaller animal models, the aim is to measure as many as possible to understand the processing in these dense networks better. The data that we thereby generate are impressively complex. At the end of the day, we have tens to thousands of simultaneously recorded time-series, each is a stream of the messages that one neuron sends to another. The statistics of these signals change over time. The strength of the activities spread over multiple orders of magnitude and their patterns vary. We need to multiply this by sessions, participants, etc. What we need are “data-neuroscientists” to develop the right tools to understand how all these neurons work together

And finally, what is your personal motivation for joining the Data Science Center?

I am actually interested in all the Data Science Center has to offer: we can really use some of your computing power, further I hope to get some adequate training in order to be able to apply data science tools in the future. And last but definitely not least: I am really looking forward to potentially fruitful collaborations with other groups at the university. I think we have interesting data to share and I am sure there are some people around that have know-how about different ways to analyze our data. Maybe we can even start a collaborative project a data-neuroscience one!

Interview Partner:

Dr. Iris Grothe
Cognitive Neurophysiology Lab
FB 02 – Biology / Chemistry
E-Mail: grothe@uni-bremen.de

John Bateman on Data Science in Digital Humanities

Thu, 29 Apr 2021 12:00:00 +0200

What topics are you currently working on in your research?

Essentially issues that arise due to the intrinsic multimodality of human communication, including theoretical and methodological foundations. Communication apparently combines speech, written language, gesture, gaze, diagrams, drawings, photographs, moving images, and much much more. Often it works, but sometimes it doesn’t; and it is an increasing challenge for education to teach literacies that can cope with this diversity. Multimodality research then looks for general methods for understanding complex communicative forms wherever they might occur.

How important is data to your research?

Many of the methods that I draw on originate in linguistics, which has a long history of engaging with large bodies of (linguistic) data in the context of corpus linguistics. Nowadays it is usual for empirical linguistic studies to engage with large collections of text to determine properties of language through statistical methods, increasingly involving deep learning strategies. We are now trying to push this for multimodality data as well, which means doing the same, but across types of language (written, spoken), images, moving images, and all the other kinds of media that are deployed in communication. Increasing both scale and access to such mixed data is then central but challenging.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

Data science is fairly central, and increasingly so. Accessing and organizing diverse forms of communication at a larger scale requires methods and approaches to analysis that are core to data science. The work undertaken is then situated both as a user, in terms of drawing on the techniques and methods established, and as a developer when it comes to formulating and developing ways of organizing multimodally complex data. The move is to develop increasingly abstract annotations levels that enable us to advance from more directly measurable properties of data to interpretations.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

Primarily mixed methods, where maximal use can be made of less abstract algorithmic processes (automatic extraction of measurable properties) wherever possible on the one hand, including very specifically targeted processing strategies (shot-lengths in film, word-embeddings, particular kinds of sound recognition, colour-balance, eye-movements, etc.), and abstract characterisations in terms of narratives, argumentative strategies, persuasion, on the other.

What are your main challenges in dealing with data?

Getting at the meanings of patterns, rather than just finding patterns.
...and so trying to direct pattern-finding so what comes out is more easily relatable to meaningful practices.

And finally, what is your personal motivation for joining the Data Science Center?

There are many quite separate initiatives using data at scale and new methods are always being developed: one never knows which kinds of data the methods will be usable for. So it is going to be important to see just what techniques and data sets are emerging across individual projects. The DSC is a forum where that information can be made more visible.

Interview Partner

Prof. Dr. John Bateman
Professor of English Applied Linguistics
FB 10 – Linguistics and Literary Studies
E-Mail: bateman@uni-bremen.de

Norman Sieroka on Philosophy And Data Science

Thu, 01 Apr 2021 10:00:00 +0200

What topics are you currently working on in your research?

I deal a lot with the topic of time in my research. Due to my background in physics, I am interested in physical time on the one hand: How do we measure time? How do we determine time in physics? But on the other hand, I am also concerned with questions about the experience of time, for example related to phenomena such as boredom or even changes that we experience as a result of Corona. The second major area of my research is the philosophy of individual scientific disciplines: How do sciences work? How do we gain knowledge? For these questions, the handling and understanding of data is particularly important. This is where I am interested in the context of the exact disciplines – including mathematics and computer science in addition to physics. I also have projects with colleagues from pharmacy, history, and architecture.

How important is data to your research?

Philosophy is a reflective discipline. Thus, in the literal sense, we are dependent on “data”, on something given or predetermined. Philosophers themselves typically do not collect empirical data in their research; the data of philosophy are actually books and texts.
And then there are concrete research projects in which I deal with philosophical questions about data and data handling. For example, we just won a project on “AI augmented architectural design” with colleagues from Zurich. This project explores the use of AI methods in design processes, for example, to create walls or facades with certain properties. And indeed, this also raises a number of exciting philosophical questions.

What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

I would not describe myself as a basic researcher in the strict sense, but in the broader sense, since I deal with fundamental questions from a reflective point of view. So, for me different approaches in different disciplines and research contexts are very interesting and insightful. For example, while one discipline is characterized by the advancement of existing theories, another focuses primarily on concrete and detailed solutions to problems. But both work data-intensively in this regard and do so with partly similar, partly different methods. In addition, data or methods of data analysis also play an important role in the context of my research on the topic of time. Here one quickly comes to questions about the connection between temporal correlations and causal dependencies – keyword “causal interference”. This is also a highly topical issue in the context of the COVID-19 pandemic – one might think, for instance, of the discussion about vaccine side effects: How can we infer causal dependencies from isolated cases of thrombosis, for example?

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

Regarding the question of how cognitive processes change, I am interested, for example, in what is outsourced to the computer or the robot, so to speak, and what is not. I’m also interested in when one would describe results obtained with the help of AI as genuinely new or even creative. Or also the question of the relationship between automation and personalization in design processes – a question that can be applied not only to architecture, but also in particular to drug design and personalized medicine.
A fundamental question that arises overall is the relationship between predictions, which are becoming better and more successful on the basis of data, and scientific understanding or theory building. There are hopes as well as concerns: predictions are becoming more accurate, but aren’t we conversely neglecting scientific insights or explanations? Or does this concern become redundant with successful implementation? If, for example, neuroscientists would build an artificial retina tomorrow that works perfectly, then one could say that the question of a theory of vision would become obsolete. After all,“obviously” everything essential has already been implemented. To put it in a philosophical slogan: verum factum – only what we ourselves have created is true anyway. – Or is it not?

What are your main challenges in dealing with data?

For me, the great challenge is to better understand the general handling of data and, in particular, the dynamics and cognitive processes behind it or made possible by it. The basic idea of such a philosophical reflection is the following: The better I understand something, the better prepared I am for what is to come. I may not have a one-to-one solution to all problems, but I generally have a better understanding of how data is handled in different contexts and can thus also better adapt to new situations. And of course, these new situations are also linked to many practical questions regarding the handling of data – for example, questions about data security, data protection, or international agreements such as the Nagoya Protocol. In my view, however, what we need here above all is a theoretical understanding so that we can then address these practical issues in a meaningful way.

And finally, what is your personal motivation for joining the Data Science Center?

Interdisciplinarity and reflection. On the one hand, I actually grew up interdisciplinary myself: since the first semester, I have studied philosophy, physics and math. Accordingly, I very much appreciate interdisciplinary centers and cross-disciplinary platforms at the university and I am happy about the collaboration and exchange in the Data Science Center. In fact, the exchange with other researchers who work with data or use AI is a content-related prerequisite for being able to investigate philosophically relevant aspects at all.

Interview Partner

Prof. Dr. Dr. Norman Sieroka
Professor of Philosophy
FB 09 – Cultural Studies
E-Mail: sieroka@uni-bremen.de

Anna Förster on New Technologies And How They Can Help Save Earth

Thu, 18 Mar 2021 12:00:00 +0100

What topics are you currently working on in your research?

I am currently working on a number of related topics, all of which have something to do with how different types of network technologies can contribute to the Sustainable Development Goals. This could be underground sensor networks for agriculture, a smart fence to protect herd animals, opportunistic networks for rural areas in Africa, or an Internet of Things approach to optimize tea fermentation. We are also developing approaches for space travel, especially for manned missions to Mars and the moon. These technologies also help our planet by offering more efficient and cleaner solutions - which brings us back to the Sustainable Development Goals.

How important is data to your research?

It is quite simple: networks transmit data. But there is much more: in all our approaches, we also use environmental data in addition to the transmitted data. This turns something as mundane as networks into a kind of spatial cognition - a topic I work on together with other colleagues here at the DSC, but especially also at the Bremen Spatial Cognition Center. And because data is so important, we always try to publicly share the data we collect, as we did recently with an image dataset of tea fermentation processes.

What role does data science play in your research: Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

Data science is extremely important for me. I need different methods to understand and use sensor data in the Internet of Things (e.g. for autonomous control of plants), to transport data more efficiently and faster (network protocols), but also to interpret our research results. Therefore, I see myself as a mixture of everything: mostly we use well-established methods, sometimes we optimize and adapt them, and sometimes we develop completely new approaches.

Which data science methods and technologies are in the focus of your research or could also become interesting in the future?

Statistical and information gain methods are very important. Recently, AI methods are also becoming more and more important.

What are your main challenges in dealing with data?

Storage space and processing time! An example: a single simulation of our opportunistic networks sometimes takes up to 4 months on our servers and produces several terabytes of data.

And finally, what is your personal motivation for joining the Data Science Center?

I love interdisciplinary research – you learn a lot from other colleagues, you can combine innovative approaches and solve complex problems. In addition, the DSC is committed to supporting young researchers, which I think is our most important task as a university and also as researchers.

Please note: The interview was originally given in German and translated into English by Lena Steinmann.

Interview Partner

Prof. Dr. Anna Förster
Professor of Sustainable Communication Networks
FB 01 – Physics and Electrical Engineering
E-Mail: anna.foerster@uni-bremen.de

Interview With Thorsten Dickhaus About Statistics and Data Science

Wed, 24 Feb 2021 10:00:00 +0100

What topics are you currently working on in your research?

My main research topics are simultaneous statistical inference and multiple statistical hypothesis testing, with diverse applications in life sciences and economics.

How important is data to your research?

Statistical methods must demonstrate their worth when applied to real data. That’s why data are an indispensable part of my research.

What role does data science play in your research: Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

Mainly as a method developer.

Which data science methods and technologies are in the focus of your research or could become interesting in the future?

Mathematical statistics develops and analyzes methods for the statistical analysis of data. Theoretical concepts from probability theory, mathematical optimization and other mathematical fields are used as well as special software solutions.

What are your main challenges in dealing with data?

Every real data set has a scientific connotation. As a result, there are always exciting and fruitful discussions with scientists from other scientific disciplines. This inherently interdisciplinary aspect of statistical research is challenging and rewarding at the same time.

And finally, what is your personal motivation for joining the Data Science Center?

I expect to etablish new contacts with researchers who have exciting data sets and related research questions that we can tackle together.

Please note: The interview was originally given in German and translated into English by Lena Steinmann.

Interview Partner:

Prof. Dr. Thorsten Dickhaus
Professor of Statistical Mathematics
FB 03 – Mathematics and Statistics
E-Mail: dickhaus@uni-bremen.de

Weiterführende Links:

Thorsten Dickhaus’ DSC Profile

Thorsten Dickhaus at the Data Science Forum (25.02.21)

DSC Funds a Project Researching on Automatic Language Processing For Reading And Writing Classes

Katharina Soemer — Mon, 15 Mar 2021 12:00:00 +0100

The DSC Seed Grant was awarded for the second time. This time it went to a project that deals with the concrete implementation of digitalization in school teaching. The project aims to investigate the potential of digital writing technologies for weak writers.

Funding recipient:

Dr. Lisa Schüler (Faculty 10 – Linguistics and Literary Studies, University of Bremen)

Funding period:

1 April 2021- 30 November 2021

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Lars Hornuf on Data Science in Economics

Thu, 04 Mar 2021 12:00:00 +0100

What topics are you currently working on in your research?

I am currently researching topics related to new financial technologies, data protection and the future of work. My main focus is on crowdfunding and crowdworking. However, I am also investigating questions related to data philanthropy and the platform economy in general.

How important is data to your research?

In economics, research has always been empirical. Mathematical theoretical research has largely disappeared from the scene in recent years. The methodological gold standard is currently large-scale randomized controlled trials in the real world. When that is not possible, researchers usually turn to already existing data sets and study them using the methods of inferential statistics. Working with data is our daily business.

What role does data science play in your research: Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?

Depending on the research question, existing methods are applied or new methods are developed in economics. However, the latter is rather the exception. Basic research takes place, especially because we deal with the behavior of people and this raises new fundamental questions in more and more new contexts. For example, the interaction between humans and machines in the workday or financing via algorithms was not a core research field in our discipline just a few years ago.

What kind of methods do you currently use for data analysis and which data science methods could be interesting for you in the future?

Depending on the research question, we mainly use classical methods of inferential statistics or classification methods. The latter can answer research questions or just be aids, for example, if data has been collected from the internet and still needs to be encoded.

What are your main challenges in dealing with data?

Especially for young researchers, it is important to not only blindly apply empirical methods, but also to understand which insights can be drawn from the results and which cannot. For all researchers in our discipline, it is increasingly important to ask the right research questions and not to simply run data sets with standard procedures in the respective statistical software.

And finally, what is your personal motivation for joining the Data Science Center?

I am excited about the scientific discourse. We have a lot of very bright minds in other disciplines and I am looking forward to learning from others and possibly developing joint research ideas.

Please note: The interview was originally given in German and translated into English by Lena Steinmann.

Interview Partner:

Prof. Dr. Lars Hornuf
Professor of Business Administration, esp. Financial Services and Financial Technology
FB 07 – Business Studies and Economics
E-Mail: hornuf@uni-bremen.de

Current Research at DSC: Picking The Right AI Hardware

Christopher Metz — Fri, 05 Feb 2021 13:00:00 +0100

With the paper “Pick the Right Edge Device: Towards Power and Performance Estimation of CUDA-based CNNs on GPGPUs” our collaborator Christopher Metz, in cooperation with Dr.-Ing. Mehran Goli (DFKI), has provided a new approach to estimate power consumption and performance for different graphics card models (GPGPUs) for the execution of Convolutional Neural Networks (CNNs).

It will be possible to perform these estimates for new CNNs without running them on real hardware in advance. This is especially helpful for systems in the edge or embedded computing domain, since fewer prototypes need to be tested. Also, this estimation can help to choose cheaper GPGPU models and thus has a direct impact on the final price of a product. However, the approach uses a neural network for the estimation. It receives as input an instruction profile for the CNN and the hardware components of a GPGPU. The instruction profile is generated from the source code of the CNN and contains the calculation instructions for the graphics card. These are divided into different classes. With the information, the neural network will perform the estimation. In doing so, it is necessary that the network must be executed for each GPGPU that should be estimated. Afterwards, the best GPGPU must still be selected manually.

Previous approaches rely on so-called performance counters for estimation and prediction. The disadvantage of performance counters is that they are only available at execution time. Thus, a new model must first be executed on real hardware in order to determine the corresponding performance counters. However, an estimation can also be performed with the existing approaches. With the new approach the machine Learning models do not need to be executed once, so it is possible to determine the appropriate hardware much earlier, already during programming.

The work was done in cooperation with the Cyber-Physical Systems group of the DFKI in Bremen and was submitted and presented at the System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA) workshop. Further authors are Dr.-Ing. Mehran Goli (DFKI/University of Bremen) and Prof. Rolf Drechsler (University of Bremen/DFKI). Currently, the necessary training data set is generated and collected on which the neural network is trained. The results of the experiments will be published in a future paper.

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

The DSC Launches an Interdisciplinary Seminar Series on Data Science

Mon, 01 Feb 2021 10:00:00 +0100

The “Data Science Forum” is a bi-weekly seminar series for cross-disciplinary exchange on data science. It starts on February 11 2021 and will henceforth take place every second Thursday from 12 to 1 PM in Zoom.

The Data Science Forum is aimed at scientists from all disciplines who work with big data, develop data science methods such as AI or (would like to) apply these in their research as well as those who investigate ethical, legal, and societal aspects of data science. The Data Science Forum offers researchers from all faculties the opportunity to present and discuss their activities, interests, and challenges in the field of data science in front of an interdisciplinary audience. The goal of the Data Science Forum is to make the diverse data science activities of researcher at the University of Bremen visible beyond their own discipline and thus to stimulate a dialogue between scientists from different research areas.

The one-hour meeting usually starts with a 20- to 30-minute presentation and offers enough time for questions, comments and discussions afterwards. Everyone is welcome to attend or contribute a presentation to the bi-weekly Data Science Forum. The seminar series will begin on February 11 2021 with a presentation by Dr. Tanja Hörner on an interdisciplinary training for doctoral candidates entitled “Towards a cross-disciplinary doctoral education program on research data management and data science – Data Train”. Details about the Data Science Forum and all dates can be found »here.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Award of The First DSC Seed Grant

Tue, 01 Dec 2020 10:00:00 +0100

The aim of the interdisciplinary project, which was carried out by Prof. Dr. Lars Hornuf and Dr. Ass. jur. Sonja Mangold (see photo), was to identify risks to data privacy arising from the innovative digital business model of crowdsourcing platforms from an economic and legal perspective. Through a statistical evaluation of privacy statements of the platform companies, research was conducted for the first time to determine the extent to which personal and highly sensitive data is collected from crowdworkers, business customers and website visitors, how this data is used and to what extent it is passed on to third parties (e.g. authorities, other companies).

The study showed that crowdsourcing portals collect and process a wide range of personal and sensitive data in all three countries studied (China, Germany, USA). In some cases, the platforms take proactive measures (e.g., appointment of company data protection officers, data protection certifications) to ensure data protection and data security. Measured against legal transparency requirements, however, the information practices of platform companies on the handling of personal data are often inadequate. Civil society engagement and industry-wide best practice standards could help here. In addition, governmental actors at national and international level must create flanking measures and incentives to establish appropriate, transparent data protection practices in the global crowdsourcing market.

The study supported by the DSC Seed Grant is the basis for further pioneering research and interdisciplinary research collaboration in the field of Data Science at the University of Bremen.

Funding recipients:

Prof. Dr. Lars Hornuf (FB07 - Business Studies and Economics)

Dr. Sonja Mangold (FB07 - Business Studies and Economics)

Funding period:

1st December 2020 - 31st January 2021

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

New Funding Opportunity With The DSC Seed Grant!

Thu, 22 Oct 2020 12:00:00 +0200

Members of the DSC can receive special funds to initiate research projects or collaborations in the field of data science through the DSC Seed Grant. In particular, ventures that foster the collaboration of working groups from different faculties and, thus, lay the foundation for interdisciplinary research projects in the context of data science are supported. The overall goal of the DSC Seed Grant is to promote excellent research in the field of data science.

The amount of the grant is up to 2,500 EUR per applicant. Cooperative applications from research teams are most welcome. Researchers from all status groups, including PhD students, postdocs, senior researchers, and professors, are eligible to apply. The funding can be used for a variety of applications in the context of data science including the implementation of pilot studies, the organization of networking events in Bremen, the invitation of researchers, the realization of a research stay, or the participation in conferences, summer schools or workshops. Detailed information on the grant criteria, application guideline, and funding conditions can be found in the call for proposals.

If you are interested in the DSC Seed Grant and you are not yet a member, please contact us by E-Mail. Further information on a DSC membership can also be found on the page »Become a Member.

If you have any questions about the DSC Seed Grant, please contact

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

Information about the DSC Seed Grant

DSC Seed Grant Flyer

NFDI Enters The Second Round: Seven Letters of Intent With Contribution From Bremen

Mon, 24 Aug 2020 12:00:00 +0200

This year, 30 declarations of intent were submitted to the DFG and published on the DFG-NFDI website. In addition to the University of Bremen and the DSC, the following seven institutions from the Bremen area are involved: BIPS, MARUM, AWI, Fraunhofer MEVIS, IWT, German Maritime Museum and Jacobs University. Out of 18 binding letters of intent for an application in 2020, four are with Bremen contribution:

NFDI4Earth - NFDI Consortium Earth System Sciences
Co-Spokesperson: Prof. Dr. Stephan Frickenhaus (AWI)
Participants: Prof. Dr.Michal Kucera (Universität Bremen / MARUM); Prof. Dr. Vikram Unnithan (Jacobs University Bremen)

NFDI4DataScience - NFDI for Data Science and Artificial Intelligence
Participant: Prof. Dr. Frank-Oliver Glöckner (Jacobs University / AWI)

NFDI4Memory - The Consortium for the Historically Oriented Humanities
Participants: Prof. Dr. Sunhild Kleingärtner; Dr. Dennis Niewerth (German Maritime Museum Leibniz Institute for Maritime History)

NFDI-neuro - NFDI Neuroscience
Co-Spokesperson: Dr. Jan Klein (Fraunhofer MEVIS)

In addition, 12 non-binding letters of intent were submitted for an application next year, three of which were with participation from Bremen:

NFDI4Phys - National Research Data Infrastructure for Disciplinary and Transdisciplinary Physics
Spokesperson: Prof. Dr. Hans-Günther Döbereiner (Universität Bremen)
Participants: Prof. Dr. Uwe Engel (Universität Bremen); Prof. Dr. Rolf Drechsler (DSC); Dr. Lena Steinmann (DSC); Prof. Dr. Frank Kirchner (Universität Bremen)

NFDI4LifeUmbrella - Research data management infrastructure for life science
Co-Speaker: Prof. Dr. Iris Pigeot (BIPS); Prof. Dr. Frank-Oliver Glöckner (MARUM / AWI)

InnoMatSafety - Consortium for the Safety of Innovative Materials
Co-Spokesperson: Dr. Norbert Riefler (IWT)

In three rounds, the German federal and state governments fund up to 30 consortia over a period of five years. A total of up to 85 million euros per year are available for this purpose. The deadline for submitting an application in this round is September 30, 2020, with funding beginning on October 1, 2021.

In 2019, nine consortia received funding, four of them with participation from Bremen. You can find more information here.

The DSC supports the organisation of a workshop about computational approaches in sociological research

Svenja Goers — Sat, 19 Aug 2023 10:00:00 +0200

The two-day workshop “Measuring Culture: Advancing Computational Approaches in Sociological Research” will bring together researchers from various backgrounds who are interested in applying new and innovative computational approaches in sociological research. These novel approaches include tools like natural language processing (NLP), computer vision and network analysis. The workshop’s goal is to spark a lively exchange of ideas and perspectives by giving scholars the opportunity to collectively explore and discuss the latest analytical tools and methodologies in the field.

The workshop’s thematic focus will lie on the sociological study of culture. It is going to cover a diverse range of topics from the field of sociology, including, for example, research on social relationships in the context of different cultural fields such as music, film, sports, and science. Moreover, participants will discuss a variety of new data formats and sources that range from song texts and film critiques to YouTube user behavior and WikiArts images.

The workshop aims to encourage interdisciplinary dialogue and collaboration. Over the span of two days, researchers from different fields will come together, present their own research, and exchange ideas. The workshop will also feature keynotes of leading scholars in the field. Thus, participants will gain insight into a variety of computational and data science applications that are available for studying cultural phenomena. Furthermore, researchers will critically reflect on the opportunities and challenges that come with these novel approaches. Hence, the workshop will enable scholars to advance their own research by developing a better understanding of data and data science and their role in investigating different processes in culture and society.

Funding recipients:

Dr. Katharina Burgdorf (Faculty 08 – Social Sciences, SOCIUM)
Prof. Dr. Annelies Blom (Faculty 08 – Social Sciences, SOCIUM)

Funding period:

20. November 2023 bis 21. November 2023

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links

Information about the DSC Seed Grant

DSC Seed Grant Flyer

DSC Seed Grant book project has now been published open-access

Svenja Goers — Mon, 28 Aug 2023 10:00:00 +0200

The DSC has supported the completion of the book project “Data Privacy and Crowdsourcing: A Comparison of Selected Problems in China, Germany and the United States ”. In order to fund the publication, the very first DSC Seed Grant was awarded to DSC member Dr. Sonja Mangold and former member Prof. Dr. Lars Hornuf in 2020 (we report here ). The results of their research project have now been released as a monograph.

The funding of the book publication has also paved the way for an new, approved third-party project with the Hans Böckler Foundation on “Platform work and data protection from a national and international perspective: market players, problem areas, regulatory requirements”. Based on the findings, policy recommendations on data protection for platform work are developed (read more here ).

In their book, the authors Lars Hornuf, Sonja Mangold und Yayun Yang address the question of how business models of crowdsourcing platforms deal with data protection risks. The focus lies on commercial platforms from China, Germany and the USA that digitally provide and distribute remote services. As part of the research project, privacy statements from more than 400 crowdsourcing platforms were collected and analysed from an economic and legal perspective. In the book, the authors compare data protection practices from the three countries and develop empirically-grounded policy recommendations.

The book is open access and available online.

We congratulate Sonja Mangold and Lars Hornuf on their book publication!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

A new approach enables classifying user engagement behaviour on crowdsourcing platforms

Sana Hassan Imam — Fri, 01 Sep 2023 12:00:00 +0200

Online collaborative communities allow people to interact, collaborate, share knowledge, solve problems, co-create value, and innovate in virtual environments. Organizations harness these potentials on crowdsourcing platforms, using various approaches and technologies to involve outside individuals in performing their tasks. Applications that enable crowdsourcing, such as Amazon Mechanical Turk (MTurk), incentivize individuals through monetary rewards for their contributions. However, there are also successful crowdsourcing platforms that rely solely on volunteer efforts. For volunteer-based crowdsourcing platforms to be lucrative, users must participate in projects over the long term, thus minimizing the costs of new recruitment.

User engagement is a crucial factor for the success of online crowdsourcing platforms, as it influences the quality and quantity of user contributions, fosters collaboration and community building, facilitates knowledge sharing and learning, promotes long-term commitment, and drives platform growth and reputation. Long-term user engagement indicates user loyalty and is essential for sustaining the competitiveness and relevance of crowdsourcing platforms. However, identifying long-term user engagement and associated behavioral patterns is challenging because of data availability and reliability issues, diversified and evolving user behaviors, and the subjectivity of user engagement measurements. Overcoming these challenges requires combining data analysis techniques as well as a deep understanding of the platform and user engagement data.

Together with Christopher Metz (DSC research associate) and under the direction of Lars Hornuf (Chair of Business Administration TU Dresden) and Rolf Drechsler (Director DFKI Bremen), DSC research associate Sana Hassan Imam has developed a novel approach that addresses this challenge. The new method allows to determine long-term user engagement through classification of users and visualization of the most important features for the user engagement on an online idea crowdsourcing platform.

This study presents a new approach to predicting whether a user will engage with online idea crowdsourcing platforms as a short-term or long-term user, applying a machine learning model that boasts 96% accuracy. By utilizing Explainable Artificial Intelligence (XAI)-SHapley Additive exPlanations (SHAP), the study proposes a framework for future research into user engagement patterns and trends across different contexts. This framework can assist platform administrators in recognizing and rewarding valuable users, ultimately leading to the lasting success of online idea crowdsourcing platforms.

The work will be presented on the 3rd of September at the UCAI 2023 workshop on “User-Centered Artificial Intelligence” at Lake Zurich, Switzerland. The interaction-focused workshop takes place for the fourth time and will be held in conjunction with the “Mensch und Computer 2023” conference, which aims at sharing and discussing recent developments at the intersection of HCI and AI, and at exploring novel methodological, technical, and interaction approaches.

Please contact us if you have any questions:

Sana Hassan Imam
Research Assistant
Tel. +49 (421) 218-63954
E-Mail: sanahassan@uni-bremen.de

Workshop on RDM in Health Psychology

Svenja Goers — Mon, 11 Sep 2023 07:00:00 +0200

Once every year the European Health Psychology Society (EHPS) invites psychologist from all over Europe to its annual conference. This year, the 37th conference was held from September 4 to 8 at the University of Bremen. The event took place under the motto “Health Psychology for all: Equity, Inclusiveness and Transformation”. The EHPS conference serves to promote international collaboration and encourage the exchange of ideas and experiences of psychologists in the field.

Part of the EHPS conference program was a workshop on the topic of research data management (RDM) in health psychology which was conducted by DSC Data Steward Dr. Sandra Zänkert. The one-day workshop with the title “An Introduction to Research Data Management - Challenges and Opportunities in Health Psychology” was aimed at PhD students and Postdocs working with health-related data.

Working with health data in research is often particularly challenging and can give rise to many questions. What do scientists have to consider when dealing with health data? How can researchers ensure the security of sensitive, personal data? Which legal frameworks and conditions need to be taken into account when working with health-related data?

The goal of the workshop was to give participants an introduction into the topic of research data management as well as the implementation of the FAIR principles. The workshop’s agenda included not only possible challenges but also new opportunities arising with Big Data and machine learning applications. Furthermore, participants were able to try out some tools and resources that help with the FAIRification of datasets. These included, for example, a tool which is used for data anonymization.

In addition, the workshop allowed everyone to ask questions about their own research projects and data. Since the participants came from different countries all over Europe, diverse experiences were exchanged and discussed together.

More information on the 37th EHPS conference in Bremen can be found »here. The next conference will take place in September 2024 in Cascais Portugal.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

A New Profiling Tool for Achieving Energy-Efficient Applications

Svenja Goers — Thu, 14 Sep 2023 07:00:00 +0200

General Purpose Computation on Graphics Processing Units (GPGPUs) are crucial when it comes to accelerating computing capacity and their usage has increased over the last decades. However, GPUs consume a lot of power to achieve high performance levels. Consequently, it becomes increasingly relevant to decrease power consumption and achieve energy-efficient applications.

One strategy that can be used to improve energy usage and performance, is the optimization of the chosen device with respect to the chosen application. To achieve this goal, one needs information about the potentially employed device, e.g. the different GPUs. To predict power consumption and performance, different standard metrics are used which are gathered by performing code profiling and execution analysis. Academia and industry have proposed different profilers that support developers with code optimization. However, these profilers often require an actual device (e.g. GPU) and the profiling process is very time-consuming.

Together with Christina Plump (DFKI), Bernhard J. Berger (Institute of Embedded Systems – Hamburg University of Technology) and under the direction of Rolf Drechsler, DSC research associate Christopher Metz has developed a hybrid Parallel Thread Execution (PTX) Analyser that can analyse PTX code statically and dynamically without having to run it on a real GPGPU. The generated profile can be used for power and performance prediction of GPU applications as well as for better code understanding (you can read more about Christopher’s previous research on GPGPU performance prediction »here). The new, hybrid analysis approach (HyPA) is further discussed in the paper “Hybrid PTX Analysis for GPU accelerated CNN inferencing aiding Computer Architecture Design”.

The hybrid PTX Analyser was tested in an experiment by performing the hybrid dynamic code analysis on several different CNNs and comparing the outcomes to classic profilers. The results showed that HyPA enables a significantly faster analysis and achieved speedups of up to 536%, compared to the nvprof profiler. Furthermore, the hybrid approach can gather metrics beyond what static code analysis can provide, including branch efficiency. It also achieves a faster execution time compared to profiling the application on an actual device. To help and support developers and system designers with further research and development, an open-source implementation of HyPA is provided.

The new work will be presented on Friday, September 15th (12:30 pm) at the FDL 2023 which takes place from September 13th to 15th in Turin, Italy. The 26th Forum on Specification and Design Languages is an international event during which academics get the opportunity to exchange their ideas and experiences and discuss new trends related to languages, tools, and techniques for developing software and hardware. A variety of targeted systems will be discussed, including e.g., cyber-physical systems, distributed systems and IoT.

DSC research associate Christopher Metz is also going participate in the Ph.D. Forum at the FDL 2023 which is going to take place on Wednesday afternoon (5 pm). The Ph.D. Forum will be a poster session that gives participants the opportunity to present their ongoing research to various experts operating in languages, tools, and techniques for hardware and software system development. During the session, senior faculties and researchers will provide Ph.D. students with feedback on their ongoing research.

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
cmetz@uni-bremen.de

New Profiling Tool wins Best Paper Award

Svenja Goers — Mon, 18 Sep 2023 07:00:00 +0200

Together with Christina Plump (DFKI), Bernhard J. Berger (Institute of Embedded Systems – Hamburg University of Technology) and Rolf Drechsler, DSC research associate Christopher Metz has developed a novel tool for the analysis of PTX code which allows to design more energy-efficient applications.

After Christopher presented the work “Hybrid PTX Analysis for GPU accelerated CNN inferencing aiding Computer Architecture Design” at the FDL 2023, the authors received the Best Paper Award. The hybrid profiling tool enables to analyse PTX code statically and dynamically and can acquire metrics beyond static analysis. The generated profiles can be used for power and performance prediction of GPU applications. Read more about the novel profiling tool HyPA »here.

The FDL (Forum on Specification and Design Languages) is an international event during which academics and industrials get the opportunity to exchange their ideas and experiences and talk about new trends related to languages, tools, and techniques for developing software and hardware. This includes a variety of targeted systems such as cyber-physical systems, distributed systems and IoT. This year, the forum took place for the 26th time in Turin, Italy.

We congratulate the whole team for winning the Best Paper Award!

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

Data Stewardship Goes Germany 2023

Svenja Goers — Mon, 25 Sep 2023 07:00:00 +0200

In the upcoming week, data stewards, data experts, data curators, and data managers will come together for the Data Stewardship Goes Germany workshop in Dresden to discuss topics and experiences in the field of research data management (RDM). The two-day event will take place at the Open Science Lab of the Saxon State and University Library Dresden (SLUB) which was newly opened last November.

This year, the focus of the workshop will lie on the concept of data stewardship and related ideas, challenges, and solutions. More and more institutions rely on data stewards to develop and build efficient RDM infrastructures, give advice to scientists, and create more awareness for the topic of research data management. As the concept of data stewards is still relatively new, the upcoming workshop will give participants the opportunity to network and exchange ideas surrounding the evolving field of data stewardship.

The workshop’s programme includes different presentations from experts in the field of RDM. The event will be opened with the keynote speech “DataStew: Recommendations for supporting research through data stewardship in academic research institutions” given by Jens Dierkes (Cologne University and City Library). Moreover, the program includes a variety of interactive formats. These include, for example, a BarCamp discussion. This session is going to build on the results of the DataStew project presented in the keynote, to spark further discussions about the implementation of data stewardship at research institutions and universities.

During the upcoming workshop, data steward Dr. Sandra Zänkert is going to represent the DSC. On Monday afternoon (3:30 pm) Sandra will participate in one of the workshop’s poster sessions where she is going to present her poster “Establishing Discipline-Specific Data Stewardship at the Data Science Center at the University of Bremen – One Year Review”. Her contribution will give an overview of the different aims, tasks, and activities of the DSC data stewards during their first year at the Data Science Center. The poster session will serve as an event which allows data stewards to share and exchange their experiences.

More information about Data Stewardship Goes Germany and the workshop programme can be found »here.

If you have any questions please contact us:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DSC hosts workshop at the INFORMATIK 2023 Festival

Svenja Goers — Fri, 29 Sep 2023 07:00:00 +0200

Under the motto “Designing Futures”, the INFORMATIK 2023 festival took place from September 26 to 29 at the University of Applied Sciences for Engineering and Economics (HTW) in Berlin. The event focuses on the design of digital technologies and information systems as well as their relevance for societal, cultural, and economic processes.

This year's program included more than 50 workshops on various topics such as artificial intelligence, robotics, the Internet of Everything, green coding, data literacy and data science. On the last day (September 29, from 9 am to 5 pm), the one-day workshop “Aktuelle Entwicklungen und Perspektiven (an Hochschulen) im Bereich Data Science” took place. The event was one of the eleven workshops organized in hybrid form at the request of the participants of the INFORMATIK 2023. The workshop was organised under the lead of the DSC represented by our spokesperson Prof. Dr. Rolf Drechsler and coordinator Dr. Lena Steinmann. Additionally, the organising committee comprised Prof. Dr. Dirk Nowotka and Dr. Helen Pfuhl (Digital Science Center, University of Kiel), and Prof. Dr. Heiner Stuckenschmidt and Dr. Lea Oberländer (Mannheim Center for Data Science, University of Mannheim).

The aim of the workshop was to foster the interdisciplinary exchange between representatives of different data science initiatives and thus promote the development of a sustainable community network. The workshop was divided into three different sessions about the topics of (1) Data Science Centers, (2) Studies & Training, and (3) FDM & NFDI. In the form of key notes, short speeches and poster contributions, participants from different data science initiatives were able to present and collectively discuss their ideas, experiences, solution approaches and best practices. Nine of the 22 workshop contributions were published in the conference proceedings of the INFORMATIK 2023. A preview of the proceedings can be found here .

Overall, the workshop was a great success and enabled participants to connect and network, thereby laying the foundation for future collaborations.

Thank you to all the workshop participants whose diverse contributions enabled a lively exchange and interesting discussions!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC funds research on the public discourse about network policy issues

Svenja Goers — Mon, 02 Oct 2023 07:00:00 +0200

This research project aims to explore how expert opinions from IT Blogs impact the traditional media discourse and discussions on social media and thus influence policymaking regarding regulations of the digital public sphere. To investigate this relation, different web corpora will be examined with the help of digital discourse analysis.

The datasets and corpora will be analysed by using methods from computational social sciences and digital humanities (frequency-, co-occurence-, network analysis, topicc modelling, etc.). Moreover, an automated analysis based on machine learning methods will be conducted.

In order to enable a transatlantic comparison, data was collected in German and English. The thematic focus of the project lies on hate speech and freedom of expression. The topic will be examined in more detail by analysing the public discourse on the German Network Enforcement (NetzDG). The transatlantic counterpart to this are discussions surrounding a possible reform of Section 230 of the Communications Decency Act in the United States.

Both discourses serve as suitable case studies for researching how the societal implications of technology and the public sphere are being negotiated. Furthermore, a transatlantic comparison will provide insights into the extent to which basic democratic values differ on both sides of the Atlantic.

Funding recipient:

Dr. Jens Pohlmann (Faculty 09 – ZeMKI)

Funding period:

01 October 2023 - 31 December 2023

Are you interesred in the DSC Seed Grant?

Please contact us if you have any questions:
Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DataNord: A Data Competence Center for the Bremen Region

Wed, 01 Nov 2023 07:00:00 +0100

This article was published as a press release by the University of Bremen.
You can find the original article here .

“Our vision is to extend Bremen’s strong expertise in the field of data science to a data competence center with a lighthouse character, which can serve as a model for other regions in Germany, ” says the project leader at the University of Bremen, Professor Rolf Drechsler, who is one of three spokespeople for the project. The goal of the interdisciplinary data competence center for the Bremen region (DataNord) is to create a place for researchers in the area to learn about data science, and research and network together, independent of boundaries in institutes and disciplines. Professor Frank Oliver Glöckner, spokesperson for the initiative at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), adds, “Digitalization is advancing steadily and the amount of available data is enormous. However, data is not useful unless it can be analyzed and transformed into knowledge. DataNord helps researchers gain the abilities needed to do this.”

DataNord provides researchers of every career level opportunities to improve their abilities in working with data. These services include trainings, hackathons, consultation services, as well as opportunities for networking and professional discussion. Research activities focusing on data literacy education are offered as part of the DataNord “Research Academy”. The Federal Ministry of Education and Research (BMBF) will support the establishment of the center with a total funding of 3.5 million euros. Of this, more than two million euros will go to the university as network coordinator.

Competence Center as a Beacon and Model for Other Regions

Professor Michal Kuchera, Vice President for Research and Transfer at the University of Bremen, adds, “DataNord is a groundbreaking initiative that will strengthen data competence in the Bremen region and will promote collaboration between different academic disciplines. This has developed as part of a long and successful tradition of cooperation between the research institutes and universities in Bremen. The project will help us achieve the goal of offering all researchers in the region a broad range of services to further develop their research and skills in working with data.” Professor Iris Pigeot, director of the Leibniz Institute for Prevention Research and Epidemiology – BIPS and one of the spokespeople, emphasizes, “With DataNord we will support a cultural change in the use of research data and also strengthen the basis for the emergence of data-driven knowledge and innovations.”

Within this training, the entire life cycle of research data is considered – from the collection and management of data to its analysis and the critical questioning and evaluation of hypotheses, data foundations and results – all while considering ethical, legal, and social aspects. Dr. Lena Steinmann, who coordinated the project proposal at the University of Bremen, emphasizes, “I am convinced that strengthening data literacy plays a decisive role in academic progress, and DataNord will play an important part in helping researchers to better use their data.”

The DataNord network covers a wide range of profile areas, including environmental and marine sciences, social sciences, material sciences and engineering, health sciences, and the liberal arts. This broad approach is representative of the diverse research environment in Bremen and ensures that researchers from several disciplines can profit from the services of the data competence center.

Who is Involved in DataNord

The project is a result of the collaborations in the U Bremen Research Alliance (UBRA) – a collaborative network established in 2016 with the University of Bremen and twelve external research institutes. The leadership of the UBRA lead project “Research Data Management and Data Science”, comprised of Prof. Dr. Frank Oliver Glöckner (MARUM/University of Bremen & AWI), Prof. Dr. Rolf Drechsler, and Prof. Dr. Iris Pigeot (BIPS), also oversee DataNord and initiated this project. Dr. Lena Steinmann and Dr. Tanja Hörner work as a team to coordinate DataNord.

Project partners who also received funding are the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), the Leibniz Institute for Prevention Research and Epidemiology – BIPS, the German Research Center for Artificial Intelligence Bremen (DFKI), the Institute for Information Management Bremen GmbH (ifib), and the U Bremen Research Alliance e.V. In addition to the other UBRA institutions, the following are also involved: the Bremen University of Applied Sciences, the State and University Library, BIBA – Bremen Institute for Production and Logistics GmbH, as well as the NFDI consortia and infrastructure centers. The University of Bremen is in charge of network coordination.

About DataNord

DataNord prevailed in two funding phases with over 70 submitted applications. The first five-month phase was for conceptual design. For the three-year implementation phase, DataNord will be supported by the Federal Ministry of Education and Research with a total of more than 3.5 million euros. Of this amount, over two million euros will go to the University of Bremen.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
+49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

The EU project AI4Ed explores the future of education in Lisbon – DSC supports third joint project meeting

Heike Thöricht — Thu, 09 Nov 2023 07:00:00 +0100

The bustling city of Lisbon played host to the third two-day project meeting of AI4Ed, a groundbreaking initiative funded by Erasmus+ and committed to challenging traditional teaching-learning processes.

Exploring Novel Technologies and Pedagogies

AI4Ed is not merely a project; it is a vision to reshape education by incorporating cutting-edge technologies, particularly artificial intelligence (AI), and innovative pedagogies. The Lisbon meeting was a testament to this vision, focusing on developing tools, methodologies, and evaluation systems that respond to the evolving reality of education.

Key Topics of the 2-Day Event:

Launching the First Use Case at IMH Campus: The highlight of the meeting was the initiation of the first use case at IMH Campus. Partners actively engaged in discussions around data generation for training, laying the groundwork for building AI models in the future. While IMH took the lead, others are gearing up in the starting blocks, preparing for the transformative journey ahead.
Capacity Building for Teachers and Students: Recognizing the pivotal role of educators and learners in the AI-powered educational landscape, the meeting delved into the crucial topic of capacity building. Partners focused on preparing training modules covering a spectrum of subjects, including Artificial Intelligence, Ethics, Project Key Performance Indicators, AI Models, Data Management and Active Teaching. These modules aim to equip teachers and students with the knowledge and skills needed to navigate the future of education seamlessly.

Our data steward Heike Thöricht supported the joint meeting by sharing her expertise and contributing to the objective of making the AI4Ed project’s data FAIR. During the 2-day event, Heike presented an approach on developing a learning unit on the topic of “Data formats” and “Data management plans” for work package 4 of the project (more information on the WPs can be found here). In addition, she made the participants aware of the need to update the data management plan regularly and showed the possibilities of Zenodo as a repository for making the research data and other outputs (e.g. the created learning materials) FAIR.

Looking Forward: A Glimpse into the Future Steps

As AI4Ed enters the next phase of its journey, the project partners are poised for significant milestones:

Further Development of Use Cases:Building on the success of the IMH Campus use case launch, partners are actively working on advancing other use cases. These initiatives aim to demonstrate the practical applications of AI in diverse educational settings.
Continuous Capacity Building: The preparation of training modules is an ongoing effort, with a focus on ensuring that teachers and students are well-prepared for the transformative impact of AI. The modules are designed to not only impart knowledge but also instill ethical considerations in AI education.
Collaboration and Knowledge Sharing: The spirit of collaboration and knowledge sharing remains at the forefront of AI4Ed's approach. Partners are actively engaging with each other to share insights, challenges, and best practices, fostering a dynamic community dedicated to the common goal of reshaping education.

As AI4Ed moves forward, its commitment to innovation, collaboration, and the integration of AI and pedagogical advancements continues to chart the course for a future where education is not just a process but a dynamic, adaptive, and inclusive experience.

If you need help with your project as well, you can contact our DSC Data Steward Heike Thöricht here. As a data steward for social sciences and humanities, Heike supports scientists with the handling of data along the entire research data cycle and gives advice on topics such as FAIR principles, data management plans, sustainable data publication, and archiving.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

The DSC Supports the Creation of a News Page Dataset

Svenja Goers — Fri, 10 Nov 2023 07:00:00 +0100

A compilation of links that were shared by COVID deniers in German-speaking Telegram groups, serves as a basis for the dataset. Over a period of three years, links from 4661 groups leading to more than 200.000 different domains were collected. The project aims at coding as many of the shared domains as possible.

In order to analyse the respective websites, a coding guideline has already been developed. The guideline was built on empirical results from 43 semi-structured interviews that were conducted with political parties from the Bremen Parliament and journalists from the United States. With the help of the interviews, different reliability criteria for news websites were defined. These criteria will be used to code the collected domains and thereby create the first, extensive and open dataset of unreliable news sites in German-speaking regions.

The project is an interdisciplinary collaboration between Faculty 03 (Mathematics and Computer Science) and Faculty 08 (Social Sciences). Also involved in the project is DSC Seed Grant recipient Dr. Dennis Redeker (ZeMKI, Centre for Media, Communication and Information Research).

The dataset will then allow to build a software that informs internet users about problematic websites. For this purpose, prototypes for browser extensions are being designed which enable users to access the coding results for different news sites. Thus, the dataset will contribute to the development of socio-technical solutions against the spread of misinformation.

Funding recipients:

Prof. Dr. Hendrik Heuer (Faculty 03 – Mathematics and Computer Science)
Prof. Dr. Stephanie Geise (Faculty 08 – ZeMKI)
Dr. Daria Dergacheva (Faculty 08 – ZeMKI)

Funding period:

01 October 2023 - 31 March 2024

Are you interesred in the DSC Seed Grant?

Please contact us if you have any questions:
Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Christopher Metz is co-organiser of the “6th Workshop on Parallel AI and Systems for the Edge (PAISE)”

Svenja Goers — Mon, 13 Nov 2023 07:00:00 +0100

Last May, Christopher Metz presented his new research findings on performance prediction of ML accelerators at the 5th PAISE Workshop (we reported »here). With his experiences and expertise, Christopher Metz is now co-organising of the upcoming PAISE Workshop in 2024. The PAISE workshop serves as a platform for exchange that gives researchers the opportunity to discuss the newest developments, challenges, and advances in the field of parallel AI and edge computing systems. In addition, the workshop allows experts from all over the world to connect, network, exchange ideas and discuss potential collaborations.

As part of the organisation team, Christopher will work closely with other international researchers to put together an interesting and diverse program. The workshop will include interactive discussions and presentations, to give participants the chance to present their newest findings and receive feedback from experts of the field.

The workshop will take place as part of the 38th IEEE International Parallel & Distributed Processing Symposium (IPDPS) in May 2024 in San Francisco (USA). You can submit your paper until 14 February 2024. More information can be found soon on our website as well as on the official website of the PAISE workshop (www.paise.org ).

We warmly invite you to participate in the 6th Workshop on Parallel AI and Systems for the Edge (PAISE) and take part in the discussions!

Please contact us if you have any questions:

Christopher Metz
Research Associate
Tel. +49 (421) 218 - 63942
E-Mail: cmetz@uni-bremen.de

DSC article published in the proceedings of the E-Science-Days 2023

Svenja Goers — Fri, 01 Dec 2023 07:00:00 +0100

The E-Science Days are an interdisciplinary conference focusing on the topics of research data management and open science. This year, the E-Science Days took place under the motto ‘Empower Your Research – Preserve Your Data’. During the conference participants discussed topics such as how to ensure the sustainable storage, management, availability, and accessibility of research data over its entire life-cycle. DSC coordinator Dr. Lena Steinmann also attended the conference and represented the DSC (we report here).

The contributions to the conference have now been published in the conference proceedings ‘E-Science-Tage 2023: Empower Your Research - Preserve Your Data’. The collection also includes the article ‘The Data Science Centre at the University of Bremen: Interdisciplinary hub and service infrastructure for data-intensive research’. The contribution provides an overview over the role of the DSC and outlines the institute’s goals, activities, and services in the field of data science and research data management.

The complete proceedings of the E-Science Days 2023 are available at bookshops and can be accessed online here. Our article can be found here.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Kick-Off Event DataNord

Mon, 04 Dec 2023 07:00:00 +0100

This article was published as a press release by the U Bremen Research Alliance (UBRA) written by Merle El-Khatib. You can find the original article here .

"Data is the gold of the present, but it must also be handled carefully and responsibly," Prof. Dr. Jutta Günther emphasized. For this reason, DataNord is of enormous importance as a pioneering initiative. The President was very happy about the approval of DataNord and the resulting funding from the Federal Ministry of Education and Research and financing from the European Union - NextGenerationEU. She congratulated the DataNord spokespersons involved in the application (Prof. Dr. Rolf Drechsler, University of Bremen/DFKI, Prof. Dr. Frank Oliver Glöckner, University of Bremen/AWI, Prof. Dr. Iris Pigeot, University of Bremen/BIPS) and DataNord coordinators (Dr. Lena Steinmann, Data Science Center at the University of Bremen and Dr. Tanja Hörner, U Bremen Research Alliance) on the success.

In his presentation, Prof. Dr Frank Oliver Glöckner then defined the importance of data competence in accordance with the "FAIR Data Principles". In order for research data to be used sustainably, across disciplines and without loss, it must be FAIR, i.e. findable, accessible, interoperable and reusable. Data expertise is the basis for gaining new insights from data and utilising its potential profitably. Unfortunately, there is a lack of data experts. Data competence centres (DCC) are intended to counteract this situation. Eleven DCCs are being funded across Germany. DataNord is one of six regional DCCs, one of four interdisciplinary DCCs and the only DCC in the north. More information on the DCC DataNord can be found here .

DataNord speaker Prof. Dr. Rolf Drechsler added: "You can do a lot with data, we would like to improve the world a little bit." No one in this group doubted that Bremen as a centre of science is contributing to a sustainable increase in data skills among researchers from all disciplines and career levels in Bremen. The following get-together provided space for discussions on how the world can be made a better place through research data management, where lively discussions took place and the success was celebrated together.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
lena.steinmann@uni-bremen.de

Data Train 2024 Kick-off Event

Svenja Goers — Thu, 18 Jan 2024 06:00:00 +0100

With this year’s kick-off event, which took place on January 17 at Fraunhofer Institute for Manufacturing Technology and Advanced Materials (IFAM), the program “Data Train – Training in Research Data Management and Data Science” has entered its next round. Data Train is a centralised, cross-discipline training program which is offered to doctoral researchers from the member in-institutions of the U Bremen Research Alliance (UBRA). Since November 2023, Data Train will continue to be further developed as part of the BMBF-funded data competence center Data Nord.

Data Train teaches competencies in the fields of data science, research-data management (RDM), and data literacy and is organized in close collaboration with the Data Science Center. This year’s program started off with an interdisciplinary overview Starter Track in English. These interactive overview lectures takes place from January to May 2024 and is open to anyone who is interested and wants to get started in RDM and data science.

The kick-off event served to introduce Data Train and provided information about the program, its concept, and the contents of this year’s curriculum. The event was opened by a welcome from Prof. Dr. Iris Pigeot (director BIPS). Together with Prof. Dr. Rolf Drechsler (DSC spokesperson, DFKI) and Prof. Dr. Frank Oliver Glöckner (University of Bremen, AWI), Iris Pigeot is one of the program’s spokespersons. Also part of the agenda, was a presentation by Data Nord coordinators Dr. Lena Steinmann (DSC coordinator) and Dr. Tanja Hörner (UBRA) who introduced the newly founded interdisciplinary data competence centre Data Nord . Data Train coordinator Dr. Maya Dalby then provided more information on the training program itself, including its contents, structure, and schedule. The event was rounded off by the data story “Beautiful Insights – The art and science of data visualisation” presented by Moritz Stefaner. At the end, participants were able to ask questions, discuss, and get to know people associated with the Data Train program during a follow-up get-together. More information on the Data Train kick-off event can be found here.

Are you interested in the Data Train program? Further information about Data Train (concept, schedule, registration, etc.) can be found on the UBRA Website . If you have any questions, please do not hesitate to contact Data Nord coordinators Dr. Lena Steinmann and Dr. Tanja Hörner or Data Train coordinator Dr. Maya Dalby.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Accelerating Data Science With New Computing Resources

Mon, 12 Apr 2021 12:00:00 +0200

Data science, particularly AI-based analysis methods, require powerful computational capacities beyond the means of a classical office computer. Accordingly, the Data Science Center (DSC) at the University of Bremen has established a new IT-infrastructure enabling fast and effective data analyses as well as the implementation of machine learning experiments. This is based on the three pillars of High-Performance Computing (HPC), Storage, and Virtualization.

In the area of HPC, the DSC is equipped with powerful GPU servers that use three NVIDIA V100 GPUs to boost the speed and performance of data analytics. In fact, one NVIDIA V100 GPU provides the performance of up to 32 CPUs, making it one of the most advanced data center GPUs ever built to accelerate data science and AI. In addition, the DSC supports multiple software environments, including the most popular languages such as Python or R and their commonly used libraries and packages, to meet the diverse needs of our users.

Data science involves large amounts of data and to effectively process such big data, a large bandwidth is required. Accordingly, the servers of the DSC are interconnected through state-of-the-art InfiniBand technology permitting high-speed data transmission with rates of up to 100 gigabits per second. As part of the pillar Storage, the DSC is currently equipped with 5 SSDs providing a total storage capacity of 5.75 TB for operational use, which can be scaled up to 24 SSDs depending on the needs of the users.

As technology gets more complex, its security becomes more elaborate and crucial. For maximum user friendliness, we will offer a same sign-on authentication for user accounts of the University of Bremen. In the area of Virtualization, the DSC is equipped with a Virtual Machine (VM) server, allowing us to offer customized resources depending on the user’s needs. Our VM service can for instance be used to implement Web crawlers or applications like R Studio Server.

In summary, the DSC offers optimal and flexible resources for running computationally intensive algorithms and data analysis in data-intensive research and teaching. If you are interested in using our computational resources, please send us an e-mail to discuss the possibilities.

Are you interested in using our IT infrastructure?

Please contact:
Dr. Lena Steinmann
DSC Coordinator
Tel.: +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Vier NFDI Konsortien mit Bremer Beteiligung gefördert

Lena Steinmann — Wed, 01 Jul 2020 12:00:00 +0200

Neues DFG Schwerpunktprogramm zur theoretischen Forschung an neuronalen Netzen

Lena Steinmann — Tue, 30 Jun 2020 11:00:00 +0200

DSC Funds a Project for Automated Content Detection in Discourse About Internet Policy

Katharina Soemer — Mon, 17 May 2021 11:00:00 +0200

The third DSC Seed Grant was awarded to a project that deals with the automated identification of complex argumentation pattern using machine learning methods. The text corpora contain articles to the discourse on internet policies both on IT blogs and in print media. By evaluating the resulting data, the discussions that take place in these two different spheres on issues at the interface between technology and society can be made. The first analysis deals with the regulation of expression of opinion online based on the discourse on the Netzwerkdurchsetzungsgesetz (Network Enforcement Act, NetzDG). On a technical level, this research will provide an insight into how current neural transformer language models can enable the automated recording of complex arguments in German.

Funding recipient:

Dr. Jens Pohlmann
(Faculty 9 – Cultural studies, ZeMKI – Centre for Media, Communication and Information Research)

Funding period:

1st June 2021 till 31th May 2021

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC continues nationwide network initiative

Svenja Goers — Tue, 16 Jan 2024 08:00:00 +0100

Together with the Digital Science Center (Kiel University) and the Mannheim Center for Data Science (University of Mannheim), the Data Science Center hosted a workshop at the INFORMATIK 2023 last September. The one-day hybrid event “Aktuelle Entwicklungen und Perspektiven (an Hochschulen) im Bereich Data Science” aimed to foster the exchange between representatives of different data science initiatives and thus lay the foundation for developing a sustainable community network (we report here).

The workshop resulted in the collective goal of establishing a nationwide data science network to further promote exchange and cooperations between different institutes and initiatives. To connect the community in a sustained manner, an e-mail list was set up as a first step towards future collaboration. Representatives of data sciences initiatives can register here .

On January 15, the first follow-up meeting of the data science community took place online. The event was aimed at discussing the further development of the network and exchange ideas regarding future plans and projects. Around 20 representatives of various data science initiatives from all over Germany and Austria took part in the community meeting.

To further promote the networking between data science initiatives, more events have already been planned. The next Community-Meetup is going to take place at INFORMATIK 2024in Wiesbaden next September. A proposal for another data science workshop at the conference has already been submitted. More information on the INFORMATIK FESTIVAL 2024 can be found here .

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

We are looking for student support!

Mon, 18 Mar 2024 09:00:00 +0100

The DSC is looking for student assistants (m/f/d) for public relations and project management activities.

The DSC supports a research stay at the Data Science Institute at Columbia University

Svenja Goers — Mon, 15 Apr 2024 10:00:00 +0200

This DSC Seed Grant aims to enable collaborative research projects in the field of learning augmented algorithms. The plan is to establish different relations with researchers of the Data Science Institute at Columbia University and other institutions in New York City. To initiate this international cooperation, DSC Seed Grant recipient Prof. Dr. Nicole Megow is going to visit the Data Science Institute at Columbia University as an Adjunct Senior Research Scientist for three months this summer. The stay also includes planned visits at Cornell Tech and NYU (New York University).

The main research area of the collaboration is the topic of algorithms under uncertainty and theoretical analysis of decision-making methods under uncertainty. The focus will be on models and analyses beyond traditional worst-case analysis, particularly on the recently emerging model of Learning-Augmented Algorithm Design. This model, also known as Algorithms with Predictions, is an approach to integrate imperfect predictions, such as machine-learned predictions, into algorithm design while still achieving provable performance guarantees. The goal is to develop and implement new research questions and projects in these areas.

The main intent of this DSC Seed Grant project is the establishment of long-term relations with renowned scientists from different institutions in New York City. It is also supposed to pave the way for future postdoc visits and student exchanges. In addition, the project could lay the foundation for a connection between the Data Science Institute at Columbia University and the Data Science Center at the University of Bremen.

Funding recipient:

Prof. Dr. Nicole Megow (Faculty 3 – Mathematics and Information Science)

Funding period:

April 2024 - July 2024

Are you interesred in the DSC Seed Grant?

Please contact us if you have any questions:
Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

PhD-Student at DSC Sana Hassan Imam Presents Paper on Generative AI Model

Jennifer Nüchter — Mon, 13 May 2024 15:43:00 +0200

Sana Hassan Imam is a PhD student at DSC as part of a collaborative project with the Faculty of Business Studies and Economics at the University of Bremen. Her paper with the title “How Can Generative AI Curate the User Creativity on an Idea Crowdsourcing Platform?” discusses how generative AI can enhance user creativity on a so-called idea crowdsourcing platform by evaluating the uniqueness, diversity, and feasibility of ideas, and providing targeted prompt designs to improve the quality of those ideas with the help of a proposed model.

Moreover, the paper showcases the limitations of traditional methods: Traditional idea-generation methods often limit novelty and diversity, requiring significant human creativity which can be hard to measure. The generative AI model mainly works in two steps:

Step 1: Evaluates creativity scores of user ideas based on uniqueness, diversity, and feasibility, using feedback from peers and managers
Step 2: Provides tailored prompts to users to stimulate, enhance, and refine their ideas based on the calculated creativity scores

To implement this model, scores for creative engagement, idea uniqueness, diversity, and flexibility are calculated. Using these scores, a novel prompt-designing mechanism has been developed. Instead of providing direct suggestions, the model uses prompts to encourage creativity without creating dependency on artificial intelligence. Examples of how to increase novelty include adding random words, using “What if”- scenarios to stimulate divergent thinking, and encouraging peer and manager feedback to improve feasibility. This feasibility is assessed through feedback summaries and different prompt designs are suggested to enhance user creativity based on these scores.

To bring this model even further, a synthetic data example, more specifically a user-generated idea for a “Smart Umbrella project”, is brought up to illustrate the model’s idea. The example aims to incorporate a dynamic light show using LED lights along the canopy’s rim. Its prompts were designed to make the idea more practical by focusing on user experience, core functionality, cost, and accessibility.

In summary, this model aids users in refining and enhancing their ideas by stimulating creative thinking. The iterative process of idea enhancement improves the quality and creativity of user-generated content. Additionally, this approach helps platform managers identify high-potential ideas with high uniqueness, diversity, and feasibility scores that may not have received enough votes.

The paper concludes by emphasizing the comprehensive framework provided by the model for boosting user creativity in idea crowdsourcing, positioning generative AI as both a thought-provoking tool and a collaborative co-creator.

For further questions please contact:

Sana Hassan Imam
Promovierende
Tel. +49 (421) 218 - 63954
E-Mail: sanahassan@uni-bremen.de

Further Links:

Paper Download
Link to the Conference

Empowering Education: AI4Ed initiative makes progress in Zreče with the support of the Data Science Center

Wed, 15 May 2024 15:52:00 +0200

The AI4Ed initiative funded by the European Union continues to pave the way for transformative changes in education by leveraging cutting-edge technologies and innovative pedagogies. In its fourth 2-day project meeting held in Zreče Slowenia, the focus remained on redefining teaching-learning processes through the integration of AI and exploring new methodologies to meet the demands of modern education.

Update on Data Collection for Use Cases

The meeting commenced with a comprehensive update on the progress of data collection for various use cases at the University of Bremen, Instituto de Máquina-Herramienta (Spain), Centro de Formação Profissional da Indústria Metalúrgica e Metalomecânica (Portugal) and School center Slovenske Konjice-Zreče (Slovenia). Different challenges (e.g. what data can be collected in the learning system Moodle), potential solutions and next steps were discussed.

Capacity Building for Teachers and Students

A pivotal aspect of the AI4Ed initiative is the empowerment of educators and students through targeted capacity-building initiatives. Day 2 of the meeting delved into the continued creation of training modules designed to enhance proficiency in artificial intelligence, ethics, data management and active teaching methodologies. For this task Heike Thöricht is creating a training module about research data, data management plans and FAIR principles in a joint Moodle platform provided by one of the project partners.

The fourth 2-day project meeting of AI4Ed marked another significant milestone in the journey towards reimagining education through AI-driven innovation and the project partners are highly motivated in continuing the next steps in the project.

If you need help with your project as well, you can contact our DSC Data Steward Heike Thöricht here . As a data steward for social sciences and humanities, Heike supports scientists with the handling of data along the entire research data cycle and gives advice on topics such as FAIR principles, data management plans, sustainable data publication, and archiving.

Please contact us if you have any questions:

Heike Thöricht
DSC Data Steward
Tel. +49 (421) 218 - 63939
E-Mail: heike.thoericht@uni-bremen.de

Further Links:

Website AI4Ed Project

The Data Science Center welcomes six new team members!

Svenja Goers — Mon, 27 May 2024 15:59:00 +0200

DataNord is an interdisciplinary data competence center for the Bremen region. It offers researchers from all disciplines and career levels diverse opportunities to enhance their data skills throughout the entire data lifecycle. This includes training sessions, hackathons, consulting services, as well as networking and professional exchange opportunities. The goal of DataNord is to sustainably increase the data competencies of researchers from various disciplines and thus promote innovation in science.

The new colleagues play a key role in shaping DataNord’s offerings. As an interdisciplinary team, Sarah Büker, Dr. Susanne de Vogel, Nele Fuchs, Dr. Maryam Movahedifar, and Annika Nolte will establish a help desk at the DSC with innovative consulting and training services in data management and data science. They bring a wide range of expertise from various scientific fields to the DSC.

Sarah completed her Master’s degree in Marine Environmental Sciences at University Oldenburg in 2023, focusing particularly on the extraction and analysis of environmental DNA. She previously completed her Bachelor’s degree in Biological Sciences in 2019. From now on, she will support researchers in the field of environmental sciences as well as health sciences, with a focus on metabarcoding and sequence analysis. To Sarah’s Profile

Susanne completed her Ph.D. in Sociology at Martin Luther University Halle-Wittenberg in 2019 and worked for several years as a research associate in various panel surveys at the German Centre for Higher Education and Science Studies (DZHW) in Hannover. Her focus in training and consulting will be on the domain social sciences. To Susanne’s Profile

Nele completed her Bachelor’s degree in Philosophy & Material Culture in 2019, followed by a Master’s degree in Transcultural Studies in 2023. In the past she also worked as editorial head at the Institute for Material Culture at Carl von Ossietzky University Oldenburg, contributing to the ‘Studien zur Materiellen Kultur’ series. With her broad expertise in the humanities, she will particularly support researchers in this field. To Nele’s Profile

Maryam completed her Ph.D. in Statistics at Payame Noor University in Tehran, Iran, in 2020. From 2021 to 2024, she worked as a postdoctoral researcher at the Institute for Statistics at the University of Bremen. At the DSC, she will be mainly involved in methods consulting and training, particularly in the field of statistics.To Maryam’s Profile

Annika completed her Master’s degree in Environmental Sciences at TU Braunschweig. From 2019 to 2024, she worked as a research associate at the Climate Service Center Germany (GERICS) and conducted research at the University of Hamburg. Her expertise will also focus on the domain of environmental and marine sciences. To Annika’s Profile

In addition, the DSC got new support in the administration department. A warm welcome also goes to Jasmin Marx-Krull who is going to work as the new team assistant at the DSC.

We are very excited to welcome all new members to our team and work together to shape the future of the Data Science Center and DataNord!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

More about Data Nord: www.bremen-research.de/datanord

Dr. Christopher Metz Successfully Defended His Dissertation

Jennifer Nüchter — Wed, 29 May 2024 16:12:00 +0200

Efficient and innovative computations of machine learning (ML) algorithms are particularly important nowadays, especially when it comes to autonomous driving, the Internet of Things (IoT), and edge computing. Convolutional Neural Networks (CNNs), a key ML technique, require significant computational resources. To meet these demands, ML accelerators like General Purpose Graphic Processing Units (GPGPUs) are often used. However, GPGPUs cause high power consumption, making the selection of the optimal accelerator a complex, manual Design Space Exploration (DSE).

Christopher’s dissertation, written in the research group of the DSC spokesperson and co-founder Rolf Drechsler, presents innovative approaches to optimizing the DSE process. It develops techniques to precisely predict the power consumption and performance of CNNs during execution. This enables developers to estimate the power consumption and performance of GPGPUs in the early development stages without needing real devices, significantly reducing the number of necessary prototypes. Additionally, developers must decide whether an application will be implemented on an IoT device or in the cloud, considering the available network, bandwidth, and latency. The dissertation introduces a system that assists developers in these decisions by considering the available network, bandwidth, and latency, allowing for informed decisions with regard to energy and performance requirements.

The entire DSC proudly celebrates the successful doctoral defense on 29 May 2025 and extends warm congratulations to Dr. Christopher Metz on this remarkable achievement!

If further questions arise, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

New Publication at DSC: Innovative Approach to Analysing Doctoral Trajectories

Sun, 18 Aug 2024 16:24:00 +0200

The paths of doctoral students obtaining a Ph.D. in Germany are rarely standardized. In addition to very straightforward doctoral paths that are completed within a single context – such as graduate school – there are also doctoral phases with frequent context changes, for example when a doctorate is continued within an employment relationship following a scholarship program. Furthermore, they can vary significantly in length. While some complete their doctorate within a few years, others take considerably longer. This substantial difference in sequence lengths has made it difficult for sequence analyses to identify typical patterns in doctoral trajectories.

To address this challenge, the researchers propose normalizing the sequences. Instead of focusing on the absolute duration of the doctorate, the relative duration of individual episodes within the doctoral trajectories is considered. This means that each episode of a doctoral trajectory is viewed as a percentage of the overall doctorate — regardless of how long the doctorate takes. This normalization makes it possible to compare different doctoral paths directly, without the total duration of the doctorate distorting the results. In this way, patterns and typical trajectories can be better identified.

Sequence normalization offers several advantages, including direct comparability, as doctoral paths of different lengths can be systematically compared. Additionally, it allows for the identification of typical trajectories and patterns, which makes it easier to define ideal doctoral paths. The method also guarantees a better graphical representation of the data.

The researchers developed their method utilizing a panel study’s data of German doctoral graduates created by the German Centre for Higher Education Research and Science Studies (DZHW). The doctoral trajectories of doctoral holders were recorded on a monthly basis. Thanks to sequence normalization, they were able to systematically compare different doctoral paths and identify typical patterns.

Especially in areas where the duration of life trajectories varies greatly, this method of sequence analyses can uncover patterns and enable scientific decisions. The method thus offers great potential for future research and could also be applied to other educational or career trajectories.

If you have any questions regarding this publication, feel free to contact me.

Dr. Susanne de Vogel
Data-Science-Support
Tel. +49 (421) 218 - 63938
E-Mail: devogel@uni-bremen.de

Further Links:

Link Publication

DSC Funds Participation at Research Conference in Toronto

Jennifer Nüchter — Wed, 18 Sep 2024 16:32:00 +0200

Andreas will attend a conference of the SERU consortium, which conducts large-scale student surveys at the Center for Studies in Higher Education (CSHE) at UC Berkeley, USA, from September 17 to 18 at the University of Toronto, Canada. SERU (Student Experience in the Research University) is based at the Center for Studies in Higher Education at UC Berkeley and administers a large-scale student survey. There are two types of surveys: undergraduate (since 2002) and graduate (since 2017), organized every two years (graduate in 2025, undergraduate in 2026) with a sample size of 400,000 students and a response rate of 30-50%. Andreas attends the conference to finalize the survey design and negotiate data re-use.

The collected data will support a sub-project in a DFG Research Unit starting in January 2025 and enhance data analysis at the DSC. With the collected data, novel data science methods can be applied within the team, and insights into the acceptance and use of AI-based systems in higher education institutions can be gained. This will form the basis of a sub-project of a DFG Research Unit, in collaboration with colleagues at ZeMKI and TZI. Additionally, a large data set from higher education research can be added to the data collection at the DSC to enable further analyses.

Funding recipient:

Prof. Dr. Andreas Breiter (Faculty 3 – Mathematics/Computer Science)

Funding period:

September 2024 - October 2024

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel.+49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

DSC Seed Grant
DSC Seed Grant Flyer

DataNord Roadshows: Discover the Offers of Bremen’s Data Competence Center!

Wed, 30 Oct 2024 08:06:00 +0100

As part of the U Bremen Research Alliance (UBRA) and in collaboration with other regional partners, the interdisciplinary data competence center for Bremen DataNord consolidates extensive expertise in research data management and data science. The center focuses on five scientific profile areas: (1) Environmental and Marine Sciences, (2) Social Sciences, (3) Material and Engineering Sciences, (4) Health Sciences, and (5) Humanities. DataNord is one of eleven data competence centers nationwide funded by the Federal Ministry of Education and Research (BMBF).

Our offers are comprehensive, ranging from practical trainings and personalized consultations to hackathons, summer schools, self–learning materials, and numerous networking opportunities. We support researchers throughout the entire data lifecycle – from data collection and analysis to long–term archiving and reuse. To ensure that our offers are of high quality, the DataNord team consists of a team of experienced professionals who work in various disciplines.

Key pillars of DataNord include the Data Science Center (DSC) at the University of Bremen, which provides tailored Trainings and Consultations through its interdisciplinary team, and the Data Train program, designed specifically to equip PhD students and early–career researchers with essential skills in data science and research data management.

The DataNord Roadshow invites you to explore our wide range of services and discover the offers that best meet your research needs. Whether you're experienced in working with data or just starting out, we have the right format for you.

Learn about exciting research support opportunities such as "Rent a Data Scientist", or our engaging formats like "Data Stories", "Data Snacks", and "Hacky Hours". Find out more about our networking options, including the "Day of Research Data" and the "Data Community Club". There is something for everyone!

Previous Roadshow Dates:

30.10.2024 | 1:00 PM - 2:00 PM | Faculty 02 - Biology / Chemistry (Group Leaders Meeting)
04.11.2024 | 12:00 PM - 1:00 PM | Faculty 07 - Business Studies (Lunch Dialogue)
19.11.2024 | 12:00 PM - 1:30 PM | Institute of Environmental Physics
18.12.2024 | 10:30 AM - 11:30 AM | Faculty 11 - Health Sciences (Faculty Council)
21.01.2025 | 9:30 AM - 10:30 AM | MARUM Café
22.01.2025 | 4:15 PM - 5:00 PM | ZeMKI Research Colloquium
06.02.2025 | afternoon | SOCIUM Annual Meeting 2025

DataNord Contacts

Speakers:

Prof. Dr. Rolf Drechsler
Prof. Dr. Frank Oliver Glöckner
Prof. Dr. Iris Pigeot
Prof. Dr. Uta Bohnebeck

Coordinators:

Dr. Tanja Hörner
Dr. Lena Steinmann

Want the DataNord Roadshow to visit your institute? Let us know!

Dr. Lena Steinmann
DSC Coordinator
+49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links

More Info on DataNord BMBF- DSC Project
DataNord Website
Information about the BMBF call for proposals

Welcome to the DSC, Nils!

Svenja Goers — Wed, 01 Jan 2025 10:00:00 +0100

Nils Leusmann completed his bachelor’s degree in information technology at the Baden-Württemberg Cooperative State University (DHBW) in Stuttgart in 2016. In 2017, he began his master’s degree in computer science at the University of Bremen, which he successfully completed in 2020. Afterwards, he worked as a research associate at the Institute for Artificial Intelligence at the University of Bremen until the end of 2024, where he conducted research in the field of digital twins, robotics, and cognitive architectures.

From now on, Nils will be working at the DSC under the BMBF-funded joint project “INDIFUN-AI”. The aim of the project is to develop an automated system for monitoring and studying biodiversity and its changes due to climate change, in cooperation with several institutes. Nils’ research will focus on self-assessment routines for online algorithms using domain-specific data (specifically plankton data). The overarching goal is to develop an AI-based system that contributes to the understanding of biodiversity in the Arctic and the “health” of the ecosystem.

We are excited to welcome Nils to our DSC team and look forward to working with him!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel.: +49 (421) 218 - 63941
E-Maill: lena.steinmann@uni-bremen.de

Data as a Bridge: Published Poster as Part of the Digital Humanities Conference 2025

Sun, 09 Mar 2025 09:34:00 +0100

Global issues like war, pandemics, and climate change shape our time – but simultaneously we are also witnessing transformative developments such as datafication and evolving gender roles. The DHd Conference 2024 in Bielefeld focused on this tension and posed the question: How can the humanities, cultural studies, and data sciences collaborate to collectively shape the experience of "being under construction"? Thus, at the heart of the discussion was the role of data in the Digital Humanities: How do we define data from a humanities perspective? How can we equally capture both analog objects (texts, architecture) and digital phenomena (internet culture, AI)? Critical discussions addressed potentials, blind spots (such as bias and sustainability), and the interdisciplinary promises of DHd – always with the aim of reinterpreting cultural practices and the data traces they leave behind.

All contributions from the conference have now been compiled in the "Book of Abstracts – DH ", including the abstract for the published poster. The poster provides an overview of how data is conceptualized in the (digital) humanities and connects this with the interdisciplinary initiatives of the DataNord project at the Data Science Center.

The "Book of Abstracts 2025 " can be found here and the published poster here .

Please contact us if you have any questions:

Nele Fuchs
Data Scientist for Digital Humanities
Tel. +49 (421) 218 - 59853
E-Mail: n.fuchs@uni-bremen.de

Further Links:

Book of Abstracts (Available in German only)
Poster: Data as a bridge (Available in German only)
Website DHd Conference 2025 (Available in German only)

Advancing Time Series Preprocessing: DSC at the 17th German Probability and Statistics Days

Dr. Maryam Movahedifar — Mon, 17 Mar 2025 08:46:00 +0100

From March 11–14, 2025, the 17th German Probability and Statistics Days (GPSD) took place at TU Dresden. As one of the most important events for the statistics and probability community in Germany and Europe, GPSD 2025 brought together researchers from a wide range of disciplines and career stages to discuss new developments, methods, and applications in the field.

Maryam Movahedifar, data scientist at the University of Bremen's Data Science Center (DSC), represented the DSC community by giving a talk during the conference. Her presentation focused on the often-overlooked but vital task of data preprocessing-particularly in the context of noisy, high-dimensional time series data.

While technical in nature, her work contributes to one of the core missions of the DSC: building robust, interdisciplinary methodologies that can be applied across domains. In her talk, Maryam presented a comparative study evaluating different preprocessing methods, with a focus on a nonparametric technique called (Multivariate) Singular Spectrum Analysis ((M)SSA). The aim was to assess how preprocessing quality affects the reliability of statistical analyses, especially in real-world, noisy datasets.

By sharing this research with the GPSD community, Maryam not only contributed to academic exchange but also raised the profile of the DSC's applied and methodological expertise. Her session sparked interesting discussions among participants working on statistical inference, time series analysis, and data-driven modeling.

Maryam is now preparing a written version of her contribution to be included in the official GPSD 2025 proceedings. This publication will detail the key findings of the project and offer guidance for other researchers facing similar challenges in their data.

This participation reflects the DSC's commitment to supporting its members in disseminating their work and engaging with the broader research community. Whether through methodological innovation or interdisciplinary collaboration, contributions like Maryam's help ensure the DSC remains a hub for cutting-edge data science in Bremen and beyond.

Please contact us if you have any questions:

Dr. Maryam Movahedifar
DSC Data Scientist
Tel. +49 (421) 218 - 59854
E-Mail: movahedm@uni-bremen.de

Further Links:

Website German Probability and Statistics Days (GPSD) 2025

DataNord as a Best Practice for Data Literacy at the E-Science-Tage 2025

Mon, 17 Mar 2025 10:00:00 +0100

The E-Science-Tage 2025 served as a key interdisciplinary platform for exchange between experts from research, infrastructure, and policy. The conference focused on current challenges in research data management (RDM) – including data quality assurance, the use of AI, publication processes, and cross-institutional coordination.

On March 13, DSC Coordinator Lena Steinmann presented the talk „DataNord: Empowering Data Literacy – Strengthening Bremen’s Research“ in the Data Literacy session.

At the heart of the presentation was DataNord , the interdisciplinary data competence center for the Bremen region, developed within the framework of the U Bremen Research Alliance and coordinated by the University of Bremen / the DSC. As one of eleven nationwide data competence centers funded by the Federal Ministry of Education and Research (BMBF), DataNord aims to strengthen data literacy across all career levels and to establish a sustainable FAIR data culture.

Key elements introduced included the DSC’s training and consulting services as well as the interdisciplinary doctoral program Data Train .

With a wide range of training opportunities, expert consulting, community formats, and inter-institutional collaborations, DataNord plays a vital role in advancing the regional RDM ecosystem – and serves as a model initiative for other regions in Germany.

We are pleased to have contributed once again to the E-Science-Tage and to have engaged in such enriching discussions following the presentation.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

Website E-Science Days
Link to Abstract & Slides on Zenodo
(DOI: 10.5281/zenodo.15118351)

Stronger Together for Data Science – Community Workshop in Bochum Moves Initiative Forward

Mon, 24 Mar 2025 10:00:00 +0100

Hosted at the Hochschule Bochum and organized by the local team – especially Christian Bockermann and Lars Michael – the event offered a space for exchange, networking, and defining concrete next steps toward long-term collaboration.

The goal of the meeting was to discuss the future of the community: How can we ensure sustainable exchange? What structural conditions are needed? And how can shared goals and positions be made more visible? These and other questions were discussed in multiple sessions. The social event at the Fiege brewery also offered plenty of opportunity for informal exchange.

Initial ideas and perspectives:

Discussions around a joint position paper are continuing in a dedicated working group. The goal is to highlight shared priorities, needs, and potentials within the Data Science / Digital Science community.
A formal organizational structure – potentially in the form of an association – is also being explored to support long-term collaboration.
Regular in-person meetings are planned to strengthen the community exchange:
- 📍 Fall 2025: Half-day workshop on September 16 as part of INFORMATIK 2025 in Potsdam (Submit contribution here)
- 📍 Spring 2026: Community meeting in Bielefeld, hosted by colleagues from BiCDaS

We are truly grateful for the great commitment shown by the community – and warmly invite everyone to get involved in the next steps!

➡️ If you would like to contribute, discuss ideas, or actively participate, please feel free to contact Lena Steinmann at any time.

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

Call for Papers | INFORMATIK 2025 Workshop
Previous networking events (Available in German only)
Sign up to E-Mail List of DS-Community (Available in German only)

Welcome to the DSC, Hermine!

Svenja Goers — Mon, 07 Apr 2025 10:00:00 +0200

Hermine is studying sociology in the Bachelor’s programme at the University of Bremen. Under the DataNord Initiative , she is currently doing a cross-institutional internship that will allow her to get to know different scientific institutions and gather practical experiences in the field of data science.

Hermine has already completed the first part of her internship. From February to March, she worked at the ifib (Institute for Information Management Bremen GmbH). There she supported the realization of the DataNord subproject “We The (Social) Media: Social Media by and for Social Movements ” (more about the project ).

In the coming weeks, Hermine will continue her internship at the Data Science Center. During this time, she will accompany and support our DSC help desk employees Susanne de Vogel (social sciences focus) and Nele Fuchs (humanities focus) in the area of data science support to gain insights into the topics of research data management and data science.

Hermines tasks will include, for instance, conducting research, attending team meetings and data science consultations, as well as assisting in the preparation of data literacy workshops.

We welcome Hermine and wish her an interesting and enriching time at the DSC!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel.: +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

DataNord Website
We The (Social) Media-Project (Available Only in German)

The DSC Supports a Data Science Project Analysing the Determinants of Cryptocurrency Trends

Svenja Goers — Thu, 01 May 2025 09:00:00 +0200

Momentum is one of the most prevalent concepts in capital market research. The term describes the phenomenon that assets which performed well (or poorly) in the past, tend to continue to do so in the future. Explanations for the sources of momentum, however, remain diverse and include both, economic factors and behavioural biases.

Moreover, momentum captures only a narrow aspect of the broader phenomenon of “trend” on cryptocurrency markets. Several studies have demonstrated that combining different trend signals into a comprehensive measurement leads to significantly more accurate results than simple momentum. The focus of the funded research project is to investigate whether the drivers of trend predictability in cryptocurrency markets stem from behavioural biases (e.g. limited attention or underreaction) or economic fundamentals (e.g. risk premia or liquidity effects).

In addition, the project aims to adapt and further develop existing methodologies for understanding and identifying the sources of momentum in the specific context of cryptocurrency markets. Next to traditional momentum measures, the so-called CTREND indicator will also be examined. CTREND is a novel machine-learning based trend factor that aggregates data from a wide range of technical indicators into a single, comprehensive measure of trend.

To enrich the empirical and theoretical foundation of the project, Emmanuel Opoku is going to travel to Concordia University in Montreal (Canada). There, he will collaborate with Professor Thomas Walker, a leading expert in the field of sustainable finance research. The cooperation aims to promote international academic exchange as well as further expand the behavioural finance perspective of the project.

Funding recipients:

Dr. Gerrit Liedtke (Faculty 07 – Business Economics)
Emmanuel Opoku (Faculty 07 – Business Economics)
Thomas J. Walker (Concordia University – Montreal, Canada)

Funding period:

May 2025 - January 2026

Are you interested in the DSC Seed Grant?

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Open Resources for Geoscience Data Science Training: DSC at the EGU General Assembly 2025

Mon, 05 May 2025 08:00:00 +0200

The EGU is one of the world’s largest and most diverse conferences in the field of geosciences. It provides a platform for researchers from around the globe to discuss current developments, interdisciplinary approaches, and societally relevant questions in the context of environment, climate, and Earth systems.

At the conference, Annika Nolte, one of our data scientists for environmental and marine sciences, contributed to the session EOS2.1 – “Open session on Teaching & Learning in Higher Education” with her presentation “Open Resources for Geoscience Data Science Training: Insights from the Data Competence Center DataNord”. At the heart of Annika’s talk was the question: How can we systematically and sustainably promote data literacy in the geosciences? She introduced the Geoscience x Data Science OER Guide – a freely accessible collection of metadata about where to find Open Educational Resources (OER) for research and teaching at the intersection of geoscience and data science, published on GitHub . The guide is aimed at researchers pursuing self-study, as well as educators and institutions looking to enhance the efficiency of their existing training programs.

In addition to her own contribution, Annika used the conference as an opportunity to network with other initiatives working to strengthen data literacy in geoscience research. She also explored current developments in machine learning and artificial intelligence – focusing particularly on their discipline-specific applications, challenges, and potentials. These insights will feed into both the support provided to researchers and the development of new training formats within the DataNord project.

Please contact us if you have any questions:

Annika Nolte, M.Sc.
Data Science Support
Meeres- und Umweltwissenschaften
Tel. +49 (421) 218 - 59856
E-Mail: anolte@uni-bremen.de

Further Links:

Abstract (DOI: 10.5194/egusphere-egu25-11877)
Data Science OER Guide: Geosciences (GitHub)

Welcome to the DSC, Svenja!

Svenja Goers — Tue, 06 May 2025 08:30:00 +0200

Under the DataNord initiative (more on the DataNord project ), Svenja has recently joined the Data Science Center as our new team assistance. From now on, she will support the DSC with a variety of administrative tasks. These include the supervision of student assistants, the organization and planning of business trips, as well as various project-related activities.

We are excited to welcome Svenja to our team and look forward to working with her!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

DataNord Website

Dr. Sana Hassan Imam successfully defended her dissertation

Wed, 21 May 2025 08:00:00 +0200

Crowdsourcing platforms are digital spaces where individuals contribute their ideas, skills, or resources toward a shared goal. These platforms have become essential tools in todays connected world, taking different forms. For example, crowdfunding platforms like Kickstarter and Indiegogo help people and organizations raise money for creative projects, social causes, or new businesses. Innovation platforms like OpenIDEO give users a space to share and improve ideas to solve tough social and environmental problems. Labor marketplaces like Upwork connect businesses with freelancers who offer specific skills. Macrotask platforms like Arcbazar host design competitions where users submit solutions to particular challenges.

The success of these platforms depends on one key factor: user engagement. Engaged users keep the platform active, contribute work and resources, and build a strong, collaborative community. This active participation speeds up problem-solving, encourages new ideas, and creates a shared sense of purpose. However, keeping users engaged is challenging. Without strong engagement, even the best-designed platforms can slow down, with users losing interest, contributing less often, or leaving the platform entirely. This makes it crucial to understand what drives user engagement and to create strategies that keep users motivated, involved, and participating regularly over time. Hence, user engagement is the heart of crowdsourcing platforms. It transforms crowdsourcing platforms from simple tools into lively communities where innovation, teamwork, and creativity grow, helping these platforms remain relevant, effective, and successful in a fast-changing digital world.

Sana Hassan Imam explored the multifaceted nature of user engagement in crowdsourcing platforms, focusing on the challenges and opportunities that shape user participation. By examining factors such as intrinsic and extrinsic motivation, platform design, trust and transparency, and social influence, her research develops data-driven solutions to enhance engagement. She proposed the integration of AI-driven technologies, such as interactive chatbots for creative stimulation, machine learning models for long-term engagement, and transparency mechanisms for building trust in crowdfunding. Additionally, structured peer feedback systems and gamification strategies are introduced to improve user interaction. By addressing these challenges, her study offered a comprehensive framework to optimize user engagement in crowdsourcing environments, ensuring personalized, transparent, and interactive participation experiences. The findings contribute to the fields of human-computer interaction, AI-driven engagement strategies, and the optimization of crowdsourcing platforms.

The whole DSC team congratulates Dr. Sana Hassan Imam on the successful defense of her dissertation!

If further questions arise, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Data Science Center at the Research Data Day 2025

Svenja Goers — Thu, 12 Jun 2025 10:00:00 +0200

Under the motto “FAIR future skills”, the “Research Data Day” (TdF) took place at the University of Bremen for the third time this June. The event aimed to foster exchange on the FAIR handling of research data and offered participants the opportunity to acquire practical skills in the field of research data management.

The Research Data Day is organised under the DataNord Project , the interdisciplinary data competence centre for the Bremen region. DataNord offers researchers and students from all disciplines and career stages a wide range of services to enhance their data handling skills throughout the entire data lifecycle.

The program of this year’s Research Data Day included a diverse mix of talks, workshops, and other interactive formats on the topic of FAIR research data. Featured on the agenda, for instance, was an on-campus Data Snack session by DSC Data Scientists Dr. Susanne de Vogel and Sarah Büker. Their presentation “Tupperware Your Data - Keep Your Data Fresh, Organized & Ready to Serve” addressed different hands-on strategies for the sustainable organization of research data.

In addition, the Data Science Center also participated in the so-called DataNord Data Bar in the Glass Hall. The Data Bar gave students and researchers the opportunity to talk to different data experts and ask them questions about data management and FAIR research.

The Research Data Day concluded with an evening event at the Bremen Parliament, which was organized under the theme “Using data together: FAIR solutions for a better society”. The event’s agenda included several speeches on the topic of data literacy and data skills, a panel discussion, as well as the presentation of the Data Champion Award 2025.

With its diverse program, the Research Data Day 2025 fostered interdisciplinary exchange and sparked interesting discussions surrounding the topic of FAIR research data management. The DSC is already looking forward to contributing to next year’s Research Data Day!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

More on DataNord
Retrospective Research Data Day 2025

Welcome to the DSC, Timo and Hannes!

Svenja Goers — Tue, 01 Jul 2025 08:30:00 +0200

Timo Laudi completed his Bachelor's degree (2018) and Master's degree (2021) in Computer Science at ETH Zürich. During his studies, he focused on machine learning, computer graphics, and computer vision. After graduating, he moved to Bremen, where he worked until 2025 as a software engineer in the field of e-commerce at neuland, where he was responsible for developing, maintaining, and deploying complex systems.

From now on, Timo will work as a research associate at the DSC. He will manage the infrastructure and IT services of the DSC and provide support to its users. As part of his doctoral research, Timo focuses on techniques and methods aimed at making artificial intelligence more sustainable and efficient. His research aims to enable decisions during the design-phase which improve energy-efficiency and performance of machine learning models on different hardware platforms. The goal is to make applications more research-efficient from the start, by analysing bottlenecks early on.

Furthermore, we are excited to welcome a new intern to the DSC. Hannes is currently studying political science at the University of Bremen. Under the DataNord Project , he is currently completing a cross-institutional internship that gives him the opportunity to gain practical experience in the field of data science.

The first part of his internship, Hannes is spending at the Data Science Center under the guidance of DSC data scientist Dr. Susanne de Vogel. In the coming weeks, he will support our team with different tasks while gaining insights into the diverse activities of the DSC.

The second half of his internship, Hannes will complete as part of Data Train, under the supervision of coordinator Dr. Lina Schaare. Data Train is a training program of the U Bremen Research Alliance (UBRA) that aims to teach interdisciplinary skills in the areas of research data management (RDM) and data science.

We are happy to welcome Timo und Hannes to the team and look forward to working together at the DSC!

Please contact us if you have any questions:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

DataNord Website
DataTrain Website

Data Nord Summer Meeting

Svenja Goers — Fri, 04 Jul 2025 08:30:00 +0200

Data Nord (more here ) is a BMBF (Federal Ministry of Education and Research) funded project that consolidates expertise in the areas of research data management (RDM) and data science. It offers researchers from all disciplines and career stages a wide range of services to enhance their data handling skills. The interdisciplinary data competence centre is a cross-institutional initiative that brings together various project partners and aims to establish a sustainable FAIR data culture.

Once a year, a DataNord meeting is held, to keep up to date with current developments, share project updates, and promote exchange between project partners. The event also offers participants the opportunity to discuss future collaborations across the different teams and institutions involved.

Part of the Data Nord project is the Research Academy , which comprises five cooperative sub-projects:

HealthyPlanet project - Lead: Leibniz Institute for Prevention Research and Epidemiology – BIPS
MRI4All - Co-lead: German Research Center for Artificial Intelligence (DFKI) & University of Bremen
SmartReps - Lead: Alfred-Wegener-Institute (AWI)
SynData - Lead: University of Bremen
WeTheSocialMedia - Lead: Institute for Information Management Bremen (ifib)

As part of this year's summer meeting, members from all the institutions involved came together to present their project work to each other. In addition, the DataTrain program of the U Bremen Research Alliance (UBRA) and the training and help desk services of the Data Science Center (DSC) were presented.

Fragen beantwortet:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Further Links:

DataNord Project
Research Academy

DSC Supports the Organization of the “Summer School for Women in Political Methodology” at the University of Bremen

Svenja Goers — Wed, 16 Jul 2025 08:30:00 +0200

The Summer School aims to counteract existing gender inequalities in academia. Studies have shown that women continue to be underrepresented in the field of data science. This imbalance is particularly pronounced in the field of computer-based methods in the social sciences.

The “Summer School for Women in Political Methodology” offers training and mentoring, with a particular focus on female political and social scientists in the early stages of their careers. The event allows participants to acquire and develop skills in the application of computer-based methods. In addition, it supports women in building valuable contacts and networks in the science community. The Summer School is part of a long-term initiative aimed at advancing the education and careers of women in quantitative research in a sustainable manner.

This year, the Summer School takes place at the University of Bremen. The seven-day program includes training in various computer-based methods, such as web scraping and large language models (LLMs). Also on the agenda is a supervised hackathon, which will allow participants to work on their own projects. The Summer School is organised and taught by established experts from the field of social and political sciences. It thus offers a supportive and cooperative learning environment that promotes networking between emerging and established female researchers.

In addition, participants are recruited internationally and represent a range of European universities. Consequently, the summer school also promotes international exchange and cooperation.

Funding recipients:

Prof. Dr. Sophia Hunger (Faculty 08 – Social Sciences, SOCIUM)
Sophia Roppertz (Faculty 08 – Social Sciences, SOCIUM)

Funding period:

July 2025

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

We Are Looking For Student Support!

Tue, 14 Oct 2025 12:00:00 +0200

Still looking for a student job to kick off the semester? 🚀👀

We are hiring a motivated student assistant (m/f/d) to start as soon as possible, for up to 38 hours per month.

The position is flexible, long-term, and offers insight into an exciting working environment.

We look forward to receiving your application!

You can find all details on how to apply here (Available in German only)

If you have questions about the position, please contact:

Dr. Lena Steinmann
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DSC at the Joint Plenary 2025 of NFDI4Biodiversity and NFDI4Earth

Thu, 25 Sep 2025 13:05:00 +0200

From 22 to 25 September 2025, the J oint Plenary 2025 von NFDI4Biodiversity und NFDI4Earth took place at MARUM – Center for Marine Environmental Sciences at the University of Bremen. The event brought together researchers, data stewards, and practitioners working with biodiversity and environmental data to exchange ideas and discuss current challenges in research data management.

The National Research Data Infrastructure (NFDI) connects scientific communities across Germany to ensure that research data remains discoverable, interoperable, and reusable over the long term. The Joint Plenary offered an important space for strengthening collaboration between different consortia and developing shared data management approaches.

The Data Science Center (DSC) contributed to the programme with an interactive workshop delivered as part of the BMFTR-funded project “Interdisciplinary Data Literacy Center for the Bremen Region – DataNord”.

Under the title “From Data to Interactive Maps: Visualization Workflows with Geospatial Data from PANGAEA”, Sarah and Annika presented Python-based workflows for processing and visualizing geospatial data. Participants learned how to access research data via the PANGAEA Data Publisher for Earth & Environmental Science API and explored the complete workflow from data retrieval and preprocessing to the creation of interactive maps using Python.

The workshop material are openly available on GitHub.

More information on all our current projects can be found here.

If you have any questions, feel free to contact:

Annika Nolte
Data Science Support | Environmental and Marine Sciences
Tel. +49 (421) 218 - 59856
E-mail: anolte@uni-bremen.de

Additional Links:

DataNord Website
NFDI4Earth
NFDI4Biodiversity

DSC hosts 3rd Data-Science-Community Workshop at the INFORMATIK 2025

Svenja Goers — Thu, 18 Sep 2025 08:00:00 +0200

This year's INFORMATIK festival took place in Potsdam under the motto “The Wide Open: Openness from Source to Science.” This time, the thematic focus was centred on exploring open access and processes within an increasingly digital and interconnected world. The conference offered a broad program covering a variety of topics such as data science, artificial intelligence, green coding, software engineering, research data, and data literacy.

The program also included the Data Science Community Workshop “Current Developments and Perspectives (at Universities) in the Field of Data Science,” which was held for the third time already. The event was co-organized by the Data Science Center (Prof. Dr. Rolf Drechsler & Dr. Lena Steinmann) and the Digital Science Center of Kiel University (Prof. Dr. Dirk Nowotka & Dr. Helen Pfuhl).

The workshop aims to bring together members from a wide range of data science initiatives to further promote interregional networking and collaboratively develop relevant focus areas and perspectives for the community. By facilitating exchange around current challenges, best practices, strategic approaches, and potential for future collaborations, the workshop fosters the sustainable development of the community.

The event's program included several talks from members of the data science community as well as a poster session. Part of the latter was the contribution “Training, Consultation, and More – Services from the Data Science Center,” which was presented by DSC data scientist Dr. Maryam Movahedifar. Here you can find the responding publication - Movahedifar et al. (2025). In addition, this year's workshop also included the introduction of the first position paper developed by the data science community. The event concluded with the establishment of the Data & Digital Science Community association (DaDiSC) whose executive board team includes Prof. Dr. Dirk Nowotka (University of Kiel), Prof. Dr. Rolf Drechsler (University of Bremen), and Dr. Martin Semmann (University of Hamburg).

More information about the INFORMATIK festival 2025 and the DSC’s contribution can be found in the digitally published conference proceedings. The next INFORMATIK will take place in September 2026 at TU Dresden. More information on the event is available here.

Further Links:

Website INFORMATIK 2025
Program Community Workshop 2025
Website DaDiSC - Data & Digital Science Community Association
Link Conference Proceedings INFORMATIK 2025
Link Workshop Article (Steinmann et al., 2025)

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Data Journalist Starts Residence Fellowship at the DataNord Project

Svenja Goers — Wed, 01 Oct 2025 08:00:00 +0200

Data journalism provides an important link between research and society. By presenting data-based research in a factual and comprehensible way, complex issues can be communicated to a broad audience in an interesting and captivating manner. Thus, data journalism contributes to promoting transparency and social exchange, as well as the responsible use of data.

The Data Journalist in Residence Fellowship (Oct.-Dec. 2025) of the DataNord project (the Data Competence Center for the Bremen Region) aims to promote collaboration by sharing the expertise of data journalists with researchers. As part of the DataNord subproject of the Data Science Center, data journalist Serafin Arhelger will provide researchers with practical skills in communicating data-based research. Serafin Arhelger has been working in the field of data journalism for many years. Since August 2022, he has been part of the NDR Data Team where he prepares public data in ways that make it accessible and understandable for the general public. You can find out more about Serafin Arhelger and his work as a data journalist here.

During his residence fellowship at DataNord, Serafin Arhelger will use different formats to demonstrate what preparations are necessary to make research data and study results accessible and usable, both for academic publications and the general public. Upcoming events include an interactive learning workshop on data journalism methods as well as a Data Story about his work as a data journalist (more information here). In addition, Serafin Arhelger will offer “consultation hours” for individual advice during his fellowship. More information on the different events will be available here shortly.

We wish Serafin Arhelger an enriching and interesting time during his fellowship at DataNord and look forward to his contributions on the topic of data journalism.

Further Links:

Interview with Serafin Arhelger

Data Story about working as a Data Journalist (20 October 2025, 3-4 PM)

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DSC Hosts Community Workshop at INFORMATIK 2024

Sat, 09 Nov 2024 08:00:00 +0100

Following the theme "Lock-in or Log out? Achieving Digital Sovereignty" of this year's INFORMATIK Festival in Wiesbaden, the DSC held an interactive workshop on September 26th. The cross-regional talk invited guests from Germany, Austria, and Switzerland to promote sustainable networking within the community and lay the foundation for future collaboration between the DSC and other data centers. Together, we discussed the opportunities and challenges of the digital age, setting the stage for joint reflection and the development of new initiatives.

The forum provided an interactive platform for exchanging activities, concepts, experiences, solutions, and best practices among the various initiatives.

The DSC team thanks all participants for the fruitful discussions and talks!

Further Links:

Website GI Data Science Workshop (Available in German only)
Link to Conference Proceedings
Link to our Article (Available in German only)

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DSC Contributes to Study on Tobacco Outlets Along School Routes

Svenja Goers — Tue, 03 Jun 2025 08:00:00 +0200

The study systematically investigated the number of tobacco outlets located in the immediate vicinity of schools. The results clearly show that schoolchildren in Bremen regularly pass tobacco outlets on their school routes and are therefore exposed to tobacco advertising. On average, there are 7.46 tobacco outlets in the vicinity of every school in Bremen (within 500 meters of the school route). More information about the study's results can be found here.

These figures are relevant in the context of smoking prevention, as tobacco products can still be advertised at and in retail outlets. The number of sales outlets thus provides information on the extent to which children and adolescents are directly exposed to tobacco marketing on their way to school and back. The study’s outcomes suggest that the presence of tobacco advertising as well as the placement of tobacco products alongside everyday goods (such as candy by the checkout) contribute to the normalization of smoking for children and teenagers.

The team of researchers also included DSC data scientists Annika Nolte and Dr. Susanne de Vogel, who contributed to the project by supporting the development of the study’s general method and the R workflow. The programming language R was used to calculate the distances between elements of urban infrastructure. Since no official public data on tobacco retail outlets is available from the authorities, the geographic coordinates and addresses were extracted from online map services (Google Maps) and then related to the locations of schools in Bremen.

The study provides the first city-wide dataset on tobacco outlets in school environments in a German city, thereby filling an important research gap. The results could be used as a basis for further preventive measures. For comparison, the same analysis was conducted on tobacco outlets in Hamburg. The data collected there is currently being evaluated. Once the analysis is finished, the researchers plan to compile the results and submit them for publication. The methodological approach and R workflow developed in the study will also be applied to another research project to investigate the relation between the availability of food sources and the eating habits of study participants.

Further Links:

Press Release Uni Bremen

If you have any questions, please contact:

Annika Nolte
DSC Data Scientist
Tel. +49 (421) 218 59856
E-Mail: anolte@uni-bremen.de

Dr. Susanne de Vogel
DSC Data Scientist
Tel. +49 (421) 218 63938
E-Mail: devogel@uni-bremen.de

Article About DataNord Published in the Proceedings of the E-Science-Days 2025

Svenja Goers — Thu, 06 Nov 2025 08:00:00 +0100

The E-Science-Days are an interdisciplinary conference focusing on the topics of research data management (RDM) and open science. The event serves as a central forum for discussion and exchange between experts from science, politics, and infrastructure. This year, the thematic focus of the conference was on current challenges around RDM and research data infrastructures, such as ensuring data quality and dealing with artificial intelligence and current (geo-)political developments.

The Data Science Center also attended this year's conference and was represented by DSC coordinator Dr. Lena Steinmann (we report here). In the session "Data Literacy" she gave a talk on the interdisciplinary data competence center of the Bremen region "DataNord", which aims to strengthen data literacy across all career levels and establish a sustainable FAIR data culture.

The contributions to the conference have now been published in the conference proceedings of the E-Science-Days 2025. The collection also includes the article "Bremen's interdisciplinary data competence center DataNord: An integrative approach for data literacy in research". The contribution gives an overview of the DataNord initiative and introduces its approach, offers, and activities in more detail.

The complete proceedings of the E-Science-Days 2025 are available at bookshops and can be accessed online here. Our article can be found here.

Further Links:

News-Article E-Science-Days 2025

Link to the Conference Proceedings

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC supports the Development of a SQL-Based Data Science Infrastructure for Digital Humanities

Svenja Goers — Fri, 03 Oct 2025 08:00:00 +0200

The interdisciplinary project AFROEUROPECYPERSPACE investigates how Afrodiasporic communities in Europe use the internet to establish alternative public spheres and reclaim the discourse surrounding their identities and histories. Part of the project is the development of a comprehensive, relational SQL database designed to document and analyze Afrodiasporic websites, online magazines, blogs, podcasts, video channels etc. across Romance-speaking Europe.

The project aims, among other things, to develop a typology by compiling an overview of digital platforms. To achieve this, the project team is developing a structured database catalog in which controlled vocabularies and relational metadata enable systematic categorization, classification, and evaluation of the growing body of digital sources. This is intended to make the increasing number of platforms manageable for the team as well as researchers using the data in the future.

The DSC Seed Grant supports the development of an interactive web-based research catalog built on SQL database infrastructure. Using a SQL-only data application builder, the project creates an interactive portal where researchers can explore the network through dynamic visualizations: geographic maps tracking author migrations across Romance-speaking regions, network diagrams revealing platform collaborations, and temporal analyses showing thematic evolution. The relational database structure enables sophisticated queries such as identifying authors who bridge multiple platforms, tracing theme co-occurrence patterns, or analyzing linguistic diversity across geographic regions. The system makes complex diaspora network analysis accessible through an intuitive web interface without requiring researchers to have prior programming expertise.

Hence, the initiative not only enhances the application of SQL-based methods in humanities research but also lays the foundation for future interdisciplinary projects, bringing together data science methodologies and digital humanities research.

Funding recipients:

Prof. Dr. Julia Borst (Faculty 10 - Linguistics and Literary Studies)
Liam Hurwitz (Faculty 03 - Mathematics/Computer Science)

Funding period:

01 October 2025 – 31 December 2025

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The DSC Supports Research Stay in Oslo for Baffin Bay Model Development (BaffinDATA)

Svenja Goers — Mon, 17 Nov 2025 08:00:00 +0100

The purpose of the two-day research stay is the collection and transfer of scientific data sets, including seismic profiles, petrophysical sediment properties, hydroacoustic data, and shallow gas indicators. The data will then be used to construct a 3D high-resolution Baffin Bay numerical model at the University of Bremen, in collaboration with Prof. Dr. Sverre Planke (University of Oslo).

Large-scale scientific 3D models of natural gas hydrate systems are currently only developed at MARUM (Center for Marine Environmental Sciences at the University of Bremen) and require both large amounts of digital data input and extensive computational resources. The model simulations and outputs advance gas hydrate research, providing unique insights into large-scale methane migration patterns in the marine subsurface and permafrost regions.

The Baffin Bay model will be employed to perform numerical simulations of sedimentary basin history as well as hydrocarbon generation, migration, and storage in the form of gas hydrate. It will allow predictions of major hydrocarbon deposit locations and seepage sites. These will enable more efficient and successful sampling strategies that will be applied during an upcoming Maria S. Merian research cruise to the Baffin Bay area (BaffinGAS, August-September 2026).

Funding recipient:

Dr. Ewa Burwicz-Galerne (MARUM – Center for Marine Environmental Sciences)

Funding period:

November 2025 – December 2025

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Strengthening Collaboration: DataNord at the NFDI4DataScience Conference

Wed, 26 Nov 2025 10:54:00 +0100

On 25 November, Tanja Hörner and Lena Steinmann presented the BMFTR-funded project “Interdisciplinary Data Literacy Center for the Bremen Region – DataNord” during the two-day NFDI4DataScience Conference (25–26 November). The community event took place at Fraunhofer FOKUS.

The overarching objective of NFDI4DataScience is the development, establishment, and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence research community. The key idea is to work towards increasing the transparency, reproducibility and fairness of projects, by making all digital artifacts available, interlinking them, and offering additional tools and services.

DataNord’s contribution highlighted the growing importance of connecting the NFDI community with regional data literacy centers – particularly as research becomes increasingly data-intensive and methodologically complex.

The DataNord umbrella project is based at the Data Science Center (DSC) at the University of Bremen, which also coordinates the overall consortium. The DSC subproject is building essential services and programmes to support learning, research, and interdisciplinary networking. A dedicated team of data scientists provides training, consultation, and community formats for researchers across all disciplines and career stages. Additionally, the research projects MRI4All and SynData are being implemented as part of the Research Academy, allowing to embed data competencies directly into the research process.

Learn more about all our research projects here.

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-mail: lena.steinmann@uni-bremen.de

Data Analytics in Focus: DSC Hosts World Café in the Data Community Club

Thu, 23 Oct 2025 15:27:00 +0200

The Data Community Clubwas established as part of the BMFTR-funded interdisciplinary data competency center “DataNord”. It connects data experts and enthusiasts from all disciplines and provides a space for exchange on research data management, data science, and related topics. Its regular meetings focus on discussing different practical approaches, challenges, and solutions with the goal of strengthening data literacy across the entire research data lifecycle.

On 22 October 2025, the Data Science Center (DSC) at the University of Bremen organized the autumn meeting of the Data Community Club – this time in an interactive World Café format. Researchers, data professionals, and interested community members joined to explore key topics in Data Analytics and learn from one another in rotating discussion rounds.

Five thematic tables formed the core of the event, each led by experts from the U Bremen Research Alliance and supported by moderators from the DSC team:

Machine Learning
Experts: Dr. Sonja Hänzelmann & Dr. Susana Simancas Giraldo (AWI); Moderator: Annika Nolte
Responsible Use of AI
Expert: Dr. Max Westphal (Fraunhofer MEVIS); Moderator: Sarah Büker
Generative AI
Expert: Floriann Deepika Louis (AWI); Moderator: Dr. Susanne de Vogel
Statistical Methods
Expert: Dr. Martin Scharpenberg (KKSB, University of Bremen); Moderator: Dr. Maryam Movahedifar
Natural Language Processing
Expert: Johanna Rockstroh (Digital Media Lab, University of Bremen); Moderator: Dr. Lena Steinmann

Participants took part in two 30-minute discussion rounds, sharing experiences, exploring challenges, and identifying opportunities and next steps. The key insights were later brought together in a final plenary session, offering valuable impulses for continued collaboration within the data community.

The World Café created an open, collegial atmosphere that encouraged participants to share expertise, learn from one another, and gather fresh inspiration for their research and data practices.

If you work at the University of Bremen or one of the DataNord partner institutes (listed here at the bottom) and are interested in hosting similar events on Data Science, Data Analytics, AI, or Research Data Management, feel free to get in touch – our team is happy to support you.

Additional Links

DataNord
Data Community Club

If you have any questions, feel free to contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-mail: lena.steinmann@uni-bremen.de

DataNord x WiNoDa Winter School 2025 – DSC Contributes Galaxy Expertise

Fri, 28 Nov 2025 16:33:39 +0100

From 24 to 28 November, the online WiNoDa Winter School “Research with Natural Science Collections: Data, Quality, and Methods” brought together researchers and curators working with object-based data. The five-day programme is organised by GFBio – German Federation for Biological Data e.V., the Museum für Naturkunde Berlin (MfN), the German Archaeological Institute (DAI) and the Vernetzungs- und Kompetenzstelle Open Access Brandenburg (VuK), in cooperation with NFDI4Biodiversity. The Winter School aims to build essential data skills needed to handle collection-based research data effectively and responsibly.

On 27 November, the DSC was represented by Sarah Büker, who gave a two-hour interactive introduction to the Galaxy-Project – an open, FAIR-oriented platform for transparent and reproducible data analysis in the life and environmental sciences.

Her workshop covered:

what Galaxy is and why it matters for researchers working with collection data,
how to conduct FAIR and transparent analyses with Galaxy,
how to run analyses and create visualisations without programming skills,
and how to get started and where to find more training resources.

The workshop drew on materials from the Galaxy Training Network and the European Galaxy Server. Participants from a wide range of disciplines took part, all united by their work with museum and scientific collections – resulting in lively discussions and a highly engaged group.

The DSC’s contribution also demonstrated the value of close collaboration between DataNord, WiNoDa, and the NFDI community. It highlighted the essential role of the DSC’s data competence team in ensuring that the University of Bremen and its DataNord partners are actively represented in national initiatives and able to help shape shared approaches to data skills and infrastructure.

Additional Links:

https://winoda.de/event/winter-school-de/

More about Galaxy:
https://usegalaxy.eu/
https://gxy.io/GTN:T00187

If you have any questions, please contact:

Sarah Büker
Data Science Support | Marine and Environmental Sciences
Tel. +49 (421) 218 - 59855
E-mail: sbueker@uni-bremen.de

Strengthening and Expanding Data Science – 40 Researchers Publish Position Paper

Mon, 24 Nov 2025 08:30:00 +0100

This article was first published by the University of Bremen. You can read the original press release here.

This demand was officially formulated in the “Positionspapier zur Zukunft der Data- und Digital Science-Community” (Position Paper on the Future of the Data and Digital Science Community). It was co-authored and signed by Rolf Drechsler, a professor of computer architecture and co-founder of the University of Bremen’s Data Science Center, and Lena Steinmann, the center’s coordinator. The University of Bremen and Kiel University are currently overseeing the establishment of the Data & Digital Science Community e.V. (DaDiSC), a nationwide network for data science research and the first of its kind in the German-speaking region.

Research with Large Datasets – A Multidisciplinary Phenomenon

Researching with large datasets is no longer limited to fields such as statistics and computer science, but has become a common practice in language and cultural sciences, history, and other fields as well. This is due to the role of modern technologies and digitalization in making increasing amounts of data from various sources available, including mobile networks, location data, open government city data, and health apps.

To sustainably strengthen data-intensive and digitally supported research, researchers are advocating for reliable and long-term funding for central institutions such as data and digital science centers. Currently, financing for these centers is often project-based, as seen in the eleven data competence centers supported by the Federal Ministry of Research, Technology and Space.

Researchers are urging policymakers to explicitly consider data and digital science in federal and state-funded research, digital, and innovation strategies, and to provide support through long-term funding programs.

Stronger Focus on Digital and Data Science in Research and Teaching

To supplement these political considerations, researchers are advocating for a stronger focus on digital and data science in research and teaching. This includes equipping digital and data science centers with the resources they need. The researchers believe that this would enable the provision of data and digital science services, including consultations, data management, and data analysis support, as well as facilitate collaborations between centers at different locations.

Furthermore, the researchers are emphasizing the importance of teaching data and digital literacy, which involves the ability to work with large datasets. They recommend providing broad support for this effort, including didactic and expert support for teachers, to ensure that competent use of data is taught in interdisciplinary courses across various degree programs. This would require collaboration between technical and non-technical disciplines.

Data and Digital Science at the University of Bremen

Since 2019, the University of Bremen has had its own interdisciplinary institute for data-based research, the Data Science Center (DSC). The university’s data-related competence and activities are bundled and developed here. The center aids in networking researchers across disciplinary boundaries, strengthening their data skills, and creating the requirements for sustainable, data-based research in all academic areas.

In its role as a central contact point, the DSC offers a range of services for researchers, including consultations, training, financial support, and computing resources, and serves as a partner in data-based research projects. The DSC is also home to the competence center DataNord, which is led by the University of Bremen in collaboration with other Bremen partner institutions, with Rolf Drechsler as one of the spokespersons. Since 2023, DataNord has received over 3.5 million euros in funding from the Federal Ministry of Research, Technology and Space.

Further Links:

Link Press Release Uni Bremen: Original Article

Link Position Paper: https://zenodo.org/records/17475528

„Data & Digital Science Community e.V. (DaDiSC): https://dadisc.org/ (Website still in development)

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
E-Mail: lena.steinmann@uni-bremen.de

DSC Supports PACE Challenge 2025

Mon, 18 Aug 2025 11:15:00 +0200

This year, the Theoretical Computer Science Group of the University of Bremen’s Faculty 03 – led by DSC member Prof. Dr. Sebastian Siebertz – hosted the international PACE Challenge. Together with Dr. Mario Grobler, he formed the program committee responsible for the scientific and organizational direction of the competition. Around 70 teams from across the globe took part, working on complex algorithmic tasks. The Challenge has been held annually since 2015 and focuses each year on new mathematical and algorithmic topics.

What is the PACE Challenge?

The PACE Challenge focuses on problems that are difficult (for computers) to solve because they require exploring or comparing a large number of possible solutions. In 2025, two problem types were at the center of the competition: Dominating Set and Hitting Set.

The teams developed their own algorithmic solution approaches (“solvers”) and competed against one another. Submissions were evaluated based on criteria such as correctness, solution quality, and computational efficiency.

The Challenge provides a platform for researchers worldwide to compare, refine, and openly share their approaches. In doing so, it helps theoretical research gain practical traction – for instance in data analysis, network design, or AI-related applications.

DSC provides the technical infrastructure

To ensure that all solvers could be evaluated under identical and reliable conditions, the DSC provided the IT infrastructure used to run the Docker-based evaluation environment. The environment itself was developed by Dr. Mario Grobler, with technical support from DSC colleague Nils Leusmann in adapting and running it on our infrastructure. This setup was essential for a fair and reproducible assessment process and highlights how valuable the DSC’s technical expertise is for supporting complex scientific activities at the University of Bremen.

The DSC’s contribution illustrates how effectively the University of Bremen combines research and technical capability. By helping to ensure the smooth operation of an international competition like PACE, the DSC strengthened the visibility of Bremen’s computer science community within the global research landscape. At the same time, the collaboration between the Theoretical Computer Science Group and the DSC shows how important well-coordinated cooperation across university units is for successfully delivering ambitious scientific events.

The winners of this year’s competition were announced in August 2025 (more information available here).

If you need support in implementing a similar format, feel free to contact us.

Additional Links:

https://pacechallenge.org/2025/
AG Theoretische Informatik
Moe about our DSC-IT

For general questions, please contact:

Dr. Lena Steinmann
DSC Koordinatorin
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

FAIR Data at 38C3: DSC Brings Data Skills to the Tech Community

Thu, 02 Jan 2025 16:04:00 +0100

From 27–30 December 2024, the 38th Chaos Communication Congress (38C3)took place in Hamburg – one of the world’s most renowned events on technology, society, and digital culture. Since 1984, the Congress has been organized by the community of the Chaos Computer Club (CCC) and thrives on the active participation of its attendees. Under this year’s motto “Illegal Instructions”, several thousand people gathered to explore creative, critical, and playful perspectives on technology and its societal implications through talks, workshops, and assemblies.

FAIR Data – explained in a clear and accessible way

On 29 December, Sarah Büker, Data Scientist in the DataNord project at the Data Science Center (DSC) of the University of Bremen, led a two-hour introductory workshop on FAIR data, metadata, data management plans, and the research data lifecycle.

With humor and practical examples, her workshop „FAIR enough? Handling Research Data like a Pro“ spoke to everyone who works with data but still files it under names like “final_v2_REALLY_FINAL.csv.” The workshop covered:

what FAIR actually means
why documentation and metadata matter across all fields and career stages
what realistic, manageable data practices look like
where to look for help when data chaos sets in

Whether you work with data every day or only stumble over it occasionally – the session offered an easy entry point into the topic and addressed common challenges from everyday research practice, particularly in the natural and life sciences.

In addition, Sarah organized and moderated the discussion session “How to Thrive in Chaos”, where more than 250 participants discussed challenges, strengths, and practical strategies for neurodiverse ways of working in research.

DSC strengthens data skills beyond academia

Sarah Büker’s contribution illustrated how the DSC, through its DataNord project, helps strengthen research data skills beyond traditional university contexts. By contributing to the 38C3, this knowledge reached interdisciplinary communities, labs, hackspaces, and the broader digital civil society – places where data play a central role in creative, experimental, and everyday contexts, even though FAIR principles are often not widely known. In doing so, the DSC contributes to improving data literacy across society.

Additional links:

38. Chaos Communication Congress (38C3)
DataNord

If you have any questions, please contact:

Sarah Büker
Data Science Support | Umwelt- und Meereswissenschaften
Tel. +49 (421) 218 - 59855
E-Mail: sbueker@uni-bremen.de

Data Literacy in Survey Research: DSC at ESRA 2025

Mon, 21 Jul 2025 08:30:00 +0200

At the 11^th European Survey Research Association (ESRA) Conference 14-18 July 2025 in Utrecht, data scientist Dr. Susanne de Vogel presented the work of the interdisciplinary help desk established at the Data Science Center (DSC) as part of the BMFTR-funded data competence center DataNord. The biennial ESRA conference is one of the largest international events in survey methodology, bringing together experts from across Europe and beyond to exchange insights on innovations in survey research.

On her poster “Empowering Data Literacy for Survey Researchers: Insights from the Interdisciplinary Help-Desk of the Data Competence Center ‘DataNord’”, Susanne highlighted how the DSC supports researchers in navigating the growing complexity of modern survey research. These include integrating data science methods, new data types, such as social media or administrative data, ethical–legal–social aspects (ELSA), and fostering critical thinking in data use and analysis.

The presentation showcased trainings, individual consultations, and collaborative networks that help strengthen data literacy of survey researchers across disciplines. A key strength of the help-desk is its interdisciplinary team composition. By combining expertise from, social sciences, statistics, natural sciences and humanities, the DSC is able to connect perspectives:

For survey researchers, the help-desk provides training and consultation to strengthen their ability to work with complex data sources, adopt methods from data science, and integrate approaches from other disciplines.
For researchers outside the field of social sciences, the DSC offers support in designing and implementing surveys, especially for those without formal training in survey methods.

The poster presented at ESRA 2025 is openly available on Zenodo: Empowering Data Literacy for Survey Researchers. By showcasing examples and best practices from the DataNord help-desk, the contribution underlined the importance of data literacy as a core competency for today’s survey researchers – from beginners to advanced practitioners. More information about the conference can be found on the ESRA 2025 website.

The DSC’s participation in ESRA 2025 highlights the growing importance of data literacy in international survey research. With its interdisciplinary approach, the DSC brings together methodological, social science, and data science perspectives to address key challenges in contemporary survey research. At the same time, the exchange with the international research community provides valuable insights that feed directly into the further development of the DSC’s consulting and training services within the DataNord project.

Further Links:

More about ESRA 2025
Link to the Poster on Zenodo

If you have any questions, please contact:

Dr. Susanne de Vogel
DSC Data Scientist
Tel. +49 (421) 218 63938
E-Mail: devogel@uni-bremen.de

Starting Early, Making an Impact: DSC Supports Data Skills at ICYMARE 2025

Svenja Goers — Mon, 15 Sep 2025 08:00:00 +0200

The “International Conference for Young MArine REsearchers” (ICYMARE) is a yearly conference organized by early-career scientists. In 2025, the conference took place from 8–13 September at Bremerhaven University of Applied Sciences, bringing together 230 participants from 37 countries. The program covered a wide range of topics, including marine biogeochemistry, sustainable marine governance, marine conservation, and marine bioacoustics. The program featured various keynotes, round tables, interactive workshops, a poster session, as well as an excursion to the Klimahaus in Bremerhaven.

The Data Science Center (DSC)supported the conference as a sponsor through a DSC Seed Grant (read more here). For the DSC, ICYMARE is a great venue for addressing data skills early in academic careers. Early-career researchers increasingly work with complex, data-intensive methods, yet often lack structured training in research data management and data science. Through its involvement, the DSC helped raise awareness of data-related topics and communicated them in a practical, discipline-specific way. At the same time, direct exchange with early-career scientists provided valuable insights into concrete needs and challenges, which feed directly into the ongoing development of the DSC’s consulting, training, and support services.

The DSC was also actively involved in the conference program:
Dr. Lena Steinmann, coordinator of the DSC, delivered a keynote entitled “Recognizing Your Data Skills: How to Expand Your Career Horizons as a Marine Scientist,” highlighting how data skills can broaden career perspectives in the marine sciences.
In the poster session, Nils Leusmann, research associate at the DSC within the BMFTR-funded project INDIFUN-AI, presented his work “A semi-automatic image clustering pipeline to support taxonomic plankton classification.”
In addition, Sarah Büker, Data Scientist in the BMFTR-funded DataNord project, organized the conference’s first Data Corner – an open exchange format that enabled participants to discuss data, code, workflows, and everyday research challenges in an informal setting. Due to the very positive response, the Data Corner is expected to remain part of the ICYMARE program in the future. Sarah Büker also moderated a roundtable on Neurodivergence in Science, creating space for personal exchange and discussion.

Why This Matters

ICYMARE clearly demonstrates the value of low-threshold, community-driven formats for early-career researchers. The DSC’s engagement highlights its commitment to fostering data skills not only centrally, but also in a domain-specific and practice-oriented way.

We are already looking forward to ICYMARE 2026, which will take place in Bremen from 7–11 September 2026.

Further Links:

Official website ICYMARE
Book of Abstracts

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-mail: lena.steinmann@uni-bremen.de

When Data Meets Society: New Conference Contribution on Online Hate Speech and Data Literacy

Mon, 13 Oct 2025 16:53:00 +0200

For the 5th Conference of the Academy of Sociology, held from 8 to 10 October 2025 at Johannes Gutenberg University Mainz under the theme “Societal Changes – Sociological Answers”, Dr. Susanne de Vogel (Data Science Center, University of Bremen) and Ricarda Luther (ifib), together with Dr. Lena Steinmann and Prof. Dr. Rolf Drechsler (Data Science Center, University of Bremen), prepared the poster “Interventions to Socio-Technical Problems: Data Literacy and the Case of Online Hate Speech.”

What is the poster about?

The contribution shows how societal challenges such as misinformation, algorithmic bias, and online hate speech are closely linked to digital infrastructures and data practices. To study these phenomena and develop meaningful societal responses, social scientists increasingly need strong data skills. At the same time, significant gaps in data literacy remain – particularly in the social sciences.

How DataNord addresses this gap

This is where the Data Science Center (DSC) comes in through its work within the BMFTR-funded DataNord project. As a key part of the regional data competence center, the DSC supports researchers through:

Tailored training in data management, data analysis, and critical data use
Individual consultation on data collection and analysis strategies
Networking opportunities that foster interdisciplinary exchange

At the DSC, Dr. Susanne de Vogel serves as a contact person for social scientists. She advises, trains, and supports researchers across the entire DataNord network, helping to build sustainable data-related skills in the region.

A central role is also played by the DataNord Research Academy, where methods specialists and domain experts collaborate across five joint research projects. By combining data science approaches with disciplinary expertise, the Research Academy promotes advanced data competencies and embeds them directly in research practice – contributing to the development of a future-oriented data culture.

Example project: “We the (Social) Media”

One of these projects, “We the (Social) Media”, is addressed in the poster to illustrate how participatory, data-informed research can help better understand online hate speech. The project is based at the Institut für Informationsmanagement Bremen GmbH (ifib), implemented by Ricarda Luther, and led by Prof. Dr. Andreas Breiter.
The project works closely with activists who are themselves affected by online hate speech, involving them directly in the research process. Together, they develop user-centered moderation tools that bring together sociological perspectives and data-driven methods. Project partners include Prof. Dr. Stephanie Geise (ZeMKI, University of Bremen), Prof. Dr. Sebastian Haunss (SOCIUM, University of Bremen), and Prof. Dr. Hendrik Heuer (Center for Advanced Internet Studies).

Why does this matter?

Digital data increasingly shape how research is conducted and how societal problems are understood. At the same time, knowledge about data quality, methods, ethics, and critical data use is unevenly distributed. This poster contribution highlights how the DSC and DataNord help close this gap – supporting researchers and affected communities alike in engaging with digital developments in informed and responsible ways.

Due to a short-term illness, the poster could not be presented in person. However, both the poster and abstract have been published on Zenodo: https://zenodo.org/records/17142514

Additional Links:

DSC Consulting offers for researchers
DataNord website
DataNord Research Academy
We The (Social) Media

If you have any questions, please contact:

Dr. Susanne de Vogel
DSC Data Scientist for Social Sciences
Tel. +49 (421) 218 63938
E-mail: devogel@uni-bremen.de

INDIFUN-AI Project Meeting at the AWI

Svenja Goers — Fri, 10 Oct 2025 08:00:00 +0200

From October 7 to 9, the annual INDIFUN-AI project meeting took place at the Alfred-Wegener-Institute (AWI) in Bremerhaven. INDIFUN-AI is a BMFTR-funded research project that investigates marine biodiversity. INDIFUN-AI aims to better understand the diversity and function of marine fungi and fungal-like organisms in the marine food web. The project thereby contributes to a better assessment of climate-induced changes and the identification of reliable indicators for these changes.

INDIFUN-AI is an interdisciplinary joint project carried out in collaboration with several institutions and under the lead of the AWI. As part of the University of Bremen's subproject, the Data Science Center (DSC) is developing an automated indicator system that reliably detects changes in biodiversity. More information about the subproject can be found here.

At this year's project meeting, representatives of the different project partners came together to discuss recent developments and strengthen the cooperation between the participating institutions. Different contributions of the respective subprojects provided the basis for joint discussions surrounding current and future project activities.

The subproject of the University of Bremen was represented by Dr. Lena Steinmann (DSC coordinator), Nils Leusmann (DSC), and Christina Plump (University of Bremen, DFKI), with Nils Leusmann and Christina Plump providing an overview of the DSC's current activities within the INDIFUN-AI project. DSC data scientist Sarah Büker also took part in the event to share her expertise in the field of data management. As part of the project meeting, the participants also worked together on the development of a data management plan.

All Project Partners:
Alfred-Wegener-Institut (AWI) (coordinating institution)
Universität Bremen
Carl-von-Ossietzky Universität
GEOMAR Helmholtz Centre for Ocean Research Kiel
Leibniz Centre for Tropical Marine Research (ZMT)
AquaEcology GmbH & Co. KG

Additional Links:

Project Website INDIFUN-AI
More about the Subproject of the University of Bremen

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-mail: lena.steinmann@uni-bremen.de

New Publication in NomosHandbuch Hochschulforschung

Tue, 16 Sep 2025 10:54:00 +0200

Published in September 2025, the NomosHandbuch Hochschulforschung – Forschung über Hochschule und Wissenschaft (German-language only) has been released for the first time as a comprehensive open-access reference work that brings together current knowledge in higher education research. The volume includes a contribution by our DSC colleague Dr. Susanne de Vogel.

Together with Kolja Briedis and Gesche Brandt, Susanne de Vogel co-authored the chapter “Prä-Docs und Promotion”. It provides a solid overview of key issues related to the doctoral phase, including access routes to doctoral studies, different models of doctoral training, debates around fixed-term employment and working conditions (#ichbinhanna), quality assurance, doctoral dropout, work–life balance and parenthood during the PhD, as well as trends in internationalization.

The contribution summarizes the current state of research in these areas while also outlining open questions and directions for future research. It is therefore relevant not only for scholars in higher education research, but also for doctoral candidates, higher education practitioners, and stakeholders in science and higher education policy.

The NomosHandbuch Hochschulforschung is edited by Peer Pasternack, Gabi Reinmann, and Christian Schneijderberg and brings together 60 contributions by 81 authors. Rather than a traditional edited volume, the handbook offers concise and structured overviews of research on topics such as research, teaching, studying, knowledge transfer, and universities as organizations. It is available both in print and as a fully open-access publication, funded by FIS Bildung.

The chapter reflects Susanne de Vogel’s long-standing expertise on qualification and employment conditions in academia and situates this perspective within a key reference work in higher education research, while also strengthening the DSC’s visibility in higher education and science policy debates.

Additional Links:

NomosHandbuch (Open Access): doi.org/10.5771/9783748943334

If you have any questions, please contact:

Dr. Susanne de Vogel
DSC Data Scientist for Social Sciences
Tel. +49 (421) 218 63938
E-mail: devogel@uni-bremen.de

AI in Qualitative Research: DSC Contributes Expertise to the AIQM Network

Thu, 27 Nov 2025 15:14:00 +0100

The interdisciplinary network AI meets Qualitative Methods (AIQM) was founded in summer 2025 by researchers from the University of Bremen and the Institut für Informationsmanagement Bremen GmbH (ifib). It brings together doctoral researchers and postdocs who are engaging with the use of AI in qualitative research. In regular meetings, participants discuss methodological, technical, and ethical questions, test new tools, and critically reflect on the meaningful use of AI across different stages of the research and writing process.

Since October, the Data Science Center (DSC) has been represented in the AIQM network by Nele Fuchs, contributing discipline speficif expertise as part of the BMFTR-funded data competence center DataNord. At the network meeting on 26 November, she provided an input on the ongoing and often controversial debate within the qualitative research community about the opportunities, limitations, and risks of using AI in research.

The network aims to jointly build competencies for the responsible use of AI, to learn from one another, and to develop a well-founded knowledge base. Insights from the network are intended to be shared with a wider research community – both within and beyond the University of Bremen – through open formats such as workshops, reading groups, and publications.

How the DSC contributes

The use of AI in qualitative research raises fundamental questions, including issues of methodological transparency, data protection, bias, scientific traceability, and resource consumption. At the same time, many researchers lack the technical and data-related expertise needed to use AI-based tools in a confident and reflective way.
This is where the DSC contributes a valuable, cross-cutting data science perspective to the AIQM network through the DataNord project. In her role as Data Scientist for the Digital Humanities, Nele Fuchs draws on extensive experience from research consultations, training formats, and collaboration with a wide range of research projects. At the same time, the DSC benefits directly from the exchange within the network: questions and challenges emerging from research practice feed straight back into the further development of advisory and qualification offerings. This creates a close feedback loop between qualitative research practice and data science support.

This role was also reflected in the Data Snack “Beyond ChatGPT: AI Systems for Qualitative Research” hosted by the DSC on 4 December 2025. In this session, Nele presented and critically discussed concrete AI-supported tools for qualitative research. The event also introduced the AIQM network to a broader research audience and helped to further strengthen connections across disciplines.

The AIQM network is open to anyone interested in qualitative research and AI. New members are very welcome and can express their interest in joining via this form (contact person: Veronika Graceva).

Additional Links:

ifib blog article on the network

If you have any questions, please contact:

Nele Fuchs
Data Scientist for Digital Humanities
Tel. +49 (421) 218 - 59853
E-mail: n.fuchs@uni-bremen.de

Data Skills for Space Science: DSC Supports Summer School

Mon, 22 Sep 2025 13:13:00 +0200

From 15 to 19 September 2025, the PIP Summer School took place at the University of Bremen, organized by colleagues from Faculty 01 – Physics / Electrical Engineering. A total of 27 students from the fields of physics, electrical engineering, and space engineering – coming from various universities – participated in the five-day program. The goal of the Summer School was to inspire students to engage with space science, deepen their subject knowledge, and explore potential career paths in the space industry.

The program combined expert lectures, practical exercises, and opportunities for exchange, covering topics ranging from space exploration and aerospace engineering to interdisciplinary applications in space science.

FAIR Data You Can Touch: DSC Workshop

The Data Science Center (DSC) was represented by Sarah Büker and Annika Nolte as part of the DataNord project team. They led a four-hour interactive workshop entitled “Cosmic Bricks: Making Space Science Data FAIR with LEGO®”.

Through playful, hands-on activities, participants learned what the FAIR principles – Findable, Accessible, Interoperable, and Reusable – mean in practice and why sustainable research data management is particularly important in space science and the natural sciences. International collaborations, long-term missions, and large volumes of observational and simulation data make FAIR data a key foundation for transparent, reproducible, and reusable research.

Using LEGO® models, such as rockets or lunar rovers, abstract concepts like documentation, metadata, and reusability became tangible and easy to grasp. No prior knowledge of research data management was required; the workshop was explicitly designed for students at an early stage of their academic careers.

Strengthening Data Skills Early On

With this workshop, the DSC demonstrated how data skills can be integrated into educational formats at an early stage in a low-threshold and target-group-oriented way. For students in these disciplines, a basic understanding of research data management is an important component for future academic and industrial careers.

By contributing to the PIP Summer School, the DSC highlights its commitment to embedding data skills at an early stage of academic education. Workshops like this demonstrate the value of the interdisciplinary data competence team within the BMFTR-funded DataNord project: drawing on established concepts, broad experience, and interdisciplinary backgrounds, innovative training formats can be implemented quickly, tailored to specific audiences, and reused sustainably. In this way, the DSC plays a key role in equipping the University of Bremen’s research and teaching environment with essential data skills.

Interested in a workshop like this? Feel free to contact us. An overview of our workshop portfolio can be found here.

Additional Links:

DataNord
PIP Summer School

If you have any questions, please contact:

Dr. Lena Steinmann
Coordinator Data Science Center & “DataNord”
Tel. +49 (421) 218 - 63941
E-mail: lena.steinmann@uni-bremen.de

DSC Supports Conference Trip to India

Svenja Goers — Mon, 16 Dec 2024 08:30:00 +0100

During the trip, Dr. Chandan Kumar Jha is going to attend the 33rd IEEE Asian Test Symposium as well as the 38th International Conference on VLSI Design (Very Large-Scale Integration Design). At the conferences, he will present new findings in the field of in-memory computing, approximate circuits, and large language models (LLMs) for verification. In addition, he will deliver a tutorial on employing LLMs for Hardware Verification in VLSI Design.

By sharing recent findings with research groups at the leading Indian research institutes, IIT Gandhinagar, IIT Bombay, and IIIT Bangalore, the trip aims to facilitate knowledge exchange at the intersection of in-memory computing and approximate circuits. The talks and follow-up discussions will also provide opportunities to network, discuss future collaborations, and exchange ideas with researchers from both academia and industry. By identifying complementary areas of research, the trip also serves to seed long-term international partnerships and lay the basis for potential joint projects and publications.

Funding recipient:

Dr. Chandan Kumar Jha (Faculty 3 – Mathematics & Computer Science)

Funding period:

14.12.2024-09.01.2025

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DSC Supports the Implementation of the ICYMARE 2025

Svenja Goers — Mon, 08 Sep 2025 08:30:00 +0200

This time, the awarding of the DSC Seed Grant supported the implementation of ICYMARE 2025, which is going to take place from September 8 to 12 at Bremerhaven University of Applied Sciences. ICYMARE (short for “International Conference for Young MArine REsearchers”) is an annual conference aimed specifically at early-career marine scientists. The event of the Bremen Society for Natural Sciences (NWV) is organized voluntarily from the bottom up by young marine researchers themselves.

The conference offers young scientists the opportunity to learn about new research findings and engage in discussions on current developments in marine sciences. In addition, students and doctoral candidates can use the multi-day event to gain their first conference experiences and build an international network. In 2024, for instance, ICYMARE brought together participants from over 30 countries worldwide.

The conference program includes different formats covering current findings and projects from all areas of marine research, ranging from marine ecology, biodiversity, and oceanography to climate protection, sustainable marine use, and governance. This year, the DSC Seed Grant supports the implementation of several workshops and a poster session, providing participants with the opportunity to gain experience in managing and presenting research data.

Funding recipient:

Dr. Simon Jungblut (Bremen Society for Natural Sciences & Marine Zoology, University of Bremen)

Funding period:

08.09.2025-11.09.2025

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DSC Supports the Organisation of the First “DiscussDataLab” Workshop

Svenja Goers — Mon, 25 Aug 2025 08:30:00 +0200

The DiscussDataLab is a three-day interdisciplinary workshop that is going to take place from August 25 to 27 at the Research Center for East European Studies at the University of Bremen. The event is organized by the research data repository Discuss Data. The interactive open-access platform, with a regional focus on the post-Soviet region, enables researchers worldwide to publicly share, archive, and cite their data. By exchanging feedback and assigning DOIs to all published data sets, the platform contributes to improving data quality.

The first DiscussDataLab will be centred around the topic “Challenges of Data Collection, Re-use, and Analysis: Public Opinion, Political Debates, and Protests in the Context of the Russo-Ukrainian War.” The event is aimed at social scientists from Eastern Europe, the Caucasus, and Central Asia, as well as early-career scientists conducting research on these regions.

The DiscussDataLab aims to teach participants (doctoral candidates, postdocs, and master's students in the final phase of their studies) the theoretical and practical basics of RDM. The theoretical part of the workshop will be taught by renowned scientists who research the mentioned regions and will provide insights into their data science methods and data sets. Under the guidance of the Discuss Data team and several curators, participants will then learn to prepare their own research data in practical workshop sessions.

The goal is to enable participants to publish their datasets on the Discuss Data platform or other repositories in accordance with the FAIR principles. By teaching data management skills to early-career researchers, the event aims to promote the sustainable adoption of good scientific practice in handling research data.

Funding recipient:

Dr. Eduard Klein (Research Center for East European Studies at the University of Bremen)

Funding period:

25.08.2025-27.08.2025

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Between FAIR Data and Inclusion: DSC Brings Key Perspectives to 39C3

Mon, 05 Jan 2026 16:04:00 +0100

The 39th Chaos Communication Congress (39C3) took place in Hamburg from 27 to 30 December 2025. As one of the world’s largest community-driven events on technology, digital culture, and the societal implications of digitalization, the congress brings together participants from a wide range of technical, scientific, and civic backgrounds. The DSC was once again part of this diverse exchange.

This year, the focus was on how research data management can be made more inclusive – particularly with regard to neurodivergent researchers. Their needs are often insufficiently reflected in existing strategies and guidelines, even though they make up a significant share of the research landscape.

Workshop: “Inclusion and Research Data Management”

On 28 December, Sarah Büker, a data scientist in the BMFTR-funded DataNord project, led an 80-minute interactive workshop combining a short introductory talk with several discussion rounds. The workshop started from the observation that while RDM is increasingly structured around concepts such as FAIR data, data management plans, and ELSA considerations, there is still little reflection on whom these strategies actually work for in practice.

Together with participants from different disciplines and career stages, the workshop explored questions such as:

Are current RDM strategies designed to be inclusive?
Where do institutional requirements create additional barriers?
What do researchers need in order to implement data management in a realistic way?

The discussions made clear that many challenges in dealing with research data are structural rather than individual. A central outcome of the workshop was the shared call for more openness in talking about difficulties, uncertainties, and mistakes—creating space for mutual learning and more sustainable solutions.

Building on “How to Thrive in Chaos”

In addition, Sarah Büker continued the conversation with a talk titled “How to Thrive in Chaos, Part II”, building on the highly successful discussion round from the previous year, which had attracted more than 250 participants. Once again, the focus was on the everyday working realities of neurodivergent researchers, offering space to exchange strategies, pressures, and strengths beyond conventional performance narratives.

Why this matters

The contributions at 39C3 highlight that research data management is not merely a technical or organizational concern, but also a social and cultural one. Especially in open, interdisciplinary settings like the Chaos Communication Congress, it becomes clear how closely data practices, digitalization, and inclusion are intertwined.

For the DSC, participating in 39C3 is therefore an important part of its knowledge transfer activities. The discussions provide valuable input for the ongoing development of inclusive advisory and training formats within the BMFTR-funded DataNord project. At the same time, the DSC helps raise awareness of inclusive data practices in research-adjacent, technical, and civil society contexts—well beyond traditional academic settings.

Additional links:

39. Chaos Communication Congress (39C3)
DataNord

If you have any questions, please contact:

Sarah Büker
Data Science Support | Umwelt- und Meereswissenschaften
Tel. +49 (421) 218 - 59855
E-Mail: sbueker@uni-bremen.de

Audio transcription and formula recognition: DSC Supports Didactics of Mathematics with an AI-Based Workshop

Tue, 20 Jan 2026 15:33:00 +0100

Annika Nolte and Nele Fuchs delivered a practice-oriented workshop for the research seminar of the Didactics of Mathematics group at Faculty 03 within the framework of the DataNord project. Held on January 13, the session focused on automated transcription of audio data and its application in qualitative research contexts.

The 90-minute workshop introduced concrete tools for automatically transcribing spoken content. In particular, it showcased the open-weight model Whisperand the open-source software NoScribe, which builds on Whisper while offering a user-friendly interface for transcription workflows.

A specific challenge: transcribing mathematical formulas

One focus addressed a challenge that frequently arises in mathematics education research: the transcription of mathematical formulas. Spoken mathematical expressions are typically rendered as plain text by conventional transcription systems, which can be limiting for further analysis.

To address this issue, Annika Nolte and Nele Fuchs presented an extended workflow in which an additional, specialized language model is applied after the initial transcription. This model translates detected formulas into proper mathematical notation, ensuring that formulas are represented using symbols rather than spelled-out words. As a result, mathematical content can be documented in a more structured and analytically usable way.

Strengthening data skills in subject-specific research

The workshop illustrated how data-related tools can be adapted to disciplinary needs and integrated into existing research processes. In qualitative studies based on audio recordings – such as interviews, classroom observations, or reflective discussions – automated transcription can significantly reduce time demands while improving transparency and traceability.

For the DSC, collaboration with subject-specific research groups like the Didactics of Mathematics team is an important part of providing data-related support across disciplines. Formats such as this workshop ensure that data skills are conveyed not in the abstract, but directly within the concrete contexts of everyday research practice.

Interested in a workshop for your research group or institute?

If you have questions about data, research data management, or data science – or if you would like to explore a similar format for your research group or institute – please contact our coordinator Dr. Lena Steinmann. For further inspiration, feel free to take a look at our existing training portfolio.

If you have any questions, please contact:

Nele Fuchs
DSC Data Scientist
Tel. +49 (421) 218 59853
E-Mail: n.fuchs@uni-bremen.de

Annika Nolte
DSC Data Scientist
Tel. +49 (421) 218 59856
E-Mail:anolte@uni-bremen.de

Are you our next data champion?

Mon, 02 Feb 2026 16:31:00 +0100

All further information and the application requirements for the Data Champion Award 2026 can be found on the website of our Bremen-based data competence center DataNord.

DSC Supports Linguistic Landscape Study at Japanese Universities

Svenja Goers — Mon, 23 Feb 2026 08:00:00 +0100

Linguistic Landscapes (LL) are an area of study concerned with the visible use of language in public spaces (e.g., signage, public notices, billboards). It originates from the field of sociolinguistics and language policy. The frameworks of LLs can be used, for instance, to study how different languages are displayed and hierarchized in multilingual societies.

The funded study aims to quantify multilingualism at two Japanese universities – public Kyoto University and private Doshisha University. The data-driven project represents a re-emerging application of LL concepts in the study of minoritized languages in East Asia, with Japan as a predominantly monolingual society. The study intends to capture the subtle presence of minoritized languages at two public institutions to uncover the mechanisms of minoritization and de facto language policies (unofficial, everyday practices of language use).

During his stay in Japan, Leon Grausam will collaborate with two local researchers to collect and process the data at the universities’ premises. The data will be collected with the help of the open source “Lingscape” tool that allows to capture displays of written language in public spaces through photography. The team will document all kinds of language fragments, including official signage as well as unofficial, disruptive signs (e.g., stickers or flyers).

The overarching goal is to gain a comprehensive understanding of language communities in university spaces and examine how different university stakeholders use language to shape the LL. The research team also plans to publish the data after the project is completed, making it accessible and freely usable for everyone.

The study is also designed to serve as a pilot project for a larger-scale study of various public institutions across Japan. The Seed Grant is intended to kick-start an application for external funding by the Japan Society for the Promotion of Science (JSPS) for said large-scale project all over Japan. In addition, a project with a similar methodology is planned for German universities, starting with the University of Bremen.

Funding recipient:

Leon Grausam, M.A. (Faculty 10 – Linguistics and Literary Studies)

Funding period:

02 March 2026 – 28 April 2026

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Working Responsibly with Research Data? DSC Workshop for Doctoral Researchers

Fri, 21 Nov 2025 11:30:00 +0100

On November 20, 2025, the Data Science Center (DSC), in cooperation with the Research Data Center QualiService, hosted the full-day workshop How to Handle Your (Digital) Research Data Responsibly” for doctoral researchers from the DFG REsearch Training Group 2686 Contradiction Studies and the Bremen International Graduate School of Social Science (BIGSSS). The workshop was delivered within the framework of the BMFTR-funded data competence center DataNord.

The aim of the event was to familiarize participants with core concepts, requirements, and good practices in research data management (RDM) – from structured data organization to questions of reuse. Central to the session was the practical meaning of responsible data handling and how thoughtful RDM can make research projects more transparent and efficient.

From RDM basics to AI-supported workflows

Nele Fuchs, Data Scientist in the DataNord project, designed and delivered the workshop together with Michaela Rizzolli from QualiService. Alongside an introduction to fundamental RDM principles, Nele led the second main focus area on data security, data storage, and RDM in the context of AI systems. The program was complemented by insights into the use of AI in research, the specific challenges of working with qualitative data, and options for archiving and reusing research data.

The workshop combined theoretical foundations with concrete use cases and offered space for discussion around participants’ individual questions and doctoral projects.

Data literacy as a cornerstone of good scientific practice

For doctoral researchers increasingly working with digital, qualitative, or AI-supported methods, a solid understanding of data practices is a key component of good scientific practice. The workshop highlighted the importance of teaching RDM not as an abstract concept, but in direct connection with real research scenarios.

Through formats like this, the DSC brings data science expertise directly into doctoral training. At the same time, the needs and challenges discussed feed straight back into the ongoing development of the DSC’s and DataNord’s advisory and training programs – creating an important feedback loop between research practice and data-related support.

Interested in a workshop for your doctoral researchers?

If you have questions about data, research data management, or data science – or if you would like to offer a similar format for doctoral researchers in your graduate school or department – please feel free to contact our coordinator, Dr. Lena Steinmann. For further inspiration, take a look at our existing training portfolio.

Additional links:

DataNord

If you have any questions, please contact:

Nele Fuchs
DSC Data Scientist | Humanities
Tel. +49 (421) 218 59853
E-mail: n.fuchs@uni-bremen.de

From Audio to Text: DSC Brings AI-Supported Transcription to the Digital Humanities

Wed, 25 Feb 2026 12:13:00 +0100

On February 24, 2026, Nele Fuchs and Annika Nolte from the Data Science Center (DSC) will lead a full-day workshop at DHd2026: Not only text, not only data in Vienna. The annual conference brings together researchers from across the Digital Humanities to explore how diverse data types, methods, and algorithmic approaches can be sustainably integrated into humanities research.

Within this context, the two DataNord team members will offer the workshop “From Audio to Text: Automated Transcription with Whisper.” It is aimed at researchers and multipliers who want to integrate qualitative audio data more efficiently into their research workflows.

Automated transcription as an entry point to data-intensive Digital Humanities research

Interviews play a central role in many areas of the Digital Humanities, including oral history, linguistics, and ethnography. At the same time, manual transcription is extremely time-consuming. In the workshop, participants learn how this process can be significantly streamlined using Whisper, an open-weight automatic speech recognition model.

Whisper generates initial transcript drafts that can then be reviewed and refined manually. A key focus of the workshop is the responsible use of AI tools in research – covering topics such as data protection, hardware requirements (CPU vs. GPU), and the limitations of automated transcription quality.

In a hands-on session, participants work with Whisper using provided audio files or their own material. Together, they reflect on how automatic transcription affects source data – especially when large datasets cannot be fully checked manually – and discuss the implications for subsequent (semi-)automated analyses.

Open teaching materials for sustainable data skills

The workshop’s teaching concept and accompanying Jupyter notebooks are available as Open Educational Resources (OER) on Zenodo and can be reused by multipliers in their own teaching and training formats. These materials were developed as part of the BMFTR-funded DataNord project.

In this way, the DSC strengthens data skills in the humanities through hands-on work with real research practices – from data preparation and AI-supported workflows to questions of reproducibility.

DataNord and the DSC: building data skills for the humanities

The workshop reflects the broader approach of DataNord and the DSC: teaching data skills in a discipline-specific and interdisciplinary way. Especially in the Digital Humanities, where text, audio, images, and computational methods increasingly intersect, accessible entry points to data science, research data management, and AI are essential.

Through formats like this, the DSC brings data science expertise directly into humanities research – while also creating space for exchange around the methodological, technical, and ethical dimensions of data-intensive scholarship.

Additional links:

Book of Abstract (With DSC article: Fuchs, N., Nolte, A., Steinmann, L., Drechsler, R., 2026. Vom Audio zum Text: Automatisierte Transkriptionen mit Whisper. pp. 79-81)
https://zenodo.org/records/18693970 (OER Resource From Audio to Text: Automated Transcriptions with Whisper – An Open Educational Resource)
DataNord

If you have any questions, please contact:

Nele Fuchs
DSC Data Scientist | Humanities
Tel. +49 (421) 218 59853
E-Mail: n.fuchs@uni-bremen.de

Annika Nolte
DSC Data Scientist | Environmental and Marine Sciences
Tel. +49 (421) 218 59856
E-Mail:anolte@uni-bremen.de

Contribution of the DSC to the YUFE Open Science Program

Fri, 17 Jan 2025 12:00:00 +0100

On January 15, 2025, the Data Science Center (DSC) participated in the design of the third workshop day (“Open Data”) in the YUFE Open Science Program. The multi-part online program brings together research support staff such as library staff, data stewards, and research funding advisors at YUFE partner universities. The joint exchange focused on reflecting on open science practices in different institutional contexts and learning from each other. The third workshop day on January 15 focused on open data and the practical implementation of the FAIR principles. Dr. Susanne de Vogel, data scientist for training and consulting at the DSC and also a participant in the YUFE program, supported the workshop day with two contributions.

Using the BMFTR-funded “DataNord” project as an example, she showed how an interdisciplinary data competence center for the Bremen region supports researchers in implementing the FAIR principles and open data practices – and which building blocks at the DSC interact in this process: training opportunities, individual consultations, and networking formats that promote exchange between disciplines and roles.

Collaborative learning with the COLLAB Game

In the second part, Susanne led an interactive workshop on FAIR principles and open data, using the COLLAB Game developed at Kiel University. This innovative method is designed to highlight different professional backgrounds, roles, and working logics in interdisciplinary teams and to improve communication and collaboration.

For use in the YUFE program, the content of the Collab Game was adapted to open data and open science practices. The aim was to use the game as a way to start a conversation about different support and advisory practices at the partner universities: Which support services work well? What typical challenges do researchers face in terms of resources, role clarification, data publication, or legal frameworks? And which solutions have proven themselves in practice at the partner universities?

The participants worked in small groups on digital boards and used reflection, discussion, and action cards to discuss key issues relating to data organization, documentation, reusability, role allocation, and practical hurdles in supporting researchers in the field of FAIR and open data.

The playful format quickly revealed different perspectives and helped to openly discuss typical areas of tension – such as between the desire for openness and requirements for data protection, resources, or institutional framework conditions. At the same time, space was created for the exchange of concrete experiences from the respective institutions and for the question of which support services are lacking at their own universities, which work well, or which should be further developed.

Insights for open data in practice

The workshop day showed how interactive, low-threshold formats can help not only to explain complex topics such as open data and FAIR principles, but also to discuss them together and translate them into practical options for action. For the DSC, co-designing the workshop was a valuable opportunity to bring experiences from DataNord into a European context and to take inspiration from the YUFE network for its own consulting and training practice

Additional links:

YUFE
COLLAB GAME
www.datanord-bremen.de

If you have any questions, please contact:

Dr. Susanne de Vogel
DSC Data Scientist
+49 (421) 218 - 63938
devogel@uni-bremen.de

Engaging in Dialogue with the RatSWD

Translated using AI — Mon, 02 Mar 2026 16:17:00 +0100

As part of the founding team of the Data & Digital Science Community (DaDiSC, https://dadisc.org), the Data Science Center (DSC) presented the initiative on February 27 at the 75th meeting of the German Data Forum (RatSWD). DSC Coordinator Dr. Lena Steinmann introduced the goals, structure, and future perspectives of the nationwide community alongside Prof. Dr. Dirk Nowotka and Dr. Martin Semmann.

The RatSWD advises the German federal government and the governments of the Länder on the development and improvement of research data infrastructure for the empirical social, behavioral, and economic sciences. It is part of the “KonsortSWD” consortium within the National Research Data Infrastructure (NFDI).

Strengthening Structures for Data-Intensive Research

DaDiSC emerged from a bottom-up process and connects Data and Digital Science centers as well as related initiatives. Its aim is to pool methodological expertise, practical experience, and competence development across institutions, foster exchange, and enable collaboration.

Data-intensive research and AI-supported methods are evolving rapidly. At the same time, many institutions still lack sustainable structures, reliable career paths, and permanently established competence frameworks. Expertise is lost, projects begin in isolation, and innovation potential remains untapped.

Data and Digital Science institutions provide continuity in this landscape: they connect infrastructure, methodological development, application, and skills development – helping to secure the long-term foundation of data-driven research.

During the exchange with the RatSWD, the initiative was presented and discussed particularly in the context of the social and economic sciences.

The DSC’s Contribution

Through its involvement in DaDiSC, the DSC brings the perspective of structurally embedded Data and Digital Science centers into the national dialogue. The goal is to systematically integrate data science methods into disciplinary research and to establish sustainable competence structures.

The recently published position paper of the community – which has already been featured in a separate article on our website – provides an important foundation for this dialogue and outlines key strategic needs for research, teaching, and infrastructure.

We would like to thank the RatSWD for the constructive exchange and for the opportunity to contribute the perspective of the Data & Digital Science community to this strategic discussion.

Additional Links:

Website Data & Digital Science Community (DaDiSC): https://dadisc.org
Position Paper of Community (Zenodo): https://zenodo.org/records/17475528

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-mail: lena.steinmann@uni-bremen.de

DSC Supports the Scaling of a Digital Workflow for Extracting Early Modern Mobility Data

Svenja Goers — Tue, 17 Mar 2026 08:00:00 +0100

Lists of visitors are regularly maintained records used to document the temporary presence of non-resident individuals as well as the mobility of local inhabitants. In the present case, the project focuses on the weekly lists of visitors published between 1762 and 1802 in the newspaper Regensburgisches Diarium of the Imperial City of Regensburg. These records were compiled by gate clerks at the city gates on behalf of the municipal authorities in order to monitor and document movements into and through the city. They include information such as names, social status, places of origin, travel groups, and modes of transportation. Today, lists of visitors serve as important sources in mobility history research. They can be analyzed, for example, to reconstruct movement patterns, migration trends, and social networks.

This time, the DSC Seed Grant supports the further development of an AI-based workflow for extracting mobility data from visitor lists originating from the early modern period. The lists published in the announcement paper Regensburgisches Diarium comprise approximately 500.000 recorded mobility events. In terms of scope, richness, and diversity, the sources represent an exceptional data basis for the German-speaking region.

Unlike many early modern visitor lists from other cities, which include only high-ranking travelers, the Regensburger records cover the full spectrum of the mobile population of the period. The systematic extraction of information from the sources, therefore, allows unique insights into the movement patterns of marginalized people and mobile individuals who have previously been conceptualized as immobile. These include, for example, traveling women of various social classes, such as Jewish women, merchant women, and (Black) servants.

In the field of historical sciences, the AI-supported analysis of large-scale, historical text sources is still in its early stages. Hence, the funded project also contributes to the establishment of a reproducible data science method that can be applied to other source collections in the historical and cultural sciences. Thus, the project also supports the strengthening of data-based research in the humanities. In addition, the collected research data will also be published to make it freely accessible and reusable in accordance with the FAIR principles.

Funding recipient:

Dr. Sarah Lentz (Faculty 08 – Social Sciences)

Funding period:

01 April 2026 – 31 September 2026

Are you interested in the DSC Seed Grant?

You can find more information about the DSC Seed Grant here.

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

DaDiSC-Workshop in Bielefeld: The Data and Digital Science Community Comes Together

Thu, 26 Mar 2026 13:50:34 +0100

The Data & Digital Science Community (DaDiSC) recently hosted a two-day Workshop in Bielefeld (March 18–19, 2026), bringing together representatives from nine institutions for an intensive exchange. The aim of the meeting was to further develop key topics from the 2025 position paper and to define specific areas of focus for 2026.

Building on the successful publication of the first position paper and the groundwork laid last year for the association’s founding, this meeting focused specifically on two key areas: data and AI literacy, and the digitization of research.

Taking Data & AI Literacy to the Next Level

At the forefront of the agenda was the presentation of a planned international data and AI literacy standard (DAILi Standard, IEEE publication forthcoming), which is being developed by Prof. Dr. Christian Bockermann (AKIS, Bochum), Dr. Katharina Weiß (BiCDaS, Bielefeld), and Dr. Henrike Weinert (DoDaS, Dortmund). The goal is to consolidate existing frameworks and create a common foundation for competency development.

Discussions revealed that the community is highly interested in applying these findings to specific training and professional development opportunities in the future – for example, through joint programs and formats.

DSC provides perspective on the digitization of research

The DSC played an active role in shaping the session on the digitization of research: DSC Coordinator Dr. Lena Steinmann co-chaired the session alongside Dr. Canan Hastik (IGSD e.V., SODa) and Dr. Martin Semmann (HCDS, Hamburg).

The focus was placed on:

strategic perspectives for the further development of the community
possible funding formats and joint grant proposals
the role of data and digital science structures in future research processes

In doing so, the DSC specifically contributed its experience in building and advancing data-related structures to the discussion.

Another central part of the session involved specific use cases from the participating institutions. In small groups, participants reflected on and presented different working methods, challenges, and the impacts of data-driven infrastructures.

This round of presentations progressed into an intensive exchange regarding the different disciplinary cultures within the community. It became clear that research and teaching are currently undergoing significant changes and that a closer convergence between disciplines is necessary to fully exploit the potential of data-intensive research.

Outlook: Joint Priorities for 2026

The workshop once again demonstrated how important ongoing dialogue within the community is for structurally strengthening data-intensive research and further developing shared perspectives.

This momentum carries forward into the fall, as the community comes together again for a DaDiSC workshop at the Informatik Festival 2026. Here, we will continue our work and welcome new voices. Interested parties are invited to contribute their own ideas and perspectives. Further information, deadlines, and the call for participation can be found on the website: https://dadisc.org/informatikfestival2026.

We would like to thank Dr. Katharina Weiß and the team in Bielefeld for organizing the event, and look forward to the next meeting in Kiel in the coming year.

Additional Links:

Data & Digital Science Community (DaDiSC) Website: Dadisc.org (Available in German only)

DaDiSC Position Paper (Zenodo): https://zenodo.org/records/17475528 (Available in German only)

For questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

Thinking Ahead Together: Data Competence Centers and Infrastructures Gather in Dresden

Thu, 09 Apr 2026 11:58:42 +0200

On March 30 and 31, 2026, a workshop on data literacy and digital research infrastructures was held at the SLUB in Dresden. The event was organized by Come2Data, one of the Data Competence Centers (DKZ) under the BMFTR funding program “for the establishment of data competence centers in science” for the research hub of Saxony.

The event brought together representatives from the eleven Data Competence Centers (DKZ) of the BMFTR funding lines, the National Research Data Infrastructures (NFDI), and the FDM state initiatives. After around two years of establishing the DKZs and nearly six years of developing the NFDI and state initiatives, the meeting provided an important opportunity to exchange experiences: Which support formats for researchers have proven effective? Where do challenges arise? What can we learn from one another?

The goal was to reflect on existing approaches and develop perspectives for the further development of data literacy and research infrastructures.
Data scientist Susanne de Vogel from the Data Science Center at the University of Bremen represented the DataNord team.

The focus was on discussing how researchers can be best supported in handling data—from data collection and management to analysis and reuse. It became clear that technical solutions alone are not enough; there is also a need for bridging work between different disciplines, methods, and requirements.

Susanne particularly contributed the perspective of research support units: entities such as data stewards and data scientists play a crucial bridging role between NFDIs and researchers, as well as between academic disciplines and data-driven methods. They help establish standards, build data literacy skills, and support researchers, for example, in implementing Open Science and FAIR practices.

On the second day of the workshop, the focus was particularly on the question of how to jointly create sustainable structures to ensure the continuity of these offerings and in which areas effective and meaningful collaboration is both possible and necessary.

A key outcome of the workshop is the shared intention to draft a Memorandum of Understanding (MoU) among all data competence centers. The workshop results are being documented and are intended to be made publicly available in the future.

Additional Links

Workshop: https://www.slub-dresden.de/en/visit/trainings-and-events/details/event/56609 (Available in German only)

BMFTR Funding Program Overview: www.bildung-forschung.digital (Available in German only)

Come2Data: come2data.de

If you have any questions, please contact:

Dr. Lena Steinmann
DSC Coordinator
Tel. +49 (421) 218 - 63941
E-Mail: lena.steinmann@uni-bremen.de

The Interdisciplinary Institute at the University of Bremen Bremen for Data-Driven Research

Fri, 06 Mar 2026 10:18:20 +0100

The Data Science Center (DSC) coordinates and advances the University of Bremen’s data-related expertise and activities. It promotes interdisciplinary collaboration, strengthens researchers’ data literacy, and supports sustainable, data-based research across allscientific fields. The DSC also serves as a central point of contact, providing services in data management and data science. In addition, the DSC collaborates on data-based research projects, bringing its data expertise to research teams as a project partner.

About Us

Fri, 06 Mar 2026 10:18:20 +0100

Learn more about the vision and mission of the DSC.

Our Team

Fri, 06 Mar 2026 10:18:20 +0100

Meet the team behind the DSC.

Our Members

Fri, 06 Mar 2026 10:18:20 +0100

Get to know the DSC members.

University of Bremen - Data Science Center

The DSC Supports The Development of an Artificially Intelligent Fence For Automated Wolve Detection

Funding recipient:

Funding period:

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

Further Links

The DSC Supports a Data Science Project About a Novel Recruitment Method in Social Scientific Survey Research

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If you have any questions regarding the DSC Seed Grant, feel free to contact me.

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A New Way Towards Performance Prediction of ML Accelerators

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Participate in The First Bremen-Cardiff Data Science Workshop!

The DSC looks forward to meeting you at the event!

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We Are Looking For Student Support For Our IT!

The DSC Supports a Project That Aims to Extract Inequality-relevant Information From Online Job Advertisements

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Funding period:

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

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The DSC Supports The Further Development of The Local News Platform molo.news

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E-Science-Days 2023

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Let’s love our data! Oder: Love Data Week 2023

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Data Science Center And Mahidol University AI Center Lay Foundation For Future Collaboration

Data Stewardship Goes Germany

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On The Search For The Right ML-Accelerator

About the MLCAD Workshop:

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Meet The DSC at The Open Science Festival!

If you would like to find out more about the DSC and its data stewardship services, visit our Data Stewards at booth 17 at the Open Science Festival Marketplace.

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Sketchnote Event on the Topic Data Science

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International Data Power Conference 2022

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Welcome to The DSC, Heike!

We are happy to welcome Heike to our team at the DSC and look forward to working with her!

Contact:

Contribution to The SKILL 2022 Student Conference

Are you interested in writing a thesis with us?

Welcome to The DSC, Sandra!

We are happy to welcome Sandra to our team at the DSC and look forward to working with her!

Contact:

RDM-Special Edition in The Data Science Forum

All Events

Why an RDM Special Edition?

Where and When?

Please contact us if you have any questions:

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Welcome to The DSC, Julian!

We are happy to welcome Julian to our team at the DSC and look forward to working with him!

CRC 1342 is Looking For a Software Developer (f/m/d) in Close Cooperation With The DSC

Software Developer (f/m/d) for Research Software

Job Description

Your Tasks

Your Profile

General Hints

Kontakt

We Are Looking For Student Support in Our IT!

Kontakt

The DSC Funds a Data Science Project in The Social Sciences

Funding recipient:

Funding period:

If you have any questions regarding the DSC Seed Grant, feel free to contact me.

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