Zum Hauptinhalt springen

The Data Train Team

Collaborations

The Research Data Working Group of the U Bremen Research Alliance monitors the development of the training curriculum.

 

Data Train is in line with efforts of the National Research Data Infrastructure NFDI-consortia (funded by the DFG) which consider education as a cross-cutting topic. On the one hand, institutions from Bremen which are part of funded NFDI-consortia contribute to the Data Train progam. On the other hand, the Data Train concept and curriculum is shared with these consortia.

 

Data Train further operates in close collaboration with and is supported by theData Science Center(DSC) of the University of Bremenwhich defined "Qualification" as one of its three pillars (i.e. Qualification, Services, Research). The DSC brings together scientists from all faculties of the University of Bremen to initiate scientific cooperation and promote the development of novel research questions related to data science.

 

With BYRD (Bremen Early Career Researcher Development), the firmly established support center for early-career researchers at the University of Bremen, Data Train has an experienced collaboration partner with an excellent network at the University of Bremen. Both programs benefit from the clearly-defined foci and well-coordinated collaboration.

 

Data Train collaborations

Steering Committee

Coordination

Iris Pigeot

Prof. Dr. Iris Pigeot

Co-Chair U Bremen Research Alliance

Chair Research Data Working Group

Co-Speaker for NFDI4Health

More...

 

Frank Oliver Glöckner

Prof. Dr. Frank Oliver Glöckner

Chair Research Data Working Group

Speaker for NFDI4Biodiversity

More...

Rolf Drechsler

Prof. Dr. Rolf Drechsler

Spokesperson for the Data Science Center of the University of Bremen

More...

Tanja Hörner

Dr. Tanja Hörner

Coordinator Data Train

Coordinator Research Data Working Group and associated exchange groups

More...

 

Lecturer Team

A team of enthusiastic lecturers from different institutions within the U Bremen Research Alliance build up this joint curriculum!

Prof. Dr. Benedikt Buchner

Benedikt Buchner is Professor of Civil Lawand the director of the Institute for Information, Health and Medical Law (IGMR) at the University of Bremen.

Research focus on data protection and information law. Research depends on the free use of research data while the (exclusivity) interests of those whose personal data are to be processed for research purposes or those who own the copyright for study or similar data are opposed to this. It is the task of the law to resolve this conflict.

RDM is an important as well as difficult challenge, which can only be met if all the disciplines concerned closely cooperate.

  1. Starter Track: Data protection and licenses

Prof. Dr. Rolf Drechsler

Rolf Drechsler

Rolf Drechsler received the Diplom a and Dr. phil. nat. degrees in computer science from the Johann Wolfgang Goethe University in Frankfurt am Main, Germany, in 1992 and 1995, respectively. He worked at the Institute of Computer Science, Albert-Ludwigs University, Freiburg im Breisgau, Germany, from 1995 to 2000, and at the Corporate Technology Department, Siemens AG, Munich, Germany, from 2000 to 2001. Since October 2001, Rolf Drechsler is Full Professor and Head of the Group of Computer Architecture, Institute of Computer Science, at the University of Bremen, Germany. In 2011, he additionally became the Director of the Cyber-Physical Systems Group at the German Research Center for Artificial Intelligence (DFKI) in Bremen. His current research interests include the development and design of data structures and algorithms with a focus on circuit and system design. He is an IEEE Fellow.

From 2008 to 2013 he was the Vice Rector for Research and Young Academics at the University of Bremen. Since 2018 he is the Dean of the Faculty of Mathematics and Computer Science. He is one of the founders and currently the spokesperson of the Data Science Center at University of Bremen (DSC@UB).

  1. Starter Track: Computer science basics for data science

Prof. Dr. Frank Oliver Glöckner

Frank Oliver Glöckner is Professor for Earth System Data Science at the Department of Geosciences at the University of Bremen. He is head of Data at the Computing and Data Center of the Alfred Wegener Institute Bremerhaven and Adjunct Professor for Bioinformatics at the Jacobs University Bremen. He is head of the Data Publisher for Earth and Environmental Science PANGAEA at MARUM and speaker of the NFDI4BioDiversity consortium. His interdisciplinary team of geologists, biologists, engineers, and software developers located at the AWI and MARUM has a national and international proven track record in research data management, data logistics and data science.

In the U Bremen Research Alliance he is interested in a strong collaboration between all members to drive qualification in research data management and data science forward. He will contribute his network and experience to establish the city and state of Bremen as a center of excellence in these fields.

  1. Starter Track: Data and information management
  2. Data Steward Track: Tools for FAIR data handling

Dr. Dennis-Kenji Kipker

Dennis-Kenji Kipker is Research Manager at the Institute for Information, Health and Medical Law (IGMR) situated at the University of Bremen and board member of the  European Academy for Freedom of Information and Data Protection (EAID) located in Berlin.

Data security is one of the central requirements and at the same time challenges for the secure handling of research data. In this context, my research focuses on the legal requirements for secure data storage and management principles to be implemented accordingly. RDM is an important as well as difficult challenge, which can only be met if all the disciplines concerned closely cooperate.

My goal is to create a higher level of data security in research contexts.

  1. Starter Track: Data protection and licenses

Prof. Dr. Iris Pigeot

Professor Iris Pigeot has been the director of the today’s Leibniz Institute for Prevention Research and Epidemiology – BIPS since March 2004 and has been in charge of the Department of Biometry and Data Management of the institute since September 2001. Furthermore, she has been professor for Statistics with a Focus on Biometry and Methods in Epidemiology at the University of Bremen since 2001. Since 2019, Iris Pigeot has been chairwoman of the U Bremen Research Alliance together with Bernd Scholz-Reiter (president of the University of Bremen). She initiated the interdisciplinary graduate education program Data Train on “Research data management and data science” in 2019 to serve the upcoming needs in this area.

This education program is led by Iris Pigeot together with Frank Oliver Glöckner from theAlfred Wegener Institute, Helmholtz Centre for Polar and Marine Research As Co- Spokesperson of the consortium to set up a National Research Data Infrastructure for Personal Health Data (NFDI4Health), she links the graduate education program to this German - wide initiative and ensures the implementation of uniform standards for personal health data.

  1. Starter Track: Statistical thinking

Prof. Dr. Dr. Norman Sieroka

Norman Sieroka is Professor for Philosophy at the University of Bremen. He is a member of the Directory Board of the Turing Centre Zurich and of the Governance Board of ETH’s "Rethink" initiative (rethinking design with artificial intelligence). He studied philosophy, physics, and mathematics in Heidelberg and Cambridge. In fact, a special trait of his research group is that all members have backgrounds in more than one academic discipline. The group is interested in questions about "how science works" and w hat values are pursued in science. Here special attention is paid to the role played by data and by artificial intelligence within different disciplines (such as physics and pharmaceutical science) and different research contexts (such as theory development, hypothesis generation, and problem solving).

Being born and raised near Bremen, Norman Sieroka is happy to be on board with the U Bremen Research Alliance's program Data Train and to make the region a haven for deliberate data science.

  1. Starter Track: Philosophical reflections on data science

Björn Tings

Björn Tings accomplished his Bachelor studies in Scientific Programming and his simultaneous qualification in Mathematical-technical Software Development in 2010 at RWTH Aachen University. In 2013 he received his Master degree in Artificial Intelligence at Maastricht University.

Since 2013 he is employed as research associate in the team of Synthetic Aperture Radar (SAR) oceanography at the Remote Sensing Technology Institute of German Aerospace Center (DLR) in Bremen, Germany. He is responsible for integrating the team’s research and development work into operational prototype software for robust and fast processing of SAR data.

His research comprises the automatic detection and classification of ship signatures on SAR imagery. As PhD student at Helmut Schmidt University, Hamburg he also elaborates on the automatic recognition of ship’s wake signatures of moving vessels.

  1. Starter Track: Data science and big data
  2. Data Steward Track: Data preparation

Prof. Dr. Hans-Christian Waldmann

University of Bremen, FB11 :: Department of Psychology :: Theoretical Psychology & Psychometrics

(a) Advanced statistical norming procedures in psychological testing, SAS analysis macro/batch automatization, database design for health care studies, data documentation, pre-analytical data handling and its impact on results,

(b) philosophy of science (especially: the qualitative aspects of quantitative data, concepts of probability, paradigms in science and statistics)

25 years in the statistical consulting business have taught me this: prevention is better thanrehabilitation. Most projects that went astray did not so because of pitfalls in data analysis or lack of programming skills, but, aside from ill project management, for reasons of negligant data handling prior to statistical modeling, and, most important, drawing unwarranted conclusions from data. Meaning is not inherent to data, it is attached to it by researchers, and in order to“do it right” one must be aware of the patterns behind “doing it wrong”.

  1. Starter Track: About the meaningfulness of data