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Data Stories

Everyone is cordially invited to take part in our Data Stories!
Data Story

In exciting talks, we will listen to inspiring stories  about data handling, data management and data science applied in the private sector or in science. 

The speakers shed light on the importance of data competences with regard to their individual working fields and will discuss current challenges.

The talks are complemented by a joint discussion in which everyone has the chance to ask questions and state comments.

Whenever possible, the events end with an opportunity for networking and socializing with peers from other disciplines and the speakers over some seasonal snacks and drinks.

Please find our current program and further information for each event below.

 

Upcoming Data Stories

Data Story 4: Prof. Dr. Carsten Oliver Schmidt (Universitätsmedizin Greifwald)

Data Automation

How to make large scale phenotypic data internationally competitive within a population-based cohort study

After reunification, North-Eastern states had the lowest life expectancy in Germany. One hypothesis was the regional accumulation of health-related risk factors, but scientific evidence was lacking. This was a major reason for initiating the population-based Study of Health in Pomerania (SHIP) in Greifswald in the late 1990s in the adult general population. Initially planned as a cross-sectional study, it has now been running for 20 years. One of the world's most extensive clinical examination programs was implemented, which proved to be a considerable challenge due to the many data sources. Largely automated processes in a  centralized data management processes have been setup including dedicated software developments. This has laid the foundation for numerous national and international cooperations, enabling more than 1000 interdisciplinary publications. New findings relate, among other things, to the accumulation of cardiometabolic risk factors and diseases in the region. The latest extension of SHIP concerns the examination of humans and animals as part of a one-health approach.

20.09.2022, 16:00-17:00 CEST, Online via VC

Program

16:00 CESTWelcomeProf. Iris Pigeot (Data Train Speaker, Director of the Leibniz Institute for Prevention Research and Epidemiology – BIPS)
16:10 CESTData Story 4Prof. Dr. Carsten Oliver Schmidt ( Universitätsmedizin Berlin)
ca.16:40 CESTDiscussionModeration: Prof. Iris Pigeot

 

 

 

Previous Data Stories

Data Story 3: Sonja Sievi & Götz Anspach von Broecker (AIRBUS)

Systems

Data Centric Systems in the Public Sector and Industry

Systems that are supposed to manage and associate data volumes, process data streams and interconnect databases are known in their smallest version as APPs on computers and smartphones. Very large systems, for example disaster reaction and control centers and security and awareness centers, are called system-of-systems.

What they all have in common is that independent data sources and data users cooperate with each other via interfaces especially in future cooperation platforms for the development, production, manufacturing and operation of complex SYSTEMS such as ships, aircraft, energy grids and vehicle fleets and of course complex administrational task (e-government).

This sounds simple and actually feasible - Amazon, Meta and Google have been doing it for a long time - but in public sectors, healthcare and industrial applications there are many legal barriers due to data security/intellectual property/export control rules that make a simple setup extremely difficult, or even impossible.

Examples will be shown that reflect the current state of the art, highlight the challenges from a technical, regulatory and socio-political point of view, and give suggestions on how to overcome these challenges. The examples will range from applications in space via governmental security systems to future cooperation platforms (GAIA-X initiative of the EU) and virtual aircraft wharfs.

Data Story 2: Dr. Anatol Fiete Näher (Charité – Universitätsmedizin Berlin)

Covid-19 data
Covid-19 data

Lessons learned from Covid-19 surveillance: How to avoid data unFAIRness

Establishing reliable surveillance systems for disease outbreak detection and policy planning remains challenging. The recent Covid-19 epidemic serves as a prime example to summarize some of the key aspects regarding the governance of high-quality health data. A particular emphasis will be put on the implementation of a surveillance system that has been set up for screening and tracking of SARS-CoV2 variants.

Data Story 1: Moritz Stefaner (Truth & Beauty)

Multiplicity - A collective photographic city portrait
Multiplicity - A collective photographic city portrait Comissioned by Fondation EDF, Paris on occasion of the exhibition 123 data; Design and implementation: Moritz Stefaner

Beyond the bar chart: How new data languages can make complexity graspable

 

Moritz Stefaner is constantly chasing the perfect shape for information — how can we create expressive, intriguing, and elegant data experiences? He will walk us through his recent explorations pushing the boundaries of data visualization — from interactive experiences over data sculptures to even using food for representing data.