Data Science

The fast adoption of advanced technologies by research communities enables new ways for generating, processing, structuring, and collaborative use of data. This has not only significant impact on the amount of data produced, but also on the variety of data formats and the velocity of data generation and handling. Consequently, scientists and research organisations have to cope with organizational challenges to manage data effectively and efficiently to support excellent research. Furthermore the focus of information infrastructures shifts towards collaborations, which accelerate the development of decentralized, globally distributed data repositories and likewise distributed data analysis.

In essence, data has become a major research asset. Although this is well known to research institutions and communities, many struggle with meeting the growing requirements regarding methodologies, knowledge, and infrastructures. The implementation of data management policies is a prominent example. Many institutions specify such policies, but the execution remains challenging, and is, consequently, not well understood or implemented. This pertains, inter alia, to the realisation of data management plans, to the reliable long‐term archiving of data, or to the reproducibility of data. It is therefore essential for research organisations to address these challenges and define a concept that incorporates scientific requirements and strategic demands. This includes method development, infrastructure and skill training.

A collaboration in HeKKSaGOn could consider the following aspects:

  • Strategies for research data management at universities
  • Methods for data management and analytics
  • Research infrastructures for data management and analytics, e.g. in data‐intensive computing or storage services for large scientific data
  • Teaching and training on data science related topics
  • Security, data privacy, legal and ethical questions

Prof. Dr. Ramin Yahyapour
Chief Information Officer of University of Göttingen
Managing director of GWDG (a joint compute and IT competence center of the university and the Max Planck Society) External Link


Project abstract:

Data science, artificial Intelligence, and robotics are major forces to change our societies. For example, deep neural networks and machine learning have by now massively changed many application fields from science to industry. It is obvious that these methods will continue to strongly influence all of us and potentially pave our way to reach the UN social development goals.

Science has an obligation to shape this development by providing the necessary basic research, its application as well as by teaching and training young scholars of these fields. As artificial intelligence poses many questions in terms of privacy, ethics and social impact, we also need to critically engage in discussions about how to balance (perceived) dangers with (potential) benefits. HeKKSaGOn is a network of six research universities from Japan and Germany, which are committed to collaborate on these subjects. HeKKSaGOn has a track record in these topics through its working groups: Data Science, Robotics and Mathematics. While working on specific domain topics, we see the need to broaden our activities through a joint initiative. Thus, we propose the organization and implementation of two actions focused on the topic: “The Digital World: Data science, artificial Intelligence, and robotics” which are:

  • In 2021 International Summer School paired with an on-line conference and
  • In 2022 International Summer School paired with a life conference.
  • Webinar series which enhance collaboration opportunity and extend outreach.
Lead coordinator:

Name: Prof. Ramin Yahyapour
Position: Managing Director Gesellschaft für wissenschaftliche Datenverarbeitung Göttingen
Institution: Georg-August-Universität Göttingen
Department, Faculty: Computer Science Institute

Other coordinator:

Name: Prof. Shinji Shimojo
Position: Director
Institution: Osaka University
Department, Faculty: Cybermedia Center