NFDI for Data Science and Artificial Intelligence

Team: Peter Mutschke
Leader: Prof. Dr. Stefan Dietze, Prof. Dr. Claudia Wagner
Scientific unit: Knowledge Technologies for the Social Sciences (KTS)


The vision of NFDI4DataScience (NFDI4DS) is to support all steps of the complex and interdisciplinary research data lifecycle, including collecting/creating, processing, analysing, publishing, archiving and reusing resources in Data Science and Artificial Intelligence.

The past years have seen a paradigm shift, with computational methods increasingly relying on data-driven and often deep learning-based approaches, leading to the establishment and ubiquity of Data Science as a discipline driven by advances in the field of Computer Science but being of relevance to most scientific disciplines. Transparency, reproducibility and fairness have become crucial challenges for Data Science and Artificial Intelligence due to the complexity of contemporary Data Science methods, often relying on a combination of code, models and data used for training.

Taking into account the increasing importance of Data Science and Artificial Intelligence methods for Computer Science as well as a broad range of scientific disciplines, NFDI4DS will develop and promote FAIR and open research data infrastructures supporting all involved resources such as code, models, data, benchmarks or publications through an integrated, knowledge graph-based approach. The overarching objective of NFDI4DS is the development, establishment and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence community in Germany. This will also deliver benefits for a wider community requiring data analytics solutions, within the NFDI and beyond. The key idea is to work towards increasing the transparency, reproducibility and fairness of Data Science and Artificial Intelligence projects, by making all digital artefacts available, by interlinking them, and by offering innovative tools and services to enable reuse.

GESIS focuses on the development of a knowledge graph, that integrates AI and data science objects, and the application of the infrastructure to computational social science use cases.

Further information:



Sponsored by

DFG (im Rahmen der Bund-Länder-Vereinbarung zur NFDI)


  • Fraunhofer-Gesellschaft zur Förderung der angewandten
  • Forschung e.V. / Fraunhofer FOKUS (Applicant Institution)
  • Deutsches Forschungszentrum für Künstliche Intelligenz
  • GmbH
  • Fraunhofer FIT
  • FIZ Karlsruhe
  • Hamburger Informatik Technologie-Center e. V.
  • Leibniz University Hannover
  • Schloss Dagstuhl – Leibniz Center for Informatics
  • RWTH Aachen University
  • TIB Leibniz Information Centre for Science and Technology
  • TU Berlin
  • Technische Universität Dresden
  • Universität Leipzig
  • ZB MED Information Centre for Life Sciences
  • ZBW Leibniz Information Centre for Economics