Data Science and Artificial Intelligence

The FAIR Data Spaces project established foundations for common data spaces for industry and research based on the principles of findable, accessible, interoperable, reusable data. In 2024, highlights from the project include open source demonstrators that bridge research data infrastructures and industry-driven data spaces to showcase the added value of data exchange, five episodes in a new podcast series, and political consulting on innovative data policy. 

The FAIR Data Spaces project, funded by the Federal Ministry of Education and Research (BMBF) and coordinated by Fraunhofer FIT from 2021 to 2024, laid the foundations for common data spaces for industry and research from an organizational, legal and technical perspective, building on the principles that data should be FAIR, i.e., findable, accessible, interoperable, and reusable. In 2024, the project delivered primarily on the practical perspective, with additional demonstrators, a podcast series, and political consulting.

The initial data space demonstrators developed by the project consortium (realizing cross-platform data analysis, visual analysis of geospatial biodiversity data, and data quality assurance) had scaled pre-existing services of the German National Research Data Infrastructure (NFDI) to industry-compatible clouds.

Beyond this, Fraunhofer FIT initiated an open call for implementing additional demonstrators, focusing on creative demonstrations of the added value of exchanging data between research organizations and companies and more specifically building bridges between one operational research data infrastructure and one industry-driven data space each. This resulted in demonstrators for exchanging clinical research results and medical product information, digital health applications, digital twins for sustainable battery manufacturing, and computing ESG scores for properties of landholders by a biodiversity analysis of satellite images.

Part of these demonstrators, legal principles for data sharing, the FAIR principles, and their connection to data spaces were featured in the five initial episodes of the ongoing "NFDI podcast – For a FAIR Data Future" series.

Building on the FAIR Data Spaces experience, project coordinator Dr. Christoph Lange-Bever gave advice to the digital committee of the German federal parliament, in their hearing on innovative data policy. In addition, Fraunhofer FIT is contributing to Mission KI, the National Initiative for Artificial Intelligence and Data Economy, whose FDO One and FDO Connect projets realize data discovery across data spaces via FAIR Digital Objects.

Further information: FAIR Data Spaces | NFDI