Published September 6, 2024 | Version v1
Poster Open

The NFDI Knowledge Graph Infrastructure service for FAIR data management

  • 1. ROR icon Technische Informationsbibliothek (TIB)
  • 2. University of Mannheim
  • 3. ROR icon FIZ Karlsruhe – Leibniz Institute for Information Infrastructure
  • 4. ROR icon ZBW – Leibniz-Informationszentrum Wirtschaft
  • 5. GESIS Leibniz-Institut fur Sozialwissenschaften in Koln
  • 6. ZB MED – Leibniz Information Centre for Life Sciences
  • 7. ROR icon ZB MED - Information Centre for Life Sciences

Description

Knowledge Graphs (KGs) are data management technologies consisting of terminologies (vocabularies and ontologies) along with interconnected data entities, based on semantic web standards like RDF and SPARQL. KGs are powerful tools for the application of the FAIR data principles in and across research domains, and thereby supporting the mission of the National Research Data Infrastructure (NFDI) in Germany. Developing KG solutions as part of the data management strategies is seen as an important step towards FAIR(er) data by a range of consortia. The NFDI Association includes subject-specific consortia, responsible for delivering research data resources and services to their respective communities, with cross-cutting sections forming Working Groups to tackle cross-domain issues. Additionally, the Base4NFDI consortium provides services deemed to be broadly applicable to all domains. 

Besides the development of technical solutions, achieving interoperability requires a high degree of social coordination that can bridge disciplinary silos. The Working Group "Knowledge Graphs" provides such coordination by including members representing consortia across the spectrum of the natural and life sciences, engineering, humanities and social science domains. The WG also led the development of the Knowledge Graph Infrastructure (KGI4NFDI) Base service proposal. This new service will provide guidance, documentation, and software for creating and reusing KGs, alongside a registry of all KGs in use by NFDI consortia. Moreover, the service will develop an interoperability strategy, conduct surveys, and demonstrate the application of KGs across various research fields and scenarios using diverse methods. All solutions generated will be available under open-source and open-content licenses for broader benefit.

This presentation will outline concrete goals, methods and intended outcomes of KGI4NFDI during its initiation phase in 2024-2025. We would like to use this opportunity to gather  feedback and explore the potential for collaboration and integration of the KGI service framework within the EOSC community. 

 

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