The Case for a Common, Reusable Knowledge Graph Infrastructure for NFDI




NFDI, Base4NFDI, FAIR principles, Research Data Management, Knowledge Graphs, Knowledge Graph Infrastructure


The Strategic Research and Innovation Agenda (SRIA) of the European Commission identifies Knowledge Graphs (KGs) as one of the most important technologies for building an interoperability framework and enabling data exchange among users across countries, sectors, and disciplines [1]. KG is a graph-structured knowledge base containing a terminology (vocabulary or ontology) and data entities interrelated via the terminology [2]. KGs are based on semantic web technologies (RDF, SPARQL, etc.) and often used for agile data integration. KGs also play an essential role within Germany as a vehicle to connect research data and research-related entities and make those accessible – examples include the GESIS Knowledge Graph Infrastructure, TIB Open Research Knowledge Graph, and Furthermore, the Wikidata knowledge graph, maintained by Wikimedia Germany, contains a large number of research-related entities and is widely used in scientific knowledge management in addition to being an important advocacy tool for open data [3]. Extending domain-specific ontology-supported KGs with the multidisciplinary, crowdsourced knowledge in Wikidata KG would enable significant applications. The linking between expert knowledge systems and world knowledge empowers lay persons to benefit from high-quality research data and ultimately contributes to increasing confidence in scientific research in society.


Download data is not yet available.


European Commission, Directorate-General for Research and Innovation, “Strategic Research and Innovation Agenda (SRIA) of the European Open Science Cloud (EOSC),” Publications Office of the European Union, 2022. [Online]. Available:

A. Hogan, C. Gutierrez, M. Cochcz, G. de Melo, S. Kirranc, A. Pollcrcs, et al, Knowledge Graphs. Springer Cham, 2022. [Online]. Available:

L. Rossenova, P. Duchesne, and I. Blümel, “Wikidata and Wikibase as complementary research data management services for cultural heritage data,” in Proc. of the 3rd Wikidata Workshop 2022, co-located with the 21st International Semantic Web Con-ference (ISWC2022), Virtual Event, Hangzhou, China, October 2022. [Online]. Availa-ble:

The MaRDI consortium, “MaRDI: Mathematical Research Data Initiative Proposal,” Zenodo, 2022. [Online]. Available:

R. Shigapov and I. Schumm. (2021). BERD: The knowledge graph of German compa-nies. Presented at Wikibase in Knowledge Graph based Research Data Management (NFDI) Projects. [Online]. Available:

S. Bruns, H. Fliegel, E. Posthumus, H. Sack, T. Schrade, and T. Tietz. (2023). Knowledge Graph-basierte Forschungsdatenintegration in NFDI4Culture. Presented at DHd2023 - Open Humanities Open Culture, Belval and Trier. [Online]. Available:

S. Bingert, J. Brase, F. Burger, B. Dreyer, S. Hagemann-Wilholt, P. Vierkant, and P. Wieder, “Concept for Setting up the Persistent Identifier Services Working Group in the NFDI Section "Common Infrastructures" (1.0),” Zenodo, 2022. [Online]. Available:

I. Anders,T. Arera-Rütenik, S. Arndt, R. Baum, N. Betancort, I. Blümel, C. Busse, A. Daniel, F. Engel, L. Ghiringelli, S. Hachinger, H.r Israel, N. Karam, A. Kranz, R. Lenz, D. Linke, T. Petrenko, L. Rossenova, D. Schulz, and N. Kockmann, “Ontology Har-monization and Mapping - Working Group Charter (NFDI section-metadata) (1.0),” Zenodo, 2022. [Online]. Available:

M. Stocker, L. Rossenova, R. Shigapov, N. Betancort, S. Dietze, B. Murphy, C. Bölling, M. Schubotz, and O. Koepler, “Knowledge Graphs – Working Group Charter (NFDI Section-Metadata) (1.2).” Zenodo, 2023. [Online]. Available:

P. Pelz, S. Herres-Pawlis, J. Liermann, F. Strauß, D. Ohse, N. Kockmann, M. Liebau, D. Tschink, J. Dierkes, J. Vandendorpe, R. Müller, K. Förstner, T. Hamann, C. Keßler, J. O. Heuer, D. Hausen, K. Sauerland, A. Bonn, A. Münzmay, and T. Hörner, “Working Group Charter Training Infrastructures (1.0),” Zenodo, 2022. [Online]. Available:

P. Strömert and O. Koepler. (2022). Ontologies4Chem: A use case to build a NMR re-search data knowledge graph. Presented at ACS Spring Meeting. 23.03.2022. [Online]. Available:

O. Simons. “FactGrid Goes NFDI.” FactGrid Blog. (accessed April 20, 2023).




How to Cite

Rossenova, L., Schubotz, M., & Shigapov, R. (2023). The Case for a Common, Reusable Knowledge Graph Infrastructure for NFDI. Proceedings of the Conference on Research Data Infrastructure , 1.
Received 2023-04-20
Accepted 2023-06-29
Published 2023-09-07