GESIS Knowledge Graph: A blueprint for connecting a domain-specific knowledge graph to international research infrastructures

The GESIS Knowledge Graph (GESIS KG) is a comprehensive Research Knowledge Graph (RKG) that semantically links metadata on social science research resources available through GESIS Search. It connects datasets, publications, survey variables, and survey instruments with each other and to entities such as authors and concepts, enhancing research discoverability and reuse. By using W3C standards, common vocabularies, and persistent identifiers, GESIS KG ensures interoperability, provenance tracking, and supports reproducible research. Practical use cases include exploring related publications, analyzing citation patterns, and integrating metadata into external systems via standardized APIs and structured formats.

To maximize accessibility and interoperability, GESIS KG is available through data dumps for offline use, is embedded in the GESIS Search portal, and supports integration across the ecosystem of the German National Research Data Infrastructure (NFDI) and other research infrastructures by provision of various APIs. A SPARQL endpoint allows complex queries and powers a live integration into systems like NFDI4DataScience Gateway or the KGI4NFDI service registry to support discovery and federation across diverse knowledge graphs.

An OAI-PMH API enables metadata harvesting in standardized formats (e.g., DataCite, OpenAIRE), supporting harvesting and integration of metadata records of the GESIS KG into infrastructures from data aggregators. Efforts are underway to expand the OAI-PMH API to integrate with OpenAIRE and by doing so with the European Open Science Cloud (EOSC), potentially serving as a blueprint for connecting other NFDI data points to EOSC.