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        <AuthEnty affiliation="GESIS – Leibniz Institute for the Social Sciences" xml:lang="en">Biswas, Debanjali
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        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="en">Gupta, Endri
        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="de">Gupta, Endri
        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="en">Yu, Ran
        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="de">Yu, Ran
        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="en">Zapilko, Benjamin
        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="de">Zapilko, Benjamin
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      <abstract xml:lang="en">The GESIS Knowledge Graph (GESIS KG) represents metadata of all scientific resources available in the GESIS Search (https://search.gesis.org/) and its semantic relationships in an integrated and consistent form and makes them accessible for integration and reuse. Understanding relations and dependencies between scientific resources is crucial to capture provenance, ensure reproducibility of research and facilitate informed search across resources. Hence, the GESIS KG captures links between different scientific resources, e.g., links between data, publications, survey instruments, survey variables, and links between entities like authors and social science concepts. The GESIS KG is geared towards interoperability and uses established W3C standards and widely accepted vocabularies, such as schema.org, DDI, the NFDIcore Ontology among others to increase interoperability and reusability of data on the Web for both humans and machines, e.g., through APIs. On instance-level, we address interoperability by reusing PIDs from commonly used PID systems, interlinking the GESIS KG with other KG provided by GESIS as well within the NFDI.  Find more information at Find more information at  &lt;a href="https://data.gesis.org/gesiskg/ " target="_blank"&gt;https://data.gesis.org/gesiskg/  &lt;/a&gt;  Detailed description of the files can be found in GESISKG_readme.txt  Keywords: knowledge graph, semantic web, scholarly resource metadata, social sciences</abstract><abstract xml:lang="de">The GESIS Knowledge Graph (GESIS KG) represents metadata of all scientific resources available in the GESIS Search (https://search.gesis.org/) and its semantic relationships in an integrated and consistent form and makes them accessible for integration and reuse. Understanding relations and dependencies between scientific resources is crucial to capture provenance, ensure reproducibility of research and facilitate informed search across resources. Hence, the GESIS KG captures links between different scientific resources, e.g., links between data, publications, survey instruments, survey variables, and links between entities like authors and social science concepts. The GESIS KG is geared towards interoperability and uses established W3C standards and widely accepted vocabularies, such as schema.org, DDI, the NFDIcore Ontology among others to increase interoperability and reusability of data on the Web for both humans and machines, e.g., through APIs. On instance-level, we address interoperability by reusing PIDs from commonly used PID systems, interlinking the GESIS KG with other KG provided by GESIS as well within the NFDI.  Find more information at Find more information at  &lt;a href="https://data.gesis.org/gesiskg/ " target="_blank"&gt;https://data.gesis.org/gesiskg/  &lt;/a&gt;  Detailed description of the files can be found in GESISKG_readme.txt  Keywords: knowledge graph, semantic web, scholarly resource metadata, social sciences</abstract>
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