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Linking Study Descriptions to the Linked Open Data (LOD) Cloud

Presenter 1
Johann Schaible
Gesis - Leibniz Institute for the Social Sciences
Presenter 2
Benjamin Zapilko
Gesis - Leibniz Institute for the Social Sciences
Presenter 3
Wolfgang Zenk-Moeltgen
Gesis - Leibniz Institute for the Social Sciences

The Data Catalogue contains the study descriptions for all archived studies at GESIS. These descriptions include information about primary researchers, research topics and objects, used methods and the resulting dataset. They are primarily used for archiving and retrieval. However, for this purpose the existing metadata can be enriched with further information about the study content, investigators, involved affiliations, collection dates, and more from other sources like e.g. DBpedia, GeoNames or the Name Authority File (PND) of the German National Library. In this paper we present how to enrich a study description with datasets from the LOD cloud. To accomplish this, we expose selected elements of the study description in RDF (Resource Description Framework) by applying commonly used vocabularies. This optimizes the interoperability to other RDF datasets and hence the possibility to express links between them. For link detection we use existing algorithms and tools, which are most promising in discovering relevant links to related data. Once links are detected, the study description is linked to external datasets and holds therefore additional information for the user, e.g. occurred events before or during the collection dates of a study, which are relevant to its topic.

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