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Dataset Knowledge Graph

The Dataset Knowledge Graph enriches the Dataset Register with insights derived from the actual content of each dataset. A pipeline periodically fetches valid dataset descriptions, analyses the RDF distributions they point to, and produces Dataset Summaries – modelled as VoID – that describe the empirical shape of each dataset:

  • the counts of RDF triples, subjects, predicates, and objects (split into literals and URIs);
  • the classes that occur and how many instances each has;
  • the predicates that occur and how they are distributed across subject classes;
  • the external terminology sources and vocabularies the dataset links to.

These summaries help researchers, software developers, and data platform builders assess whether a dataset is suitable for their purpose and which query patterns they can use to access it.

Access​

  • Explore aggregated insights across all datasets in the Dataset Knowledge Graph datastory.
  • Query the graph directly via the SPARQL endpoint at https://triplestore.netwerkdigitaalerfgoed.nl/repositories/dataset-knowledge-graph.
  • The source code of the pipeline is available on GitHub.