Grr: Generating Random RDF

Presented at: 8th Extended Semantic Web Conference (ESWC2011)

by Daniel Blum, Sara Cohen

This paper presents Grr, a powerful system for generating random RDF data, which can be used to test Semantic Web applications. Grr has a SPARQL-like syntax, which allows the system to be both powerful and convenient. It is shown that Grr can easily be used to produce intricate datasets, such as the LUBM benchmark. Optimization techniques are employed, which make the generation process efficient and scalable.

Keywords: RDF, Semantic Web, data generation

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