Grr: generating random RDF

Authors:
Daniel Blum;Sara Cohen
Affiliations:
School of Computer Science and Engineering, The Hebrew University of Jerusalem;School of Computer Science and Engineering, The Hebrew University of Jerusalem
Venue:
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Year:
2011

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Abstract

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.