Grr: Generating random RDF

Daniel Blum*, Sara Cohen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

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.

Original languageAmerican English
Title of host publicationThe Semantic Web
Subtitle of host publicationResearch and Applications - 8th Extended Semantic Web Conference, ESWC 2011, Proceedings
Pages16-30
Number of pages15
EditionPART 2
DOIs
StatePublished - 2011
Event8th Extended Semantic Web Conference, ESWC 2011 - Heraklion, Crete, Greece
Duration: 29 May 20112 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6643 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Extended Semantic Web Conference, ESWC 2011
Country/TerritoryGreece
CityHeraklion, Crete
Period29/05/112/06/11

Bibliographical note

Funding Information:
This work was partially supported by the GIF (Grant 2201-1880.6/2008) and the ISF (Grant 143/09).

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