Grr: Generating random RDF

Daniel Blum; Sara Cohen

doi:10.1007/978-3-642-21064-8_2

Grr: Generating random RDF

Daniel Blum^*, Sara Cohen

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	The Semantic Web
Subtitle of host publication	Research and Applications - 8th Extended Semantic Web Conference, ESWC 2011, Proceedings
Pages	16-30
Number of pages	15
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-21064-8_2
State	Published - 2011
Event	8th Extended Semantic Web Conference, ESWC 2011 - Heraklion, Crete, Greece Duration: 29 May 2011 → 2 Jun 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6643 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th Extended Semantic Web Conference, ESWC 2011
Country/Territory	Greece
City	Heraklion, Crete
Period	29/05/11 → 2/06/11

Bibliographical note

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

Access to Document

10.1007/978-3-642-21064-8_2

Cite this

Blum, D., & Cohen, S. (2011). Grr: Generating random RDF. In The Semantic Web: Research and Applications - 8th Extended Semantic Web Conference, ESWC 2011, Proceedings (PART 2 ed., pp. 16-30). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6643 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-21064-8_2

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title = "Grr: Generating random RDF",

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.",

author = "Daniel Blum and Sara Cohen",

note = "Funding Information: This work was partially supported by the GIF (Grant 2201-1880.6/2008) and the ISF (Grant 143/09).; 8th Extended Semantic Web Conference, ESWC 2011 ; Conference date: 29-05-2011 Through 02-06-2011",

year = "2011",

doi = "10.1007/978-3-642-21064-8_2",

language = "אנגלית",

isbn = "9783642210631",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Blum, D & Cohen, S 2011, Grr: Generating random RDF. in The Semantic Web: Research and Applications - 8th Extended Semantic Web Conference, ESWC 2011, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6643 LNCS, pp. 16-30, 8th Extended Semantic Web Conference, ESWC 2011, Heraklion, Crete, Greece, 29/05/11. https://doi.org/10.1007/978-3-642-21064-8_2

Grr: Generating random RDF. / Blum, Daniel; Cohen, Sara.
The Semantic Web: Research and Applications - 8th Extended Semantic Web Conference, ESWC 2011, Proceedings. PART 2. ed. 2011. p. 16-30 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6643 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Grr: Generating random RDF

Abstract

Publication series

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Bibliographical note

Access to Document

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