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RDFox: a highly-scalable RDF store

Abstract:
We present RDFox—a main-memory, scalable, centralised RDF store that supports materialisation-based parallel datalog reasoning and SPARQL query answering. RDFox uses novel and highlyefficient parallel reasoning algorithms for the computation and incremental update of datalog materialisations with efficient handling of owl: sameAs. In this system description paper, we present an overview of the system architecture and highlight the main ideas behind our indexing data structures and our novel reasoning algorithms. In addition, we evaluate RDFox on a high-end SPARC T5-8 server with 128 physical cores and 4TB of RAM. Our results show that RDFox can effectively exploit such a machine, achieving speedups of up to 87 times, storage of up to 9.2 billion triples, memory usage as low as 36.9 bytes per triple, importation rates of up to 1 million triples per second, and reasoning rates of up to 6.1 million triples per second.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-319-25010-6_1

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author

Contributors

Role:
Editor
Role:
Editor
Role:
Editor
Role:
Editor
Role:
Editor


Publisher:
Springer Verlag
Host title:
International Semantic Web Conference
Journal:
International Semantic Web Conference More from this journal
Volume:
9367
Pages:
3-20
Publication date:
2015-10-24
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
ISBN:
9783319250090


Pubs id:
pubs:576342
UUID:
uuid:2a08b023-77be-431a-a08c-89b47381586a
Local pid:
pubs:576342
Source identifiers:
576342
Deposit date:
2016-03-06

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