SAOR: Template Rule Optimisations for Distributed Reasoning over 1 Billion Linked Data Triples

Aidan Hogan, Jeff Z. Pan, Axel Polleres, Stefan Decker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we discuss optimisations of rule-based materialisation approaches for reasoning over large static RDF datasets. We generalise and re-formalise what we call the ``partial-indexing'' approach to scalable rule-based materialisation: the approach is based on a separation of terminological data, which has been shown in previous and related works to enable highly scalable and distributable reasoning for specific rulesets; in so doing, we provide some completeness propositions with respect to semi-naïve evaluation. We then show how related work on template rules -- T-Box-specific dynamic rulesets created by binding the terminological patterns in the static ruleset -- can be incorporated and optimised for the partial-indexing approach. We evaluate our methods using LUBM(10) for RDFS, pD* (OWL Horst) and OWL 2 RL, and thereafter demonstrate pragmatic distributed reasoning over 1.12 billion Linked Data statements for a subset of OWL 2 RL/RDF rules we argue to be suitable for Web reasoning.
Original languageEnglish
Title of host publicationThe Semantic Web -- ISWC 2010
Subtitle of host publication9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I
EditorsPeter F. Patel-Schneider, Yue Pan, Pascal Hitzler, Peter Mika, Lei Zhang, Jeff Z. Pan, Ian Horrocks, Birte Glimm
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages337-353
Number of pages17
ISBN (Electronic)978-3-642-17746-0
ISBN (Print)978-3-642-17745-3
DOIs
Publication statusPublished - 8 Dec 2010

Publication series

NameLecture Notes in Computer Science
PublisherSpringer, Berlin, Heidelberg
Volume6496
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fingerprint

Dive into the research topics of 'SAOR: Template Rule Optimisations for Distributed Reasoning over 1 Billion Linked Data Triples'. Together they form a unique fingerprint.

Cite this