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How Can Reasoner Performance of ABox Intensive Ontologies Be Predicted? Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Towards Answering Provenance-Enabled SPARQL Queries Over RDF Data Cubes

Authors : Kim Ahlstrøm, Katja Hose, Torben Bach Pedersen

Published in: Semantic Technology

Publisher: Springer International Publishing

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Abstract

The SPARQL 1.1 standard has made it possible to formulate analytical queries in SPARQL. While some approaches have become available for processing analytical queries on RDF data cubes, little attention has been paid to answering provenance-enabled queries over such data. Yet, considering provenance is a prerequisite to being able to validate if a query result is trustworthy. The main challenge for existing triple stores is the way provenance can be encoded in standard triple stores based on context values (named graphs). Hence, in this paper we analyze the suitability of existing triple stores for answering provenance-enabled queries on RDF data cubes, identify their shortcomings, and propose an index to handle the high number of context values that provenance encoding typically entails. Our experimental results using the Star Schema Benchmark show the feasibility and scalability of our index and query evaluation strategies.

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previous chapter ASPG: Generating OLAP Queries for SPARQL Benchmarking
next chapter Data Analysis of Hierarchical Data for RDF Term Identification
Footnotes
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Metadata
Title
Towards Answering Provenance-Enabled SPARQL Queries Over RDF Data Cubes
Authors
Kim Ahlstrøm
Katja Hose
Torben Bach Pedersen
Copyright Year
2016
Book
Semantic Technology

Print ISBN: 978-3-319-50111-6

Electronic ISBN: 978-3-319-50112-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-50112-3_14