Rewriting-Based Query Answering for Semantic Data Integration Systems

Maxime Buron 1 François Goasdoué 2 Ioana Manolescu 1 Marie-Laure Mugnier 3
1 CEDAR - Rich Data Analytics at Cloud Scale
Inria Saclay - Ile de France
2 SHAMAN - Symbolic and Human-centric view of dAta MANagement
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
3 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : We consider the integration of heterogeneous data under a global RDF graph data model, based on the knowledge expressed in an ontology describing the concepts relevant for an application, and a set of entailment rules which characterize the logical relationships between these concepts. We consider both standard RDF Schema rules and user-specified ones. We propose a data integration architecture to compute certain query answers in this setting. Existing approaches to query answering in the presence of knowledge (expressed here in the ontology and the entailment rules) involve either the materialization of inferences in the data or the refor-mulation of the query. Both approaches have well-known drawbacks. We introduce a new approach to query answering , based on a reduction to view-based query answering. This approach avoids both materialization in the data and query reformulation. We define restrictions of our general architecture under which our method is correct, and formally prove its correctness.
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Submitted on : Monday, November 19, 2018 - 5:14:16 PM
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  • HAL Id : hal-01927282, version 1

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Maxime Buron, François Goasdoué, Ioana Manolescu, Marie-Laure Mugnier. Rewriting-Based Query Answering for Semantic Data Integration Systems. 34ème Conférence sur la Gestion de Données – Principes, Technologies et Applications (BDA 2018), Oct 2018, Bucarest, Romania. ⟨hal-01927282⟩

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