Ontology-Based RDF Integration of Heterogeneous Data

Maxime Buron 1 François Goasdoué 2 Ioana Manolescu 1 Marie-Laure Mugnier 3
1 CEDAR - Rich Data Analytics at Cloud Scale
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], 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 : The proliferation of heterogeneous data sources in many application contexts brings an urgent need for expressive and efficient data integration mechanisms. There are strong advantages to using RDF graphs as the integration format: being schemaless, they allow for flexible integration of data from all sources; RDF graphs can be interpreted with the help of an ontology, describing application semantics; last but not least, RDF enables joint querying of the data and the ontology. To address this need, we introduce the novel class of RDF Integration Systems (RIS), going beyond the state of the art in the expressive power, that is, in the ability to expose, integrate and flexibly query data from heterogeneous sources through GLAV (global-local-as-view) mappings. Our second contribution is a set of query answering strategies, two combining existing techniques and three others based on an innovative integration of view-based rewriting; our experiments show that the latter bring strong performance advantages .
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Maxime Buron, François Goasdoué, Ioana Manolescu, Marie-Laure Mugnier. Ontology-Based RDF Integration of Heterogeneous Data. [Technical Report] LIX, Ecole polytechnique; Inria Saclay. 2019. ⟨hal-02266517⟩

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