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Poster communications

Existential Rules: A Graph-Based View

Marie-Laure Mugnier 1
1 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 rules that allow to assert the existence of new individuals, an ability called value invention in databases. These rules are of the form body --> head, where the body and the head are function-free conjunctions of atoms, and variables that occur only in the head are existentially quantified, hence their name existential rules. Existential rules have long been studied in databases as high-level constraints called tuple generating dependencies. Recently, there has been renewed interest for these rules in the context of ontology-based data access (OBDA), a new paradigm that seeks to exploit the semantics encoded in ontologies while querying data. The deductive database language Datalog could be seen as a natural candidate for expressing ontological knowledge in this context, however its limitation is that it does not allow for value invention, since all variables in a rule head necessarily occur in the rule body. Value invention has been recognized as a necessary prerequisite in an open-world perspective, where all individuals are not known a priori. It is in particular a feature of description logics (DLs), well-known languages dedicated to ontological representation and reasoning. This prerequisite motivated the recent extension of Datalog to existential rules, which gave rise to the Datalog +/- formalism. In this talk, we present a graph view of the existential rule framework and some related results.
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Poster communications
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Contributor : Marie-Laure Mugnier <>
Submitted on : Monday, September 16, 2019 - 1:01:33 PM
Last modification on : Tuesday, September 17, 2019 - 10:28:53 AM
Long-term archiving on: : Saturday, February 8, 2020 - 2:07:44 PM


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Marie-Laure Mugnier. Existential Rules: A Graph-Based View. Pablo Barceló; Reinhard Pichler. Datalog 2.0, Sep 2012, Vienne, Austria. Springer, 2nd International Workshop on Datalog 2.0, LNCS (7494), pp.21-26, 2012, ⟨10.1007/978-3-642-32925-8_3⟩. ⟨lirmm-00763474⟩



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