Datalog±: a unified approach to ontologies and integrity constraints.

We report on a recently introduced family of expressive extensions of Datalog, called Datalog±, which is a new framework for representing ontological axioms in form of integrity constraints, and for query answering under such constraints. Datalog± is derived from Datalog by allowing existentially qu...

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Main Authors: Calì, A, Gottlob, G, Lukasiewicz, T
Other Authors: Fagin, R
Format: Journal article
Language:English
Published: ACM 2009
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author Calì, A
Gottlob, G
Lukasiewicz, T
author2 Fagin, R
author_facet Fagin, R
Calì, A
Gottlob, G
Lukasiewicz, T
author_sort Calì, A
collection OXFORD
description We report on a recently introduced family of expressive extensions of Datalog, called Datalog±, which is a new framework for representing ontological axioms in form of integrity constraints, and for query answering under such constraints. Datalog± is derived from Datalog by allowing existentially quantified variables in rule heads, and by enforcing suitable properties in rule bodies, to ensure decidable and efficient query answering. We first present different languages in the Datalog ± family, providing tight complexity bounds for all cases but one (where we have a low complexity AC0 upper bound). We then show that such languages are general enough to capture the most common tractable ontology languages. In particular, we show that the DL-Lite family of description logics and F-Logic Lite are expressible in Datalog ±. We finally show how stratified negation can be added to Datalog± while keeping ontology querying tractable in the data complexity. Datalog± is a natural and very general framework that can be successfully employed in different contexts such as data integration and exchange. This survey mainly summarizes two recent papers. Copyright 2009 ACM.
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spelling oxford-uuid:a6568297-40ed-4dbe-a426-14b91c27d1ed2022-03-27T02:46:38ZDatalog±: a unified approach to ontologies and integrity constraints.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:a6568297-40ed-4dbe-a426-14b91c27d1edEnglishSymplectic Elements at OxfordACM2009Calì, AGottlob, GLukasiewicz, TFagin, RWe report on a recently introduced family of expressive extensions of Datalog, called Datalog±, which is a new framework for representing ontological axioms in form of integrity constraints, and for query answering under such constraints. Datalog± is derived from Datalog by allowing existentially quantified variables in rule heads, and by enforcing suitable properties in rule bodies, to ensure decidable and efficient query answering. We first present different languages in the Datalog ± family, providing tight complexity bounds for all cases but one (where we have a low complexity AC0 upper bound). We then show that such languages are general enough to capture the most common tractable ontology languages. In particular, we show that the DL-Lite family of description logics and F-Logic Lite are expressible in Datalog ±. We finally show how stratified negation can be added to Datalog± while keeping ontology querying tractable in the data complexity. Datalog± is a natural and very general framework that can be successfully employed in different contexts such as data integration and exchange. This survey mainly summarizes two recent papers. Copyright 2009 ACM.
spellingShingle Calì, A
Gottlob, G
Lukasiewicz, T
Datalog±: a unified approach to ontologies and integrity constraints.
title Datalog±: a unified approach to ontologies and integrity constraints.
title_full Datalog±: a unified approach to ontologies and integrity constraints.
title_fullStr Datalog±: a unified approach to ontologies and integrity constraints.
title_full_unstemmed Datalog±: a unified approach to ontologies and integrity constraints.
title_short Datalog±: a unified approach to ontologies and integrity constraints.
title_sort datalog a unified approach to ontologies and integrity constraints
work_keys_str_mv AT calia datalogaunifiedapproachtoontologiesandintegrityconstraints
AT gottlobg datalogaunifiedapproachtoontologiesandintegrityconstraints
AT lukasiewiczt datalogaunifiedapproachtoontologiesandintegrityconstraints