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Communication Dans Un Congrès Année : 2022

Monotone Abstractions in Ontology-Based Data Management

Résumé

In Ontology-Based Data Management (OBDM), an abstraction of a source query q is a query over the ontology capturing the semantics of q in terms of the concepts and the relations available in the ontology. Since a perfect characterization of a source query may not exist, the notions of best sound and complete approximations of an abstraction have been introduced and studied in the typical OBDM context, i.e., in the case where the ontology is expressed in DL-Lite, and source queries are expressed as unions of conjunctive queries (UCQs). Interestingly, if we restrict our attention to abstractions expressed as UCQs, even best approximations of abstractions are not guaranteed to exist. Thus, a natural question to ask is whether such limitations affect even larger classes of queries. In this paper, we answer this fundamental question for an essential class of queries, namely the class of monotone queries. We define a monotone query language based on disjunctive Datalog enriched with an epistemic operator, and show that its expressive power suffices for expressing the best approximations of monotone abstractions of UCQs.
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Dates et versions

hal-03686667 , version 1 (02-06-2022)

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  • HAL Id : hal-03686667 , version 1

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Gianluca Cima, Marco Console, Maurizio Lenzerini, Antonella Poggi. Monotone Abstractions in Ontology-Based Data Management. The Thirty-Sixth AAAI Conference on Artificial Intelligence, Feb 2022, Virtual Event, Canada. ⟨hal-03686667⟩

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