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.

Monotone Abstractions in Ontology-Based Data Management / Cima, Gianluca; Console, Marco; Lenzerini, Maurizio; Poggi, Antonella. - 36:5(2022), pp. 5556-5563. (Intervento presentato al convegno Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI-2022 tenutosi a In remote) [10.1609/aaai.v36i5.20495].

Monotone Abstractions in Ontology-Based Data Management

Cima, Gianluca
;
Console, Marco
;
Lenzerini, Maurizio
;
Poggi, Antonella
2022

Abstract

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.
2022
Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI-2022
Knowledge Representation And Reasoning (KRR); Abstracting; Knowledge representation; Ontology; Query languages; Query processing; Semantics; Description logics
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Monotone Abstractions in Ontology-Based Data Management / Cima, Gianluca; Console, Marco; Lenzerini, Maurizio; Poggi, Antonella. - 36:5(2022), pp. 5556-5563. (Intervento presentato al convegno Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI-2022 tenutosi a In remote) [10.1609/aaai.v36i5.20495].
File allegati a questo prodotto
File Dimensione Formato  
Cima_Monotone-Abstractions_2022.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 170.42 kB
Formato Adobe PDF
170.42 kB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1652612
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 0
social impact