Ontology focusing: knowledge-enriched databases on demand

Gogacz, Tomasz, Gutierrez Basulto, Victor ORCID: https://orcid.org/0000-0002-6117-5459, Ibanez Garcia, Yazmin ORCID: https://orcid.org/0000-0002-1276-904X, Murlak, Filip, Ortiz, Magdalena and Simkus, Mantas 2020. Ontology focusing: knowledge-enriched databases on demand. Presented at: 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostela, Spain, 29 August - 8 September 2020. Proceedings of the 24th European Conference on Artificial Intelligence. Frontiers in Artificial Intelligence and Applications , vol.325 IOS Press, pp. 745-752. 10.3233/FAIA200162

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Abstract

We propose a novel use of ontologies to aid the ondemand design of data-centric systems. By means of a process that we call focusing, a schema for a (possibly knowledge-enriched) database can be obtained semi-automatically from an existing ontology and a specification of the scope of the desired system.We formalize the inputs and outputs of focusing, and identify relevant computational problems: finding a schema via focusing, testing its consistency, and answering queries in the knowledge-enriched databases it produces. These definitions are independent from the ontology language. We then study focusing for selected description logics as ontology languages, and popular classes of queries for specifying the scope of the system. For several representative combinations, we study the decidability and complexity of the identified computational problems. As a by-product, we isolate (and solve) mixed variants of the classical satisfiability and entailment problems, where selected predicates are required to have finite extension, as well as the nullability problem, which is closely related to query emptiness.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	IOS Press
ISBN:	9781643681009
Date of First Compliant Deposit:	18 February 2020
Date of Acceptance:	15 January 2020
Last Modified:	04 Sep 2025 14:03
URI:	https://orca.cardiff.ac.uk/id/eprint/129802

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