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Towards semantics for abstractions in ontology-driven conceptual modeling
Free University of Bozen-Bolzano, Bolzano, Italy.
Free University of Bozen-Bolzano, Bolzano, Italy.
Umeå University, Faculty of Science and Technology, Department of Computing Science. Free University of Bozen-Bolzano, Bolzano, Italy.ORCID iD: 0000-0001-5174-9693
University of Twente, Enschede, Netherlands.
2023 (English)In: Advances in conceptual modeling: ER 2023 Workshops, CMLS, CMOMM4FAIR, EmpER, JUSMOD, OntoCom, QUAMES, and SmartFood, Lisbon, Portugal, November 6–9, 2023, proceedings / [ed] Tiago Prince Sales; João Araújo; José Borbinha; Giancarlo Guizzardi, Springer Science+Business Media B.V., 2023, p. 199-209Conference paper, Published paper (Refereed)
Abstract [en]

Ontology-driven conceptual models are precise and semantically transparent domain descriptions that enable the development of information systems. As symbolic artefacts, such models are usually considered to be self-explanatory. However, the complexity of a system significantly correlates with the complexity of the conceptual model that describes it. Abstractions of both conceptual models and ontology-driven conceptual models are thus considered to be a promising way to improve the understandability and comprehensibility of those models. Although algorithms for providing abstractions of such models already exist, they still lack precisely formulated formal semantics. This paper aims to provide an approach towards the formalization of the abstraction process. We specify in first-order modal logic one of the graph-rewriting rules for ontology-driven conceptual model abstractions, in order to verify the correctness of the corresponding abstraction step. We also assess the entire network of abstractions of ontology-driven conceptual models and discuss existing drawbacks.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2023. p. 199-209
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 14319
Keywords [en]
Abstractions of Ontology-Driven Conceptual Models, Networks of Model Abstractions, Semantics for Abstractions
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-217411DOI: 10.1007/978-3-031-47112-4_19Scopus ID: 2-s2.0-85177175844ISBN: 9783031471117 (print)OAI: oai:DiVA.org:umu-217411DiVA, id: diva2:1816662
Conference
42nd International Conference on Conceptual Modeling, ER 2023, Lisbon, Portugal, November 6–9, 2023
Available from: 2023-12-04 Created: 2023-12-04 Last updated: 2023-12-04Bibliographically approved

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Calvanese, Diego

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CiteExportLink to record
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