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What do users think about abstractions of ontology-driven conceptual models?
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: Research Challenges in Information Science: Information Science and the Connected World: 17th International Conference, RCIS 2023, Corfu, Greece, May 23–26, 2023, Proceedings, Springer, 2023, p. 53-68Conference paper, Published paper (Refereed)
Abstract [en]

In a previous paper, we proposed an algorithm for ontology-driven conceptual model abstractions [18]. We have implemented and tested this algorithm over a FAIR Catalog of such models represented in the OntoUML language. This provided evidence for the correctness of the algorithm’s implementation, i.e., that it correctly implements the model transformation rules prescribed by the algorithm, and its effectiveness, i.e., it is able to achieve high compression (summarization) rates over these models. However, in addition to these properties, it is fundamental to test the validity of this algorithm, i.e., that it achieves what it is intended to do, namely provide summarizing abstractions over these models whilst preserving the gist of the conceptualization being represented. We performed three user studies to evaluate the usefulness of the resulting abstractions as perceived by modelers. This paper reports on the findings of these user studies and reflects on how they can be exploited to improve the existing algorithm.

Place, publisher, year, edition, pages
Springer, 2023. p. 53-68
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 476
Keywords [en]
Conceptual Model Abstraction, Ontology-Driven Conceptual Models, User Study
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-212086DOI: 10.1007/978-3-031-33080-3_4Scopus ID: 2-s2.0-85163329659ISBN: 978-3-031-33079-7 (print)ISBN: 978-3-031-33080-3 (electronic)OAI: oai:DiVA.org:umu-212086DiVA, id: diva2:1782815
Conference
17th International Conference on Research Challenges in Information Sciences, RCIS 2023, Corfu, Greece, May 23-26, 2023
Available from: 2023-07-17 Created: 2023-07-17 Last updated: 2023-07-17Bibliographically approved

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Calvanese, Diego

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CiteExportLink to record
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