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Multi-level ontology-based conceptual modeling

Authors:

Victorio A. Carvalho,

Joo Paulo A. Almeida,

Claudenir M. Fonseca,

Giancarlo GuizzardiAuthors Info & Claims

Data & Knowledge Engineering, Volume 109, Issue C

Pages 3 - 24

https://doi.org/10.1016/j.datak.2017.03.002

Published: 01 May 2017 Publication History

Abstract

Since the late 1980s, there has been a growing interest in the use of foundational ontologies to provide a sound theoretical basis for the discipline of conceptual modeling. This has led to the development of ontology-based conceptual modeling techniques whose modeling primitives reflect the conceptual categories defined in a foundational ontology. The ontology-based conceptual modeling language OntoUML, for example, incorporates the distinctions underlying the taxonomy of types in the Unified Foundational Ontology (UFO) (e.g., kinds, phases, roles, mixins, etc.). This approach has focused so far on the support to types whose instances are individuals in the subject domain, with no provision for types of types (or categories of categories). In this paper we address this limitation by extending the Unified Foundational Ontology with the MLT multi-level theory. The UFO-MLT combination serves as a foundation for conceptual models that can benefit from the ontological distinctions of UFO as well as MLT's basic concepts and patterns for multi-level modeling. We discuss the impact of the extended foundation to multi-level conceptual modeling.

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Cited By

Hinkel GCombemale BWimmer MChechik MEgyed A(2024)Modeling a Warehouse system using refinements and decompositionProceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems10.1145/3652620.3688209(770-779)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3652620.3688209
Yeom KYang HPark GJeon MKo YOh BLee KBaeza-Yates RBonchi F(2024)Embedding Two-View Knowledge Graphs with Class Inheritance and Structural SimilarityProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671941(3931-3941)Online publication date: 25-Aug-2024
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Bogea Gomes SSantoro FMira da Silva MPinto PGuizzardi G(2023)Towards a core ontology of organisational transformationApplied Ontology10.3233/AO-23027618:1(31-70)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/AO-230276
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Published In

cover image Data & Knowledge Engineering

Data & Knowledge Engineering Volume 109, Issue C

May 2017

124 pages

ISSN:0169-023X

Issue’s Table of Contents

Copyright © Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 May 2017

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Cited By

Hinkel GCombemale BWimmer MChechik MEgyed A(2024)Modeling a Warehouse system using refinements and decompositionProceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems10.1145/3652620.3688209(770-779)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3652620.3688209
Yeom KYang HPark GJeon MKo YOh BLee KBaeza-Yates RBonchi F(2024)Embedding Two-View Knowledge Graphs with Class Inheritance and Structural SimilarityProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671941(3931-3941)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671941
Bogea Gomes SSantoro FMira da Silva MPinto PGuizzardi G(2023)Towards a core ontology of organisational transformationApplied Ontology10.3233/AO-23027618:1(31-70)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/AO-230276
Shuttleworth DPadilla J(2022)From Narratives to Conceptual Models via Natural Language ProcessingProceedings of the Winter Simulation Conference10.5555/3586210.3586396(2222-2233)Online publication date: 11-Dec-2022
https://dl.acm.org/doi/10.5555/3586210.3586396
Guizzardi GBotti Benevides AFonseca CPorello DAlmeida JPrince Sales TBorgo SGalton AKutz O(2022)UFOApplied Ontology10.3233/AO-21025617:1(167-210)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/AO-210256
Li YCurrim FRam S(2022)Data Completeness and Complex Semantics in Conceptual Modeling: The Need for a Disaggregation ConstructJournal of Data and Information Quality10.1145/353278414:4(1-21)Online publication date: 23-Nov-2022
https://dl.acm.org/doi/10.1145/3532784
Batista JAlmeida JZambon EGuizzardi G(2022)Ontologically correct taxonomies by constructionData & Knowledge Engineering10.1016/j.datak.2022.102012139:COnline publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.datak.2022.102012
Neumayr BSchrefl M(2022)Domain object hierarchies inducing multi-level modelsSoftware and Systems Modeling (SoSyM)10.1007/s10270-022-00973-721:2(587-621)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s10270-022-00973-7
Fonseca CGuizzardi GAlmeida JSales TPorello D(2022)Incorporating Types of Types in Ontology-Driven Conceptual ModelingConceptual Modeling10.1007/978-3-031-17995-2_2(18-34)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1007/978-3-031-17995-2_2
De Giacomo GOriol XRosati RSavo D(2021)Instance-Level Update in DL-Lite Ontologies through First-Order RewritingJournal of Artificial Intelligence Research10.1613/jair.1.1241470(1335-1371)Online publication date: 1-May-2021
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