A FAIR catalog of ontology-driven conceptual models

Tiago Prince Sales; Pedro Paulo F. Barcelos; Claudenir M. Fonseca; Isadora Valle Souza; Elena Romanenko; César Henrique Bernabé; Luiz Olavo Bonino da Silva Santos; Mattia Fumagalli; Joshua Kritz; João Paulo A. Almeida; Giancarlo Guizzardi

doi:10.1016/j.datak.2023.102210

A FAIR catalog of ontology-driven conceptual models

Tiago Prince Sales, Pedro Paulo F. Barcelos^*, Claudenir M. Fonseca, Isadora Valle Souza, Elena Romanenko, César Henrique Bernabé, Luiz Olavo Bonino da Silva Santos, Mattia Fumagalli, Joshua Kritz, João Paulo A. Almeida, Giancarlo Guizzardi

^*Corresponding author for this work

Semantics, Cybersecurity & Services

Research output: Contribution to journal › Article › Academic › peer-review

7 Citations (Scopus)

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Abstract

Multi-domain model catalogs serve as empirical sources of knowledge and insights about specific domains, about the use of a modeling language's constructs, as well as about the patterns and anti-patterns recurrent in the models of that language crosscutting different domains. They may support domain and language learning, model reuse, knowledge discovery for humans, and reliable automated processing and analysis if built following generally accepted quality requirements for scientific data management. More specifically, not unlike scientific (meta)data, models should be shared according to the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). In this paper, we report on the construction of a FAIR model catalog for Ontology-Driven Conceptual Modeling research, a trending paradigm lying at the intersection of conceptual modeling and ontology engineering in which the Unified Foundational Ontology (UFO) and OntoUML emerged among the most adopted technologies. The catalog, publicly available at https://w3id.org/ontouml-models, currently includes over one hundred and forty models, developed in a variety of contexts and domains.

Original language	English
Article number	102210
Journal	Data & knowledge engineering
Volume	147
DOIs	https://doi.org/10.1016/j.datak.2023.102210
Publication status	Published - Sept 2023

Keywords

FAIR
Linked data
Model catalog
Ontology-driven conceptual modeling
OntoUML
Unified Foundational Ontology (UFO)

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10.1016/j.datak.2023.102210Licence: CC BY

ArticleFinal published version, 4.06 MBLicence: CC BY

Cite this

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title = "A FAIR catalog of ontology-driven conceptual models",

abstract = "Multi-domain model catalogs serve as empirical sources of knowledge and insights about specific domains, about the use of a modeling language's constructs, as well as about the patterns and anti-patterns recurrent in the models of that language crosscutting different domains. They may support domain and language learning, model reuse, knowledge discovery for humans, and reliable automated processing and analysis if built following generally accepted quality requirements for scientific data management. More specifically, not unlike scientific (meta)data, models should be shared according to the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). In this paper, we report on the construction of a FAIR model catalog for Ontology-Driven Conceptual Modeling research, a trending paradigm lying at the intersection of conceptual modeling and ontology engineering in which the Unified Foundational Ontology (UFO) and OntoUML emerged among the most adopted technologies. The catalog, publicly available at https://w3id.org/ontouml-models, currently includes over one hundred and forty models, developed in a variety of contexts and domains.",

keywords = "FAIR, Linked data, Model catalog, Ontology-driven conceptual modeling, OntoUML, Unified Foundational Ontology (UFO)",

author = "Sales, {Tiago Prince} and Barcelos, {Pedro Paulo F.} and Fonseca, {Claudenir M.} and Souza, {Isadora Valle} and Elena Romanenko and Bernab{\'e}, {C{\'e}sar Henrique} and {Bonino da Silva Santos}, {Luiz Olavo} and Mattia Fumagalli and Joshua Kritz and Almeida, {Jo{\~a}o Paulo A.} and Giancarlo Guizzardi",

note = "Funding Information: We would like to thank Accenture Israel Cybersecurity Labs for supporting this work, as well as {\'I}talo Oliveira, Thomas Derave, Tim van Ee, Cristiano Silva, and Lucas Maddalena for their contributions to the catalog. We especially thank Andr{\'a}s Kom{\'a}romi for his contribution and inspiring passion for modeling in OntoUML. C{\'e}sar H. Bernab{\'e} is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement N∘ 825575. Mattia Fumagalli is supported by the “Dense and Deep Geographic Virtual Knowledge Graphs for Visual Analysis - D2G2” project, funded by the Autonomous Province of Bolzano (CUP ID: I53C21000180003). Jo{\~a}o Paulo A. Almeida is funded by CNPq (313687/2020–0) and FAPES (281/2021, 1022/2022). Funding Information: C{\'e}sar H. Bernab{\'e} is funded by the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement 825575 . Mattia Fumagalli is supported by the “Dense and Deep Geographic Virtual Knowledge Graphs for Visual Analysis - D2G2” project, funded by the Autonomous Province of Bolzano (CUP ID: I53C21000180003 ). Jo{\~a}o Paulo A. Almeida is funded by CNPq ( 313687/2020–0 ) and FAPES ( 281/2021 , 1022/2022 ). Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

month = sep,

doi = "10.1016/j.datak.2023.102210",

language = "English",

volume = "147",

journal = "Data & knowledge engineering",

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AU - Bernabé, César Henrique

AU - Bonino da Silva Santos, Luiz Olavo

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AU - Almeida, João Paulo A.

AU - Guizzardi, Giancarlo

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N2 - Multi-domain model catalogs serve as empirical sources of knowledge and insights about specific domains, about the use of a modeling language's constructs, as well as about the patterns and anti-patterns recurrent in the models of that language crosscutting different domains. They may support domain and language learning, model reuse, knowledge discovery for humans, and reliable automated processing and analysis if built following generally accepted quality requirements for scientific data management. More specifically, not unlike scientific (meta)data, models should be shared according to the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). In this paper, we report on the construction of a FAIR model catalog for Ontology-Driven Conceptual Modeling research, a trending paradigm lying at the intersection of conceptual modeling and ontology engineering in which the Unified Foundational Ontology (UFO) and OntoUML emerged among the most adopted technologies. The catalog, publicly available at https://w3id.org/ontouml-models, currently includes over one hundred and forty models, developed in a variety of contexts and domains.

AB - Multi-domain model catalogs serve as empirical sources of knowledge and insights about specific domains, about the use of a modeling language's constructs, as well as about the patterns and anti-patterns recurrent in the models of that language crosscutting different domains. They may support domain and language learning, model reuse, knowledge discovery for humans, and reliable automated processing and analysis if built following generally accepted quality requirements for scientific data management. More specifically, not unlike scientific (meta)data, models should be shared according to the FAIR principles (Findability, Accessibility, Interoperability, and Reusability). In this paper, we report on the construction of a FAIR model catalog for Ontology-Driven Conceptual Modeling research, a trending paradigm lying at the intersection of conceptual modeling and ontology engineering in which the Unified Foundational Ontology (UFO) and OntoUML emerged among the most adopted technologies. The catalog, publicly available at https://w3id.org/ontouml-models, currently includes over one hundred and forty models, developed in a variety of contexts and domains.

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JO - Data & knowledge engineering

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A FAIR catalog of ontology-driven conceptual models

Abstract

Keywords

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