A FAIR Model Catalog for Ontology-Driven Conceptual Modeling Research

Barcelos, Pedro Paulo F.; Sales, Tiago Prince; Fumagalli, Mattia; Fonseca, Claudenir M.; Sousa, Isadora Valle; Romanenko, Elena; Kritz, Joshua; Guizzardi, Giancarlo

doi:10.1007/978-3-031-17995-2_1

Cited by 15 publications

(10 citation statements)

References 26 publications

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“…To conduct our evaluation, we needed a set of taxonomies for which the ontological categorization of its classes was known in advance. Since no such dataset existed, we built one from the models available in the FAIR Model Catalog for Ontology-Driven Conceptual Modeling Research, short-named OntoUML/UFO Catalog [19]. This opensource catalog contains ontology models grounded in UFO and in its derived conceptual modeling language, OntoUML.…”

Section: Methodsmentioning

confidence: 99%

Inferring Ontological Categories of OWL Classes Using Foundational Rules

Barcelos,

Sales,

Romanenko

et al. 2023

Frontiers in Artificial Intelligence and Applications

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Several efforts that leverage the tools of formal ontology (such as OntoClean, OntoUML, and UFO) have demonstrated the fruitfulness of considering key metaproperties of classes in ontology engineering. These metaproperties include sortality, rigidity, and external dependence, and give rise to many fine-grained ontological categories for classes, including, among others, kinds, phases, roles, mixins, etc. Despite that, it is still common practice to apply representation schemes and approaches—such as OWL—that do not benefit from identifying these ontological categories, and simplistically treat all classes in the same manner. In this paper, we propose an approach to support the automated classification of classes into the ontological categories underlying the (g)UFO foundational ontology. We propose a set of inference rules derived from (g)UFO’s axiomatization that, given an initial classification of the classes in an OWL ontology, can support the inference of the classification for the remaining classes in the ontology. We formalize these rules, implement them in a computational tool and assess them against a catalog of ontologies designed by a variety of users for a number of domains.

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Section: Methodsmentioning

confidence: 99%

Inferring Ontological Categories of OWL Classes Using Foundational Rules

Barcelos,

Sales,

Romanenko

et al. 2023

Frontiers in Artificial Intelligence and Applications

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“…In addition to the formal specification and automated proofs for the flattening and lifting operations, we have performed a number of tests on the implemented transformation. We employed in the tests the first 30 projects published in the OntoUML repository (Barcelos et al, 2022), which are OntoUML plugin was developed to facilitate the development of OntoUML models and verifies its compliance with OntoUML's syntactical rules (see Guizzardi et al, for more details), among other features.…”

Section: Implementation and Testsmentioning

confidence: 99%

“…Section 4 shows how we instrument the transformation process by maintaining a set of traces that are updated in each flattening and lifting application; these traces are ultimately used to generate triggers in the database that reflect the constraints that are required by each step in the transformation process; the automatically-generated triggers accumulate all the required constraints. Section 5 reports on the implementation of the tool and on the tests that were performed to validate the approach, using models made available in an open model repository (Barcelos et al, 2022). Section 6 discusses related work, and, finally, Section 7 presents concluding remarks.…”

mentioning

confidence: 99%

Preserving conceptual model semantics in the forward engineering of relational schemas

Guidoni¹,

Almeida²,

Guizzardi³

2022

Front. Comput. Sci.

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Forward engineering relational schemas based on conceptual models (in languages such as UML and ER) is an established practice, with several automated transformation approaches discussed in the literature and implemented in production tools. These transformations must bridge the gap between the primitives offered by conceptual modeling languages on the one hand and the relational model on the other. As a result, it is often the case that some of the semantics of the source conceptual model is lost in the transformation process. In this paper, we address this problem by forward engineering additional constraints along with the transformed schema (ultimately implemented as triggers). We formulate our approach in terms of the operations of “flattening” and “lifting” of classes to make our approach largely independent of the particular transformation strategy (one table per hierarchy, one table per class, one table per concrete class, one table per leaf class, etc.). An automated transformation tool is provided that traces the cumulative consequences of the operations as they are applied throughout the transformation process. We report on tests of this tool using models published in an open model repository.

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“…The authors group the ontologies' characterization eorts into ve main lines: domain/task t, error checking, libraries, metrics, and modularization. Already the OntoUML/UFO Catalog 6 initiative [14] provides an open solution for ontology metadata availability. All those eorts target ontology as artifacts, pointing to the ontology engineers' eyes and how they perceive the conceptualizations.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, properties such as the ones related to the ontology and their data Findability and Availability are covered by the notions present in the FAIR Principles [254]. Well-controlled ontology catalogs [14], ontologies such as [22], data models such as [203], and proposals such as [50,211] are good initiatives in this direction.…”

Section: Ontology Propertiesmentioning

confidence: 99%

A Framework for Conceptual Characterization of Ontologies and its Application in the Cybersecurity Domain

Franco Martins Souza

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This thesis was a great personal challenge for me and my family. We have changed house, country, and continent, building a new life full of challenges and new things. Along the way, we have left many dear people behind. But with a lot of study, perseverance, and the help of many people, we have made it. I would like to express my sincere thanks to all of them. I begin by expressing my gratitude to my advisor, Óscar Pastor López, who guided me along this path of study and research. It was years of great learning with him, I thank him for sharing his immense knowledge with me and for his support, patience, and dedication. More than a professor, he is an example to be followed, with a big sense of humor; always focused, and communicative, he supported me on this path. Thank you for accepting me on this journey as my advisor, but more for being my friend.Thanks to José Fabián Reyes Román, my co-advisor who also helped me during all the research and for reviewing the preliminary version of this thesis. I am grateful to my colleagues from the Accenture Israel Cyber R&D Lab (Moshe Hadad, Dan Klein, Gal Engelberg, and Ethan Hadar) who helped with their immense knowledge in cybersecurity. Thanks to my dear old friends and Prof. Renata Guizzardi and Prof. Giancarlo Guizzardi for their valuable advice and support during the course of this research work. Also, thanks to my colleagues Bruno Duarte Borlini and Cristine Grio for the countless philosophical and ontological discussions that opened me to new possibilities.Thanks to Vicente Javier Julian Inglada of DSIC, Ana Cidad Vila of ValgrAI, ix Prof. José Ignacio Panach Navarrete, and the other PROS@VRAIN team members and colleagues. For all of you, who believed in me, especially when I was weakest and thought that the end never to come.Besides my advisors and research team, I thank my thesis committee Prof.

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A FAIR Model Catalog for Ontology-Driven Conceptual Modeling Research

Cited by 15 publications

References 26 publications

Inferring Ontological Categories of OWL Classes Using Foundational Rules

Inferring Ontological Categories of OWL Classes Using Foundational Rules

Preserving conceptual model semantics in the forward engineering of relational schemas

A Framework for Conceptual Characterization of Ontologies and its Application in the Cybersecurity Domain

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