Abstract
For over a decade now, a community of researchers has contributed to the development of the Unified Foundational Ontology (UFO) - aimed at providing foundations for all major conceptual modeling constructs. This ontology has led to the development of an Ontology-Driven Conceptual Modeling language dubbed OntoUML, reflecting the ontological micro-theories comprising UFO. Over the years, UFO and OntoUML have been successfully employed in a number of academic, industrial and governmental settings to create conceptual models in a variety of different domains. These experiences have pointed out to opportunities of improvement not only to the language itself but also to its underlying theory. In this paper, we take the first step in that direction by revising the theory of types in UFO in response to empirical evidence. The new version of this theory shows that many of the meta-types present in OntoUML (differentiating Kinds, Roles, Phases, Mixins, etc.) should be considered not as restricted to Substantial types but instead should be applied to model Endurant Types in general, including Relator types, Quality types and Mode types. We also contribute a formal characterization of this fragment of the theory, which is then used to advance a metamodel for OntoUML 2.0. Finally, we propose a computational support tool implementing this updated metamodel.
Keywords
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- 1.
Several dozens of these models are available at http://www.menthor.net/.
- 2.
For the formal specification, see https://github.com/nemo-ufes/ufo-types.
- 3.
The OntoUML plug-in for Visual Paradigm is available at https://github.com/nemo-ufes/OntoUML-2.0-for-Visual-Paradigm.
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Acknowledgments
We thank Nicola Guarino for the fruitful discussions; and CNPq, CAPES, and FAPES for funding. The third author was supported by the grant No 71024352.
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Guizzardi, G., Fonseca, C.M., Benevides, A.B., Almeida, J.P.A., Porello, D., Sales, T.P. (2018). Endurant Types in Ontology-Driven Conceptual Modeling: Towards OntoUML 2.0. In: Trujillo, J., et al. Conceptual Modeling. ER 2018. Lecture Notes in Computer Science(), vol 11157. Springer, Cham. https://doi.org/10.1007/978-3-030-00847-5_12
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