Using the Unified Foundational Ontology (UFO) as a Foundation for General Conceptual Modeling Languages

Abstract

Abstract. In recent years, there has been a growing interest in approaches that employ ontological models as theoretical tools for analyzing and improving conceptual modeling languages. In this paper we present a philosophically and cognitively well-founded formal ontology which has been developed with the special purpose of serving as a foundation for general conceptual modeling languages. Furthermore, we demonstrate how this foundational ontology named the Unified Foundational Ontology (UFO) has been used to evaluate and redesign the metamodel of the Unified Modeling Language (UML) for the purpose of conceptual modeling.

Toward an Ontology-Driven Unifying Metamodel for UML Class Diagrams, EER, and ORM2

“…Comparing the languages through their metamodels (in ORM) highlighting their differences [18] is a useful step before unifying them. The Unifying Foundational Ontology (UFO) focuses on the philosophical aspects of conceptual modelling and has been applied to extend the UML 2.0 metamodel with more specific entities, such as a Sortal Class [15,17]. Their ontological analysis of, among others, the nature of UML's class and association did not translate into a revised metamodel specification, however.…”

The Foundational Ontology Library ROMULUS

“…BFO is an ontology of universals, which has, Independent Continuant (alike Endurant), Process, and Fiat Object Part. UFO [3] and GFO [7] are ontologies of particulars and universals: one of the first distinctions in the hierarchy is between Particular/Individual and Universal, where the former subsumes, among others, gfo:Presential, gfo:Role, ufo:Set, and ufo:Quality, and the latter gfo:Persistant and ufo:RigidSortal. Does it matter for conceptual data modelling?…”

“…It has been 15 years since the introduction of the notion of ontology-driven information systems [1], which entails ontology-driven conceptual data modelling [2][3][4][5]. Ontology-driven conceptual data modelling uses principles and solutions from Ontology (philosophy) and ontologies (as artifacts) to improve the quality of a conceptual data model and refine its language, which therewith improves the quality of the information system.…”

“…Ontology-driven conceptual data modelling uses principles and solutions from Ontology (philosophy) and ontologies (as artifacts) to improve the quality of a conceptual data model and refine its language, which therewith improves the quality of the information system. This can be applied to individual aspects by devising solutions to modelling problems in conceptual data models-e.g., part whole relations in conceptual models, aided by a foundational ontology [4]-as well as more broadly to modify a conceptual data modelling language's metamodel thanks to a foundational ontology (e.g., [3]). However, one solution or extension may use, say, the DOLCE foundational ontology [6] for refining UML's aggregation association [4], another could be informed by the UFO foundational ontology [3], and yet another by GFO [7], but it is not clear whether DOLCE, UFO, and GFO are compatible.…”

“…This can be applied to individual aspects by devising solutions to modelling problems in conceptual data models-e.g., part whole relations in conceptual models, aided by a foundational ontology [4]-as well as more broadly to modify a conceptual data modelling language's metamodel thanks to a foundational ontology (e.g., [3]). However, one solution or extension may use, say, the DOLCE foundational ontology [6] for refining UML's aggregation association [4], another could be informed by the UFO foundational ontology [3], and yet another by GFO [7], but it is not clear whether DOLCE, UFO, and GFO are compatible. Proliferation of modelling improvements, then, end up to be incompatible if the improvements rest on different philosophical assumptions represented in different foundational ontologies.…”