Insights on the Use and Application of Ontology and Conceptual Modeling Languages in Ontology-Driven Conceptual Modeling

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

2017

Abstract-In recent years, there has been a growing interest in the use of ontological theories in the philosophical sense (Foundational Ontologies) to analyze and (re)design conceptual modeling languages. This paper is about an ontologically wellfounded conceptual modeling language in this tradition, termed OntoUML. This language embeds a number of ontological patterns that reflect the micro-theories comprising a particular foundational ontology named UFO. We here (re)define OntoUML as a formal graph grammar and demonstrate how the models of this language can be constructed by the combined application of ontological patterns following a number of graph transformation rules. As a result, we obtain a version of this language fully defined as a formal Ontology Pattern Grammar. In other words, this paper presents a formal definition of OntoUML that is both explicit in terms of the ontological patterns that it incorporates and is completely independent of the UML meta-model.

Section: Discussionmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 98%

Formal Definition of a General Ontology Pattern Language using a Graph Grammar

Zambon

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

2017

“…It has been successfully employed in academic, industrial and governmental settings to create conceptual models in a number of different domains, including Geology, Biodiversity Management, Organ Donation, Petroleum Reservoir Modeling, Disaster Management, Context Modeling, Datawarehousing, Enterprise Architecture, Data Provenance, Measurement, Logistics, Complex Media Management, Telecommunications, Heart Electrophysiology, among many others [14]. In fact, research shows that it is among the most used ODCM languages in the literature [27]. Moreover, empirical evidence shows that OntoUML significantly contributes to improving the quality of conceptual models without requiring an additional effort to produce them.…”

Section: Introductionmentioning

confidence: 99%

“…UFO is an axiomatic formal theory based on contributions from Formal Ontology in Philosophy, Philosophical Logics, Cognitive Psychology, and Linguistics. A recent study shows that UFO is the second-most used foundational ontology in conceptual modeling and the one with the fastest adoption rate [27]. In the remainder of this section, we briefly explain a selected subset of the ontological distinctions put forth by the Unified Foundational Ontology (UFO).…”

Section: A Brief Introduction To Ufo and Ontoumlmentioning

confidence: 99%

Ontology-Based Model Abstraction

2019 13th International Conference on Research Challenges in Information Science (RCIS)

Figueiredo

Hedblom

et al. 2019

In recent years, there has been a growth in the use of reference conceptual models to capture information about complex and critical domains. However, as the complexity of domain increases, so does the size and complexity of the models that represent them. Over the years, different techniques for complexity management in large conceptual models have been developed. In particular, several authors have proposed different techniques for model abstraction. In this paper, we leverage on the ontologically well-founded semantics of the modeling language OntoUML to propose a novel approach for model abstraction in conceptual models. We provide a precise definition for a set of Graph-Rewriting rules that can automatically produce much-reduced versions of OntoUML models that concentrate the models' information content around the ontologically essential types in that domain, i.e., the so-called Kinds. The approach has been implemented using a model-based editor and tested over a repository of OntoUML models.

“…UFO and OntoUML have been successfully employed in academic, industrial and governmental settings to create conceptual models in a number of different domains, including Geology, Biodiversity Management, Organ Donation, Petroleum Reservoir Modeling, Disaster Management, Context Modeling, Datawarehousing, Enterprise Architecture, Data Provenance, Measurement, Logistics, Complex Media Management, Telecommunications, Heart Electrophysiology, among many others [9]. In fact, research shows that they are among the most used foundational ontology and modeling language in the ODCM literature, respectively [13]. Moreover, empirical evidence shows that OntoUML significantly contributes to improving the quality of conceptual models without requiring an additional effort to produce them.…”

Section: Introductionmentioning

confidence: 99%

Endurant Types in Ontology-Driven Conceptual Modeling: Towards OntoUML 2.0

Fonseca

Benevides

et al. 2018

Conceptual Modeling

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.