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

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

A comparative illustration of foundational ontologies : BORO and UFO

This paper investigates the differences that exist between a 3D and a 4D ontology. We examine these differences by comparing both ontologies through the metaphysical choices each ontology makes and explore the composing characteristics that define them. More specifically, the differences between the ontologies were illustrated through several modeling fragments that were derived from a modeling case presented at the 5thOntoCom workshop. Each of these modeling fragments focused on the metaphysical choices that the ontologies make –Essence and Identity, Relationships and Time. These comparisons highlighted the different ontological approaches and structures that exist between the ontologies. Moreover, depending on the ontology, the resulting conceptual model could differ substantially, confirming the impact and importance of the choice of a certain ontology. The observed differences between both ontologies eventually led us to formulate three discussion points that question the applicability of certain metaphysical choices in certain circumstances, and that can serve as a basis for future discussion or future research studies in the domain of ODCM

Reification and Truthmaking Patterns

Reification is a standard technique in conceptual modeling, which consists of including in the domain of discourse entities that may otherwise be hidden or implicit. However, deciding what should be rei- fied is not always easy. Recent work on formal ontology offers us a simple answer: put in the domain of discourse those entities that are responsible for the (alleged) truth of our propositions. These are called truthmakers. Re-visiting previous work, we propose in this paper a systematic analysis of truthmaking patterns for properties and relations based on the ontolog- ical nature of their truthmakers. Truthmaking patterns will be presented as generalization of reification patterns, accounting for the fact that, in some cases, we do not reify a property or a relationship directly, but we rather reify its truthmakers

Processes endure, whereas events occur

In this essay, we aim to help clarify the nature of so-called 'occurrences' by attributing distinct modes of existence and persistence to processes and events. In doing so, we break with the perdurantism claimed by DOLCE’s authors and we distance ourselves from mereological analyzes like those recently conducted by Guarino to distinguish between 'processes' and 'episodes'. In line with the works of Stout and Galton, we first bring closer (physical) processes and objects in their way of enduring by proposing for processes a notion of dynamic presence (contrasting with a static presence for objects). Then, on the events side, we attribute to them the status of abstract entities by identifying them with objects of thought (by individual and collective subjects), and this allows us to distinguish for themselves between existence and occurrence. We therefore identify them with psychological (or even social) endurants, which may contingently occur

Semantic interoperability: ontological unpacking of a viral conceptual model

Background. Genomics and virology are unquestionably important, but complex, domains being investigated by a large number of scientists. The need to facilitate and support work within these domains requires sharing of databases, although it is often difficult to do so because of the different ways in which data is represented across the databases. To foster semantic interoperability, models are needed that provide a deep understanding and interpretation of the concepts in a domain, so that the data can be consistently interpreted among researchers. Results. In this research, we propose the use of conceptual models to support semantic interoperability among databases and assess their ontological clarity to support their effective use. This modeling effort is illustrated by its application to the Viral Conceptual Model (VCM) that captures and represents the sequencing of viruses, inspired by the need to understand the genomic aspects of the virus responsible for COVID-19. For achieving semantic clarity on the VCM, we leverage the “ontological unpacking” method, a process of ontological analysis that reveals the ontological foundation of the information that is represented in a conceptual model. This is accomplished by applying the stereotypes of the OntoUML ontology-driven conceptual modeling language.As a result, we propose a new OntoVCM, an ontologically grounded model, based on the initial VCM, but with guaranteed interoperability among the data sources that employ it. Conclusions. We propose and illustrate how the unpacking of the Viral Conceptual Model resolves several issues related to semantic interoperability, the importance of which is recognized by the “I” in FAIR principles. The research addresses conceptual uncertainty within the domain of SARS-CoV-2 data and knowledge.The method employed provides the basis for further analyses of complex models currently used in life science applications, but lacking ontological grounding, subsequently hindering the interoperability needed for scientists to progress their research

Applying the UFO Ontology to Design an Agent-Oriented Engineering Language

Abstract. The problem of designing suitable conceptual modeling languages for system engineering is far from being solved. In the past years, some works have proposed the use of foundational ontologies as analysis tools to enable semantic coherence when (re)designing such languages. In this paper, we exemplify this approach by applying a foundational ontology named UFO in the design of an agent-oriented modeling language for the ARKnowD methodology. Instead of proposing new concepts and constructs, ARKnowD relies on existing work, combining two different approaches, namely Tropos and AORML. Each work is applied in a different development activity, according to their natural propensity: Tropos in Requirements Analysis and AORML in System Design. Besides the ontological approach, we propose some mapping rules between the notations, inspired in the Model Driven Architecture (MDA) metamodel transformation method. This approach helps to guarantee a smooth transition from one activity to the other

Types and taxonomic structures in conceptual modeling: A novel ontological theory and engineering support

Types are fundamental for conceptual modeling and knowledge representation, being an essential construct in all major modeling languages in these fields. Despite that, from an ontological and cognitive point of view, there has been a lack of theoretical support for precisely defining a consensual view on types. As a consequence, there has been a lack of precise methodological support for users when choosing the best way to model general terms representing types that appear in a domain, and for building sound taxonomic structures involving them. 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. At the core of this enterprise, there has been a theory of types specially designed to address these issues. This theory is ontologically well- founded, psychologically informed, and formally characterized. These results have led to the development of a Conceptual Modelling language dubbed OntoUML, reflecting the ontological micro-theories comprising UFO. Over the years, UFO and OntoUML have been successfully employed on conceptual model design in a variety of domains including academic, industrial, and governmental settings. These experiences exposed improvement opportunities for both the OntoUML language and its underlying theory, UFO. In this paper, we revise the theory of types in UFO in response to empirical evidence. The new version of this theory shows that many of OntoUML’s meta-types (e.g. kind, role, phase, mixin) 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 with a formal characterization of this fragment of the theory, which is then used to advance a new metamodel for OntoUML (termed OntoUML 2). To demonstrate that the benefits of this approach are extended beyond OntoUML, the proposed formal theory is then employed to support the definition of UFO-based lightweight Semantic Web ontologies with ontological constraint checking in OWL. Additionally, we report on empirical evidence from the literature, mainly from cognitive psychology but also from linguistics, supporting some of the key claims made by this theory. Finally, we propose a computational support for this updated metamodel