Towards ontological foundations for agent modeling concepts using UFO

Foundational ontologies provide the basic concepts upon which any domain-specific ontology is built. This paper presents a new foundational ontology, UFO, and shows how it can be used as a foundation of agent concepts and for evaluating agent-oriented modeling methods. UFO is derived from a synthesis of two other foundational ontologies, GFO/GOL and OntoClean/DOLCE. While their main areas of application are the natural sciences and linguistics/cognitive engineering, respectively, the main purpose of UFO is to provide a foundation for conceptual modeling, including agentoriented modeling

Ontological foundations for structural conceptual models

In this thesis, we aim at contributing to the theory of conceptual modeling and ontology representation. Our main objective here is to provide ontological foundations for the most fundamental concepts in conceptual modeling. These foundations comprise a number of ontological theories, which are built on established work on philosophical ontology, cognitive psychology, philosophy of language and linguistics. Together these theories amount to a system of categories and formal relations known as a foundational ontolog

Ontology, Ontologies and the "I" of FAIR

According to the FAIR guiding principles, one of the central attributes for maximizing the added value of information artifacts is interoperability. In this paper, I discuss the importance, and propose a characterization of the notion of Semantic Interoperability. Moreover, I show that a direct consequence of this view is that Semantic Interoperability cannot be achieved without the support of, on one hand, (i) ontologies, as meaning contracts capturing the conceptualizations represented in information artifacts and, on the other hand, of (ii) Ontology, as a discipline proposing formal meth- ods and theories for clarifying these conceptualizations and articulating their representations. In particular, I discuss the fundamental role of formal ontological theories (in the latter sense) to properly ground the construction of representation languages, as well as methodological and computational tools for supporting the engineering of ontologies (in the former sense) in the context of FAIR

A formal theory of conceptual modeling universals

Conceptual Modeling is a discipline of great relevance to several areas in Computer Science. In a series of papers [1,2,3] we have been using the General Ontological Language (GOL) and its underlying upper level ontology, proposed in [4,5], to evaluate the ontological correctness of conceptual models and to develop guidelines for how the constructs of a modeling language (UML) should be used in conceptual modeling. In this paper, we focus on the modeling metaconcepts of classifiers and objects from an ontological point of view. We use a philosophically and psychologically well-founded theory of universals to propose a UML profile for Ontology Representation and Conceptual Modeling. The formal semantics of the proposed modeling elements is presented in a language of modal logics with quantification restricted to Sortal universals

Processes as variable embodiments

In a number of papers, Kit Fine introduced a theory of embodiment which distinguishes between rigid and variable embodiments, and has been successfully applied to clarify the ontological nature of entities whose parts may or may not vary in time. In particular, he has applied this theory to describe a process such as the erosion of a cliff, which would be a variable embodiment whose manifestations are the different statesof erosion of the cliff. We find this theory very powerful, and especially appropriate to capture the intuition that the same process may go on at different times. However, its formal principles have been subject to some criticisms, mainly concerning the mereological structure of a variable embodiment. Moreover, since the notion of variable embodiment is very general, simply saying that processes are variable embodiments is not enough to understand their ontological nature. To address these concerns, in this paper we proceed in two phases: first, we propose a revised version of Fine’s original theory adapted to the case of processes, which adopts a classical mereology instead of Fine’s hylomorphic mereology, and a temporalized constitution relation in place of Fine’s function of variable embodiment; second, we go deeper into the ontologicalnature of processes by revisiting the notions of homogeneity, intentionality, and telicity discussed in the literature, and propose an account based on ontological principles and not on semantic properties of predicates. This allows us to organize processes into a novel taxonomy based exclusively on their unity and individuation principles

In the Defense of Ontological Foundations for Conceptual Modeling

Abstract not available

Semantics, Ontology and Explanation

The terms 'semantics' and 'ontology' are increasingly appearing together with 'explanation', not only in the scientific literature, but also in organizational communication. However, all of these terms are also being significantly overloaded. In this paper, we discuss their strong relation under particular interpretations. Specifically, we discuss a notion of explanation termed ontological unpacking, which aims at explaining symbolic domain descriptions (conceptual models, knowledge graphs, logical specifications) by revealing their ontological commitment in terms of their assumed truthmakers, i.e., the entities in one's ontology that make the propositions in those descriptions true. To illustrate this idea, we employ an ontological theory of relations to explain (by revealing the hidden semantics of) a very simple symbolic model encoded in the standard modeling language UML. We also discuss the essential role played by ontology-driven conceptual models (resulting from this form of explanation processes) in properly supporting semantic interoperability tasks. Finally, we discuss the relation between ontological unpacking and other forms of explanation in philosophy and science, as well as in the area of Artificial Intelligence

Using a foundational ontology to investigate the semantics behind the concepts of the i* language

In the past few years, the community that develops i* has become aware of the problem of having so many variants, since it makes it difficult for newcomers to learn how to use the language and even to experts to efficiently exchange knowledge and disseminate their proposals. Moreover, this problem also delays the transfer of the i* framework to industrial settings. Our work is one of the current attempts to promote interoperability among the existing variants, and it does that by investigating the semantics behind the i* core concepts. For that, we apply a foundational ontology named UFO, which is used as a semantically coherent reference model to which the language should be isomorphic. In this paper, we report on the steps we have pursued, what we have accomplished so far, also setting the context for the work ahead

On the Multiple Roles of Ontologies in Explainable AI

This paper discusses the different roles that explicit knowledge, in particular ontologies, can play in Explainable AI and in the development of human-centric explainable systems and intelligible explanations. We consider three main perspectives in which ontologies can contribute significantly, namely reference modelling, common-sense reasoning, and knowledge refinement and complexity management. We overview some of the existing approaches in the literature, and we position them according to these three proposed perspectives. The paper concludes by discussing what challenges still need to be addressed to enable ontology-based approaches to explanation and to evaluate their human-understandability and effectiveness