Ontological Approaches to Model Engineering Qualities and Values in DOLCE OWL

Abstract

Ontologies are gaining popularity in engineering applications as a conceptual tool for sharing information and knowledge between experts and software systems. However, most communities tend to focus on their own ontology, which is optimized for a limited set of tasks, resulting in models that are difficult to integrate with each other. This article explores how starting from a foundational ontology can enhance the quality of domain ontologies and improve their interoperability. To this end, we analyze the structure of Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) OWL and investigate how it can be enriched for use in an engineering context. Our focus is on representing qualities and their values, particularly quantitative ones, which are crucial in engineering but often inadequately addressed by top-level ontologies. We propose various approaches for incorporating quantitative values, highlighting their pros and cons, and comparing them with other works present in the literature. The aim of the article is to enhance the usability of the foundational ontology DOLCE in practical engineering contexts, allowing engineers to concentrate on domain-specific aspects rather than the complexities of ontology usage.