Using a trope-based foundational ontology for bridging different areas of concern in ontology-driven conceptual modeling

• We present a foundational ontology for conceptual modeling.
• We present a formal characterization of this ontology.
• We discuss a conceptual modeling language founded on this ontology (OntoUML).
• We provide mapping directives bridging OntoUML and the semantic web language OWL.
• We discuss computational support for model building, transformation and manipulation.

In recent years, ontology-driven reference models have gained much attention in the literature due to their potential key role in activities such as complex information modeling and semantic interoperability. The engineering process of these conceptual models should account for different phases addressing different areas of concern. In an initial phase of conceptual domain modeling, the target modeling artifacts should be constructed with the goal of maximizing quality attributes such as expressivity and truthfulness to the represented domain in reality. In a subsequent development phase, the resulting domain models can be used to guide the design decisions in the construction of different implementation artifacts addressing different computational concerns. In this paper, we present a philosophically sound, cognitively-oriented and formally characterized foundational theory of objects and tropes (property-instances). Moreover, we use this theory to bring about engineering contributions to both the aforementioned phases of ontology-driven conceptual modeling. Firstly, we show how this theory has been used to (re)design a system of modeling primitives underlying the conceptual domain modeling language OntoUML. Furthermore, we provide precise directives on how to map conceptual domain models in this language to their implementation in less-expressive computationally-oriented codification languages. In particular, we address here a mapping strategy to OWL (Web Ontology Language) that partially preserves the modal-temporal semantics of OntoUML. Finally, we discuss computational support for the proposed approach in terms of conceptual model construction, automatic transformation and temporal querying.