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

Deductive reconstruction of MLT* for multi-level modeling

In the last two decades, about a dozen proposals were made to extend object-oriented modeling by multiple abstraction levels. One group of proposals designates explicit levels to objects and classes. The second group uses the powertype pattern to implicitly establish levels. From this group, we consider two proposals, DeepTelos and MLT*. Both have been defined via axioms and both give a central role to the powertype pattern. In this paper, we reconstruct MLT* with the deductive axiomatization style used for DeepTelos. The resulting specification is executed in a deductive database to check MLT* multi-level models for errors and complete them with derived facts that do not have to be explicitly asserted by modelers. This leverages the rich rules of MLT* with the deductive approach underlying DeepTelos. The effort also allows us to clearly establish the relation between DeepTelos and MLT*, in an attempt to clarify the relations between approaches in this research domain. As a byproduct, we supply MLT-Telos as a fully operational deductive implementation of MLT* to the research community.For copyright information, see attached file.</p