Evidence-based Lean Conceptual Data Modelling Languages

Multiple logic-based reconstructions of UML class diagram, Entity Relationship diagrams, and Obect-Role Model diagrams exists. They mainly cover various fragments of these Conceptual Data Modelling Languages and none are formalised such that the logic applies simultaneously for the three language families as a unifying mechanism. This hampers interchangeability, interoperability, and tooling support. In addition, due to the lack of a systematic design process of the logic used for the formalisation, hidden choices permeate the formalisations that have rendered them incompatible. We aim to address these problems, first, by structuring the logic design process in a methodological way. We generalise and extend the DSL design process to logic language design. In particular, a new phase of ontological analysis of language features is included, to apply to logic language design more generally and, in particular, by incorporating an ontological analysis of language features in the process. Second, we specify minimal logic profiles availing of this extended process, including the ontological commitments embedded in the languages, of evidence gathered of language feature usage, and of computational complexity insights from Description Logics (DL). The profiles characterise the essential logic structure needed to handle the semantics of conceptual models, therewith enabling the development of interoperability tools. No known DL language matches exactly the features of those profiles and the common core is in the tractable DL ALNI. Although hardly any inconsistencies can be derived with the profiles, it is promising for scalable runtime use of conceptual data models.