Reusing Certain Database Design Principles, Methods and Techniques for Ontology Theory, Construction and Methodology

Formal ontologies can be seen as mathematical objects that form the range of a classical "Tarskian" semantics interpretation mapping of first-order language constructs that could represent situations, functions or procedures related to a given domain. In this paper we try to identify some of the theoretical and practical issues that result from this view, in particular concerning the problems of definition, representation, organization of ontologies, and methodologies for their construction and maintenance. We identify and discuss a number of the critical success factors for the “ontologization” of IT, namely large standardized ontological resources (ontobases), the so-called Semantic Web, and methodological, teachable approaches. Some design methods and techniques such as view integration that were originally developed for large databases, where the "data models" and their semantics typically are limited to a particular application, could be relevant for this purpose, and we analyze parallelisms and fundamental differences between databases and ontologies. In particular the ORM (Object-Role Modeling) method, or rather its precursor NIAM, with its rigorous distinction and handling of so-called lexical and non-lexical knowledge proved to be an interesting candidate to help identify and clarify a number of these issues, and a number of examples are given. In this paper we report on research within STARLab’s DOGMA Project that indicates how such methods may or must be adapted to be usable in the context of ontologies, and how they may then help to define ontology updates, the role of domain constraints, and future tools that assist in e.g. the alignment of ontologies.