Epistemic and normative aspects of ontologies in modelling and simulation

Abstract

In modelling and simulation, ontologies can be used for the formal definition of methods and techniques (methodological ontologies), as well as for the representation of parts of reality (referential ontologies), like manufacturing or military systems, for example. Such ontologies are two sided: they are both models of a certain body of knowledge and models for automated information processing and further implementation. The first function of ontologies as pre-images (models of) has a strong epistemic nature especially for referential ontologies since they try to capture pieces of the ‘semantic relations of the real world’. The second function as models for further processing, in contrast, is completely normative in nature—it is a specification of a ‘formal semantics’. Unfortunately, the ideal realization of ontologies as epistemic models differs from the normative ideal. As specifications, ontologies have to be as precise (unequivocal) as possible; as representations of reality, in contrast, they have to be as descriptive as possible, which may imply ambiguity and even inconsistency in some domains. Ontology processing is particularly challenging as balancing these ideals is a domain specific task. The paper scrutinizes possibilities and fundamental limits for such a balance with a focus on simulation model interoperability and ontology-driven development based on experiences with ontologies in military projects.