Philosophical Scrutiny for Run-Time Support of Application Ontology Development

The development and maintenance of domain-specific application ontologies require knowledge input from domain experts who are usually without any formal ontology or AI background. When dealing with large-scale ontologies, for example of the kind with which we are currently familiar in the biomedical spheres, quality assurance becomes important in minimizing modelling mistakes and the application errors which they bring in their wake. In this paper we describe how the upper-level framework BFO (for: Basic Formal Ontology), developed by the Institute for Formal Ontology and Medical Information Science, is being used to provide automatic error detection and run-time modelling support to the development of LinKBase®, a large-scale medical domain ontology developed by Language and Computing NV to serve a range of natural language processing applications.