An approach for ontology development and assessment using a quality framework. Knowledge

Ontologies have been identified as important components of a number of types of information systems, including data warehouses, e-commerce systems and knowledge management systems, and the quality of such systems is therefore likely to be heavily dependent on the quality of the embedded ontology. An ontology can be studied from two perspectives; the Artificial Intelligence (AI) perspective and the philosophical perspective. The research presented in this paper takes the AI perspective in which an ontology is considered to be an engineering artefact that can be represented using a specific vocabulary. The paper describes an approach to the development, representation and evaluation of formal ontologies with the explicit aim being to develop a set of techniques that will improve the coverage of the ontology, and thus its overall quality. The proposed approach will be illustrated by applying it to the development and evaluation of an ontology for the information technology infrastructure at a university campus