OntoClean

Abstract: OntoClean is a methodology for validating the ontological adequacy and logical consistency of taxonomic relationships. It is based on highly general ontological notions drawn from philosophy, like essence, identity, and unity, which are used to elicit and characterize the intended meaning of properties, classes, and relations making up an ontology. These aspects are represented by formal metaproperties, which impose several constraints on the taxonomic relationships between concepts. The analysis of these constraints helps in evaluating and validating the choices made. In this chapter we present an informal overview of the philosophical notions involved and their role in OntoClean, review some common ontological pitfalls, and walk through the example that has appeared in pieces in previous papers and has been the basis of numerous tutorials and talks.

Abstract: This article studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of developing information systems A mapping algorithm has been proposed and embedded in a special purpose transformation engine to generate a conceptual data model from a given domain ontology Both quantitative and qualitative methods have been adopted to critically evaluate this new approach In addition, this article focuses on evaluating the quality of the generated conceptual data model elements using Bunge-Wand-Weber and OntoClean ontologies The results of this evaluation indicate that the generated conceptual data model provides a high degree of accuracy in identifying the substantial domain entities, along with their relationships being derived from the consensual semantics of domain knowledge The results are encouraging and support the potential role that this approach can take part in the process of information system development

Abstract: In this paper we propose an analysis and an upgrade of WordNet's top-level synset taxonomy. We briefly review WordNet and identify its main semantic limitations. Some principles from a forthcoming OntoClean methodology are applied to the ontological analysis of WordNet. A revised top-level taxonomy is proposed, which is meant to be more conceptually rigorous, cognitively transparent, and efficiently exploitable in several applications.

Abstract: OntoClean is a unique approach towards the formal evaluation of ontologies, as it analyses the intensional content of concepts. Although it is well documented in numerous publications, and its importance is widely acknowledged, it is still used rather infrequently due to the high costs for applying OntoClean, especially on tagging concepts with the correct meta-properties. In order to facilitate the use of OntoClean and to enable proper evaluation of it in real-world cases, we provide AEON , a tool which automatically tags concepts with appropriate OntoClean meta-properties. The implementation can be easily expanded to check the concepts for other abstract meta-properties, thus providing for the first time tool support in order to enable intensional ontology evaluation for concepts. Our main idea is using the web as an embodiment of objective world knowledge, where we search for patterns indicating concepts meta-properties. We get an automatic tagging of the ontology, thus reducing costs tremendously. Moreover, AEON lowers the risk of having subjective taggings. As part of the evaluation we report our experiences from creating a middle-sized OntoClean-tagged reference ontology.