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Abstract

Ontologies are increasingly seen as a new type of knowledge organization system (KOS) besides traditional ones such as classification schemes or thesauri. Consequently, there are efforts to compare them with and map them to other KOS. This paper argues that only ontologies for reality representation are useful subjects of such comparisons and mappings. These ontologies are difficult to distinguish from other "data modelling" - types of ontology, since both can be represented through the popular Web Ontology Language (OWL). Data modelling ontologies such as Simple Knowledge Organization Systems (SKOS) are useful instruments for establishing interoperability between KOS in the sense of publishing and accessing data and data models in a uniform way as well as for relating them to each other. Discriminating these two understandings of ontologies particularly supports comparisons and mappings between traditional KOS and ontologies. In practice, such efforts are still impeded by the absence of standards or guidelines for vocabulary control in ontologies. Moreover, this paper emphasizes that methods for constructing and evaluating reality representation ontologies can be useful to re-engineer traditional KOS. This makes them become more interoperable in the sense of combinable, but also more useful in the sense of improving search expansion results and reusable for different purposes.

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Abstract

Thesauri and other types of controlled vocabularies are increasingly re-engineered into ontologies described using the Web Ontology Language (OWL), particularly in the life sciences. This has led to the perception by some that thesauri are ontologies once they are described by using the syntax of OWL while others have emphasized the need to re-engineer a vocabulary to use it as ontology. This confusion is rooted in different perceptions of what ontologies are and how they differ from other types of vocabularies. In this article, we rigorously examine the structural differences and similarities between thesauri and meaning-defining ontologies described in OWL. Specifically, we conduct (a) a conceptual comparison of thesauri and ontologies, and (b) a comparison of a specific thesaurus and a specific ontology in the same subject field. Our results show that thesauri and ontologies need to be treated as 2 orthogonal kinds of models with superficially similar structures. An ontology is not a good thesaurus, nor is a thesaurus a good ontology. A thesaurus requires significant structural and other content changes to become an ontology, and vice versa.