Modeling classification systems in SKOS: some challenges and best-practice recommendations

Authors:
Michael Panzer;Marcia Lei Zeng
Affiliations:
OCLC;Kent State University
Venue:
DCMI '09 Proceedings of the 2009 International Conference on Dublin Core and Metadata Applications
Year:
2009

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Abstract

Representing classification systems on the web for publication and exchange continues to be a challenge within the SKOS framework. This paper focuses on the differences between classification schemes and other families of KOS (knowledge organization systems) that make it difficult to express classifications without sacrificing a large amount of their semantic richness. Issues resulting from the specific set of relationships between classes and topics that defines the basic nature of any classification system are discussed. Where possible, different solutions within the frameworks of SKOS and OWL are proposed and examined.