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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.

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Abstract

The Semantic Web consists of data structured for use by computer programs, such as data sets made available under the Linked Open Data initiative. Much of this data is structured following the entity-relationship model encoded in RDF for syntactic interoperability. For semantic interoperability, the semantics of the relationships used in any given dataset needs to be made explicit. Ultimately this requires an inventory of these relationships structured around a relation ontology. This talk will outline a blueprint for such an inventory, including a format for the description/definition of binary and n-ary relations, drawing on ideas put forth in the classification and thesaurus community over the last 60 years, upper level ontologies, systems like FrameNet, the Buffalo Relation Ontology, and an analysis of linked data sets.

Source

Classification and ontology: formal approaches and access to knowledge: proceedings of the International UDC Seminar, 19-20 September 2011, The Hague, The Netherlands. Eds.: A. Slavic u. E. Civallero

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Date

3.12.2016 18:39:22

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Abstract

This study considers the expressiveness (that is the expressive power or expressivity) of different types of Knowledge Organization Systems (KOS) and discusses its potential to be machine-processable in the context of the Semantic Web. For this purpose, the theoretical foundations of KOS are reviewed based on conceptualizations introduced by the Functional Requirements for Subject Authority Data (FRSAD) and the Simple Knowledge Organization System (SKOS); natural language processing techniques are also implemented. Applying a comparative analysis, the dataset comprises a thesaurus (Eurovoc), a subject headings system (LCSH) and a classification scheme (DDC). These are compared with an ontology (CIDOC-CRM) by focusing on how they define and handle concepts and relations. It was observed that LCSH and DDC focus on the formalism of character strings (nomens) rather than on the modelling of semantics; their definition of what constitutes a concept is quite fuzzy, and they comprise a large number of complex concepts. By contrast, thesauri have a coherent definition of what constitutes a concept, and apply a systematic approach to the modelling of relations. Ontologies explicitly define diverse types of relations, and are by their nature machine-processable. The paper concludes that the potential of both the expressiveness and machine processability of each KOS is extensively regulated by its structural rules. It is harder to represent subject headings and classification schemes as semantic networks with nodes and arcs, while thesauri are more suitable for such a representation. In addition, a paradigm shift is revealed which focuses on the modelling of relations between concepts, rather than the concepts themselves.

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Source

Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a