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International Journal on Digital Libraries

, Volume 20, Issue 4, pp 433–452 | Cite as

Expressiveness and machine processability of Knowledge Organization Systems (KOS): an analysis of concepts and relations

  • Manolis PeponakisEmail author
  • Anna Mastora
  • Sarantos Kapidakis
  • Martin Doerr
Article

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.

Keywords

Knowledge Organization Systems (KOS) Ontologies Semantic web Computational linguistics Expressiveness Machine processability 

Notes

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Information Science and InformaticsIonian UniversityCorfuGreece
  2. 2.National Hellenic Research Foundation/National Documentation CentreAthensGreece
  3. 3.Institute of Computer ScienceFORTHHeraklionGreece

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