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dc.contributor.authorPeponakis, Manolisen
dc.contributor.authorMastora, Annaen
dc.contributor.authorKapidakis, Sarantosen
dc.contributor.authorDoerr, Martinen
dc.date.accessioned2020-05-19T09:57:52Z
dc.date.available2020-05-19T09:57:52Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10797/26662en
dc.descriptionΠεριέχει το πλήρες κείμενο.el_GR
dc.description.abstractThis 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.en
dc.language.isoengen
dc.sourceInternational Journal on Digital Libraries, 2019, vol. 40, n. 4, pp. 433-452.en
dc.titleExpressiveness and machine processability of Knowledge Organization Systems (KOS): an analysis of concepts and relationsen
dc.typeArticleen
dc.subject.uncontrolledtermKnowledge Organization Systems (KOS)en
dc.subject.uncontrolledtermOntologiesen
dc.subject.uncontrolledtermComputational Linguisticsen
dc.subject.uncontrolledtermExpressivenessen
dc.subject.uncontrolledtermMachine Processabilityen
dc.subject.uncontrolledtermFRSADen
dc.subject.uncontrolledtermSKOSen
dc.subject.uncontrolledtermEurovocen
dc.subject.uncontrolledtermLCSHen
dc.subject.uncontrolledtermDDCen
dc.subject.uncontrolledtermCIDOC-CRMen
dc.subject.uncontrolledtermSemantic Weben
dc.subject.JITAΔιαχείριση υπηρεσιών, λειτουργιών και τεχνικών πληροφόρησης, Γλώσσες ευρετηρίασης, διαδικασίες και σχήματαel_GR
dc.subject.JITAInformation treatment for information services, Information functions and techniques, Index languages, processes and schemes en
dc.identifier.JITAICen


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