Search (7 results, page 1 of 1)

  • × theme_ss:"Semantische Interoperabilität"
  • × type_ss:"a"
  • × year_i:[2020 TO 2030}
  1. Hider, P.; Coe, M.: Academic disciplines in the context of library classification : mapping university faculty structures to the DDC and LCC schemes (2022) 0.00 
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    Date
    29. 9.2022 17:15:48
  2. Candela, G.: ¬An automatic data quality approach to assess semantic data from cultural heritage institutions (2023) 0.00 
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    Date
    22. 6.2023 18:23:31
  3. Marcondes, C.H.: Towards a vocabulary to implement culturally relevant relationships between digital collections in heritage institutions (2020) 0.00 
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    Date
    4. 3.2020 14:22:41
  4. Rocha Souza, R.; Lemos, D.: a comparative analysis : Knowledge organization systems for the representation of multimedia resources on the Web (2020) 0.00 
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  5. Smith, A.: Simple Knowledge Organization System (SKOS) (2022) 0.00 
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    Abstract
    SKOS (Simple Knowledge Organization System) is a recommendation from the World Wide Web Consortium (W3C) for representing controlled vocabularies, taxonomies, thesauri, classifications, and similar systems for organizing and indexing information as linked data elements in the Semantic Web, using the Resource Description Framework (RDF). The SKOS data model is centered on "concepts", which can have preferred and alternate labels in any language as well as other metadata, and which are identified by addresses on the World Wide Web (URIs). Concepts are grouped into hierarchies through "broader" and "narrower" relations, with "top concepts" at the broadest conceptual level. Concepts are also organized into "concept schemes", also identified by URIs. Other relations, mappings, and groupings are also supported. This article discusses the history of the development of SKOS and provides notes on adoption, uses, and limitations.
  6. Binding, C.; Gnoli, C.; Tudhope, D.: Migrating a complex classification scheme to the semantic web : expressing the Integrative Levels Classification using SKOS RDF (2021) 0.00 
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    Abstract
    Purpose The Integrative Levels Classification (ILC) is a comprehensive "freely faceted" knowledge organization system not previously expressed as SKOS (Simple Knowledge Organization System). This paper reports and reflects on work converting the ILC to SKOS representation. Design/methodology/approach The design of the ILC representation and the various steps in the conversion to SKOS are described and located within the context of previous work considering the representation of complex classification schemes in SKOS. Various issues and trade-offs emerging from the conversion are discussed. The conversion implementation employed the STELETO transformation tool. Findings The ILC conversion captures some of the ILC facet structure by a limited extension beyond the SKOS standard. SPARQL examples illustrate how this extension could be used to create faceted, compound descriptors when indexing or cataloguing. Basic query patterns are provided that might underpin search systems. Possible routes for reducing complexity are discussed. Originality/value Complex classification schemes, such as the ILC, have features which are not straight forward to represent in SKOS and which extend beyond the functionality of the SKOS standard. The ILC's facet indicators are modelled as rdf:Property sub-hierarchies that accompany the SKOS RDF statements. The ILC's top-level fundamental facet relationships are modelled by extensions of the associative relationship - specialised sub-properties of skos:related. An approach for representing faceted compound descriptions in ILC and other faceted classification schemes is proposed.
  7. Cheng, Y.-Y.; Xia, Y.: ¬A systematic review of methods for aligning, mapping, merging taxonomies in information sciences (2023) 0.00 
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    Abstract
    The purpose of this study is to provide a systematic literature review on taxonomy alignment methods in information science to explore the common research pipeline and characteristics. Design/methodology/approach The authors implement a five-step systematic literature review process relating to taxonomy alignment. They take on a knowledge organization system (KOS) perspective, and specifically examining the level of KOS on "taxonomies." Findings They synthesize the matching dimensions of 28 taxonomy alignment studies in terms of the taxonomy input, approach and output. In the input dimension, they develop three characteristics: tree shapes, variable names and symmetry; for approach: methodology, unit of matching, comparison type and relation type; for output: the number of merged solutions and whether original taxonomies are preserved in the solutions. Research limitations/implications The main research implications of this study are threefold: (1) to enhance the understanding of the characteristics of a taxonomy alignment work; (2) to provide a novel categorization of taxonomy alignment approaches into natural language processing approach, logic-based approach and heuristic-based approach; (3) to provide a methodological guideline on the must-include characteristics for future taxonomy alignment research. Originality/value There is no existing comprehensive review on the alignment of "taxonomies". Further, no other mapping survey research has discussed the comparison from a KOS perspective. Using a KOS lens is critical in understanding the broader picture of what other similar systems of organizations are, and enables us to define taxonomies more precisely.

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