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  • 标题:Represent Changes of Knowledge Organization Systems on the Semantic Web
  • 本地全文:下载
  • 作者:Qing Zou
  • 期刊名称:International Journal of Librarianship (IJoL)
  • 电子版ISSN:2474-3542
  • 出版年度:2018
  • 卷号:3
  • 期号:1
  • 页码:67-77
  • DOI:10.23974/ijol.2018.vol3.1.64
  • 出版社:Chinese American Librarians Association
  • 摘要:Traditional knowledge organization systems (KOS) including thesauri, classification schemes, taxonomies, subject heading systems, name authorities, and other lists of terms and codes have been playing important roles in indexing, information organization, and retrieval. With the advent of the semantic web, a large number of them have been converted into Linked Open Data (LOD) datasets. Since the Simple Knowledge Organization Systems (SKOS) and SKOS eXtension for Labels (SKOS-XL) became formal World Wide Web Consortium (W3C) recommendations, they have been applied to knowledge organization systems. In this article, the issues surrounding changes, versioning control, and evolution of KOS are investigated. From KOS services providers and consumers perspectives, this study focuses on the representation of changes on the semantic web.
  • 其他摘要:Traditional knowledge organization systems (KOS) including thesauri, classification schemes, taxonomies, subject heading systems, name authorities, and other lists of terms and codes have been playing important roles in indexing, information organization, and retrieval. With the advent of the semantic web, a large number of them have been converted into Linked Open Data (LOD) datasets. Since the Simple Knowledge Organization Systems (SKOS) and SKOS eXtension for Labels (SKOS-XL) are languages for representation of knowledge organization systems, they have been applied to knowledge organization systems. In this article, the issues surrounding changes, versioning control, and evolution of KOS are investigated. From KOS services providers and consumers perspectives, this study focuses on representation of changes on the semantic web.
  • 关键词:KOS; Change Representation; Linked Data; SKOS; SKOS-XL; Ontology
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