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Trends and issues in establishing interoperability among knowledge organization systems

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  • Marcia Lei Zeng
  • Lois Mai Chan

Abstract

This report analyzes the methodologies used in establishing interoperability among knowledge organization systems (KOS) such as controlled vocabularies and classification schemes that present the organized interpretation of knowledge structures. The development and trends of KOS are discussed with reference to the online era and the Internet era. Selected current projects and activities addressing KOS interoperability issues are reviewed in terms of the languages and structures involved. The methodological analysis encompasses both conventional and new methods that have proven to be widely accepted, including derivation/modeling, translation/adaptation, satellite and leaf node linking, direct mapping, co‐occurrence mapping, switching, linking through a temporary union list, and linking through a thesaurus server protocol. Methods used in link storage and management, as well as common issues regarding mapping and methodological options, are also presented. It is concluded that interoperability of KOS is an unavoidable issue and process in today's networked environment. There have been and will be many multilingual products and services, with many involving various structured systems. Results from recent efforts are encouraging.

Suggested Citation

  • Marcia Lei Zeng & Lois Mai Chan, 2004. "Trends and issues in establishing interoperability among knowledge organization systems," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 55(5), pages 377-395, March.
    • Handle: RePEc:bla:jamist:v:55:y:2004:i:5:p:377-395
    DOI: 10.1002/asi.10387
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    Cited by:

    1. Jan Pawlowski & Markus Bick & René Peinl & Stefan Thalmann & Ronald Maier & Lars Hetmank & Paul Kruse & Malte Martensen & Henri Pirkkalainen, 2014. "Social Knowledge Environments," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(2), pages 81-88, April.
    2. Qingqiang Wu & Yichen Kuang & Qingqi Hong & Yingying She, 2019. "Frontier knowledge discovery and visualization in cancer field based on KOS and LDA," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 979-1010, March.
    3. Wentao Cui & Meng Xiao & Ludi Wang & Xuezhi Wang & Yi Du & Yuanchun Zhou, 2024. "Automated taxonomy alignment via large language models: bridging the gap between knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5287-5312, September.
    4. Andreas Vlachidis & Douglas Tudhope, 2016. "A knowledge‐based approach to Information Extraction for semantic interoperability in the archaeology domain," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1138-1152, May.
    5. Stubkjær, Erik & Çağdaş, Volkan, 2021. "Alignment of standards through semantic tools – The case of land administration," Land Use Policy, Elsevier, vol. 104(C).
    6. Wei Du & Xusen Cheng & Chen Yang & Jianshan Sun & Jian Ma, 2017. "Establishing interoperability among knowledge organization systems for research management: a social network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1489-1506, September.
    7. Wei Du & Raymond Yiu Keung Lau & Jian Ma & Wei Xu, 2015. "A multi-faceted method for science classification schemes (SCSs) mapping in networking scientific resources," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2035-2056, December.

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