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  • P-ISSN1013-0799
  • E-ISSN2586-2073
  • KCI

ISSN : 1013-0799

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Vol.40 No.4

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Constructing a Knowledge Graph for Improving Quality and Interlinking Basic Information of Cultural and Artistic Institutions

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2023, v.40 no.4, pp.329-349
https://doi.org/10.3743/KOSIM.2023.40.4.329
Euntaek Seon (Chung-Ang University)
Haklae Kim (Chung-Ang University)
Seon, E., & Kim, H. (2023). Constructing a Knowledge Graph for Improving Quality and Interlinking Basic Information of Cultural and Artistic Institutions. Journal of the Korean Society for Information Management, 40(4), 329-349, https://doi.org/10.3743/KOSIM.2023.40.4.329

Abstract

With the rapid development of information and communication technology, the speed of data production has increased rapidly, and this is represented by the concept of big data. Discussions on quality and reliability are also underway for big data whose data scale has rapidly increased in a short period of time. On the other hand, small data is minimal data of excellent quality and means data necessary for a specific problem situation. In the field of culture and arts, data of various types and topics exist, and research using big data technology is being conducted. However, research on whether basic information about culture and arts institutions is accurately provided and utilized is insufficient. The basic information of an institution can be an essential basis used in most big data analysis and becomes a starting point for identifying an institution. This study collected data dealing with the basic information of culture and arts institutions to define common metadata and constructed small data in the form of a knowledge graph linking institutions around common metadata. This can be a way to explore the types and characteristics of culture and arts institutions in an integrated way.

keywords
arts & culture, small data, knowledge graph, semantic web, linked data
Submission Date
2023-11-20
Revised Date
2023-12-08
Accepted Date
2023-12-11

Journal of the Korean Society for Information Management

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