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Intellectual Structure Analysis on the Field of Open Data Using Co-word Analysis
- fantarias3@gmail.com
Yong-Gu Lee (Kyungpook National University)
- yglee@knu.ac.kr
Abstract
The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword “open data” in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that “big data” exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that “the semantic web” had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.
- keywords
- 오픈 데이터, 링크드 오픈 데이터, 공공데이터, 지적 구조, 네트워크분석
- Submission Date
- 2023-11-24
- Revised Date
- 2023-12-10
- Accepted Date
- 2023-12-13
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