한국비블리아학회지 (Journal of the Korean BIBLIA Society for library and Information Science)

한국비블리아학회 (Korean Biblia Society for Library and Information Science)
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키워드 네트워크 분석을 활용한 연구데이터 분야 동향 분석 - SCOPUS DB를 중심으로 -

Analyzing Trends in Research Data Using Keyword Network Analysis: Focusig on SCOPUS DB

  • 금효진 (전북대학교 기록관리학과) ;
  • 김선태 (전북대학교 문헌정보학과)
  • Hyojin Geum ;
  • Suntae Kim
  • 투고 : 2024.05.15
  • 심사 : 2024.06.13
  • 발행 : 2024.06.30
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초록

본 연구는 최근 15년간의 연구데이터 관련 연구 현황을 파악하기 위하여 2010년부터 2024년까지의 연구데이터 학술논문의 연구 동향을 분석하고자 하였다. 목적을 달성하고자 Scopus DB에 게재된 학술논문 14,921편을 대상으로 키워드 빈도 분석 및 네트워크 중심성 분석을 수행하였다. 학술지 게재 시기에 따라 1기(2010-2014년), 2기(2015-2019년), 3기(2020-2024년)로 구분하여 UCINET을 활용한 키워드 네트워크 분석을 수행한 결과, 시기에 상관없이 연구되는 주요 키워드와 기간별로 주목받는 키워드, 시간이 지나면서 관심이 줄어드는 키워드를 도출하였다. 최근 15년간 연구데이터 관련 연구가 가장 활발히 이루어진 주제는 데이터 공유인 것으로 확인되었으며, 연결 중심성이 높은 키워드들이 대부분 매개 중심성 또한 높은 것으로 나타났다. 본 연구의 결과는 향후 국내 연구데이터 분야의 연구 방향성을 제시하는 기초자료로서 활용될 수 있을 것으로 판단된다.

This study aimed to analyze the research trends of research data academic papers from 2010 to 2024 to understand the research status of research data over the past 15 years. To achieve this goal, keyword frequency analysis and network centrality analysis were conducted on 14,921 academic articles published in Scopus DB. The keyword network analysis using UCINET, which was divided into the first period (2010-2014), second period (2015-2019), and third period (2020-2024) according to the period of publication of academic journals, revealed the main keywords studied regardless of the period, the keywords that attracted attention by period, and the keywords that decreased in attention over time. It was found that the most active topic of research data-related research in the last 15 years is data sharing, and most of the keywords with high Degree Centrality also have high Betweenness Centrality. The results of this study can be utilized as a basis for suggesting future research directions in the field of research data in Korea.

키워드

과제정보

이 논문은 2023년 전북대학교 국립대학 육성사업의 지원을 받아 수행되었음.

참고문헌

  1. Han, Sang Woo (2023). An analysis of domestic research trend on research data using keyword network analysis. Korean Library And Information Science Society, 54(4), 393-414. https://dx.doi.org/10.16981/kliss.54.4.202312.393
  2. Jeong, Sun-Kyeong (2022). The study on data governance research trends based on text Mining: based on the publication of Korean academic journals from 2009 to 2021. Journal of Digital Convergence, 20(4), 133-145. https://dx.doi.org/10.14400/JDC.2022.20.4.133
  3. Kim, Byeong Sun, Jeong, Min-Woo, Jeon, Sang Eun, & Shin, Dong Bin (2015). Global research trends on geospatial information by keyword network analysis. Spatial Information Research, 23(1), 69-77. https://doi.org/10.12672/ksis.2015.23.1.069
  4. Kim, Ji Hyun (2013). An analysis of data management policies of governmental funding agencies in the U.S., the U.K., Canada and Australia. Journal of the Korean Society for Library and Information Science, 47(3), 251-274. https://dx.doi.org/10.4275/KSLIS.2013.47.3.251
  5. Kim, So-Yeon & Lee, Eun Ju (2022). Research trends of archival information services using language network analysis. Journal of Korean Society of Archives and Records Management, 22(4), 87-107. https://dx.doi.org/10.14404/JKSARM.2022.22.4.087
  6. Kim, Woo Ju (2015). Network Centrality Theory. Seoul: Chaosbook.
  7. Kim, Yong Hak & Kim, Yeong Jin (2011). Social Network Analysis. Seoul: Pakyoungsa.
  8. Koo, Bon Jin & Chang, Durk Hyun (2023). Research on overseas trends and emerging topics in field of library and information science. Journal of the Korean Society for Library and Information Science, 57(3), 71-96. https://dx.doi.org/10.4275/KSLIS.2023.57.3.071
  9. Lee, Hyekyung & Lee, Yong-Gu (2023). Intellectual structure analysis on the field of open data using co-word analysis. Journal of the Korean Society for Information Management, 40(4), 429-450. http://doi.org/10.3743/KOSIM.2023.40.4.429
  10. Lee, Jae Yun (2023). Analyzing the main paths and intellectual structure of the data Literacy Research Domain. Journal of the Korean Society for Information Management, 40(4), 403-428. http://dx.doi.org/10.3743/KOSIM.2023.40.4.403
  11. Lee, Jin Woo & Park, Dongmyung (2023). Semantic network analysis of domestic and international research trends related to museum marketing. Journal of Museum Studies, 46, 57-79. https://dx.doi.org/10.22884/joksms..46.202312.003
  12. Lee, Soosang (2014). A content analysis of journal articles using the language network analysis methods. Journal of the Korean Society for Information Management, 31(4), 49-68. https://dx.doi.org/10.3743/KOSIM.2014.31.4.049
  13. Shin, Eun-Ja (2015). An analysis on trends and tasks of open data policy in the digital era. Journal of the Korean Society for Information Management, 32(3), 49-68. https://dx.doi.org/10.3743/KOSIM.2015.32.3.049
  14. Yoon, Chong-min & Kim, Kyubin (2013). Legislation cases, management policies and countermeasures on scientific data: focusing Australia, the United States and China. Journal of Korea Technology Innovation Society, 16(1), 63-100.
  15. Chunlai Yan, Hongxia Li, Ruihui Pu, Jirawan Deeprasert, & Nuttapong Jotikasthira (2022). Knowledge mapping of research data in China: a bibliometric study using visual analysis. Library Hi Tech, 42(1), 331-349. https://doi.org/10.1108/LHT-11-2020-0285
  16. Freeman, L. C. (1978). Centrality in social networks conceptual classification. Social Networks, 1(3), 215-239. https://doi.org/10.1016/0378-8733(78)90021-7
  17. Kwanya, T. (2021). Publishing trends on research data management in Sub-Saharan Africa: A bibliometrics analysis. IASSIST Quarterly, 45(3-4). https://doi.org/10.29173/iq996
  18. Popping, R. (2000). Computer-assisted text analysis. SAGE Publications, Ltd. https://doi.org/10.4135/9781849208741
  19. Sheriff, N. & Sevukan, R. (2022). Global research trends in research data management (rdm): a scientometric view. International Journal of Information Science and Management (IJISM), 20(4), 117-135. https://dorl.net/dor/20.1001.1.20088302.2022.20.4.8.7 1001.1.20088302.2022.20.4.8.7
  20. Sheriff, N. & Sevukan, R. (2023). Discovering research data management trends from job advertisements using a text-mining approach. Journal of Information Science, 0(0). https://doi.org/10.1177/01655515231193845
  21. Zhang, L. & Eichmann-Kalwara, N. (2019). Mapping the scholarly literature found in scopus on "research data management": a bibliometric and data visualization approach. Journal of Librarianship and Scholarly Communication, 7(1). https://doi.org/10.7710/2162-3309.2266