DOI QR코드

DOI QR Code

키워드 네트워크 분석을 이용한 연구데이터 관련 국내 연구 동향 분석

An Analysis of Domestic Research Trend on Research Data Using Keyword Network Analysis

  • 한상우 (광주대학교 문헌정보학과)
  • 투고 : 2023.12.12
  • 심사 : 2023.12.20
  • 발행 : 2023.12.30

초록

본 연구는 연구데이터 관련 국내 연구의 동향을 파악하기 위하여 RISS에서 연구데이터 관련 논문을 수집하였으며, 데이터 정제 후 총 58건의 연구논문을 대상으로 134개의 저자 키워드를 추출하여 키워드 네트워크 분석을 수행하였다. 분석 결과, 첫째, 아직까지 국내에서 연구데이터 관련 연구의 수가 58건에 지나지 않아 추후 많은 관련 연구가 진행될 필요가 있음을 알 수 있었다. 둘째, 연구데이터 관련 연구 분야는 대부분 복합학 중 문헌정보학에 집중되어 있었다. 셋째, 연구데이터 관련 저자 키워드의 빈도분석 결과 '연구데이터관리', '연구데이터공유', '데이터리포지터리', '오픈사이언스' 등이 다빈도 주요 키워드로 분석되어 연구데이터 관련 연구는 위의 키워드를 중심으로 진행되고 있음을 알 수 있었다. 키워드 네트워크 분석 결과에서도 다빈도 키워드는 연결 중심성 및 매개 중심성에서 중심적인 위치를 차지하며 관련 연구에서 핵심 키워드에 위치하고 있음을 알 수 있었다. 본 연구의 결과를 통하여 최근의 연구데이터 관련 동향을 파악할 수 있었고, 향후 집중적으로 연구해야 하는 분야를 확인할 수 있었다.

The goal of this study is to investigate domestic research trend on research data study. To achieve this goal, articles related research data topic were collected from RISS. After data cleansing, 134 author keywords were extracted from a total of 58 articles and keyword network analysis was performed. As a result, first, the number of studies related to research data in Korea is still only 58, so it was found that many related studies need to be conducted in the future. Second, most research fields related to research data were focused on library and information science among complex studies. Third, as a result of frequency analysis of author keywords related to research data, 'research data management', 'research data sharing', 'data repository', and 'open science' were analyzed as major frequent keywords, so research data-related research focuses on the above keywords. The keyword network analysis results also showed that high-frequency keywords occupy a central position in degree centrality and betweenness centrality and are located as core keywords in related studies. Through the results of this study, we were able to identify trends related to recent research data and identify areas that require intensive research in the future.

키워드

과제정보

이 연구는 2023년도 광주대학교 대학 연구비의 지원을 받아 수행되었음.

참고문헌

  1. Cho, Jane (2011). A study for research area of library and information science by network text analysis. Journal of the Korean Society for Information Management, 28(4), 65-83. http://dx.doi.org/10.3743/KOSIM.2011.28.4.065
  2. Cho, Sungbum & Shin, Hayoung (2022). The trend of academic research on high school credit system: Network Text Analysis. Culture and Convergence, 44(3), 149-167. http://doi.org/10.33645/cnc.2022.03.44.3.149
  3. Kim, Junhyun (2015). An essay for understanding the meaning of the network text analysis results in study of the public administration. The Journal of Humanities and Social Sciences, 16(4), 247-280. http://doi.org/10.15818/ihss.2015.16.4.247
  4. KISTI [n.d]. DataON. Available: https://dataon.kisti.re.kr/intro/intro02.do
  5. Ko, Jeonghyeun, Kang, Woojin, & Lee, Jongwook (2021). Research trend analysis of digital divide in South Korea. Journal of Korean Library and Information Science Society, 52(4), 179-203. http://dx.doi.org/10.16981/kliss.52.4.202112.179
  6. Korea Ministry of Government Legislation (2023, September 27). Legislative advance notice on law enactment of national research data management and usage promotion. Available: https://www.moleg.go.kr/lawinfo/makingInfo.mo?lawSeq=74834&lawCd=0&&lawType=TYPE5&mid=a10104010000
  7. Lee, Min-Soo & Kim, Hea-Jin (2022). Comparative study of information literacy education and librarian teacher evaluation index in teachers' competency development evaluation. Journal of Korean Library and Information Science Society, 53(3), 455-477. http://dx.doi.org/10.16981/kliss.53.3.202209.455
  8. Lim, Jeong-Hoon (2022). Analysis of research trends in information literacy education using keyword network analysis and topic modeling. Journal of the Korean Society for Information Management, 39(4), 23-48. http://dx.doi.org/10.3743/KOSIM.2022.39.4.023
  9. Min, Yohan, Kim, Giyoung, & Park, Oknam (2021). The trend analysis of 'cultural contents' research using topic modeling and keyword network analysis. Journal of Social Science, 32(2), 113-131. http://dx.doi.org/10.16881/jss.2021.04.32.2.113
  10. Mun, Seong Yun & Song, Ki-Sang (2019). A study on the complex problem solving research trends through keyword network analysis. JKIIT, 17(5), 117-128. http://doi.org/10.14801/jkiit.2019.17.5.117
  11. NST (2019). Research data management guideline (NST Policy Research 2018-09). National Research Council of Science & Technology.
  12. STAR Library [n.d]. Research Data Management. Available: https://starlibrary.org/research-data-management
  13. OSTP (2023, January 11). FACT SHEET: Biden-Harris Administration Announces New Actions to Advance Open and Equitable Research. The White House. Available: https://www.whitehouse.gov/ostp/news-updates/2023/01/11/fact-sheet-biden-harris-administration-announces-new-actions-to-advance-open-and-equitable-research/