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A Study on Evaluation Model for Usability of Research Data Service

연구데이터 서비스의 유용성 평가 모형 연구

  • 박진호 (주식회사 리스트 사업개발본부) ;
  • 고영만 (성균관대학교 문과대학 문헌정보학과) ;
  • 김현수 (성균관대학교 정보관리연구소)
  • Received : 2019.11.17
  • Accepted : 2019.12.13
  • Published : 2019.12.30

Abstract

The Purpose of this study is to develop an evaluation model for usability of research data service from the angles of evaluating usefulness of research data service itself and research data use experience-based usability. First, the various cases of evaluating usability of data services are examined and 4 rating scales and 20 measuring indicators for research data service are derived as a result of comparative analysis. In order to verify validity and reliability of the rating scale and the measuring indicators, the study conducted a survey of 164 potential research data users. KMO Bartlett Analysis was performed for validity test, and Principle Component Analysis and Verimax Rotating Method were used for component analysis on measuring indicators. The result shows that the 4 intrinsic rating scales satisfy the validity criteria of KMO Barlett; A single component was determined from component analysis, which verifies the validity of measuring indicators of the current rating scale. However, the result of 12 user experience-based measuring indicators analysis identified 2 components that are each classified as rating scale of utilization level and that of participation level. Cronbach's alpha of all 6 rating scales was 0.6 or more for the overall scale.

본 연구의 목적은 연구데이터 서비스 자체의 유용성과 연구데이터에 대한 사용경험 기반의 유용성 측면에서 평가 모형을 개발하는 것이다. 다양한 사례에서 도출한 데이터 서비스의 유용성 평가 요소로부터 연구데이터에 내재된 평가척도인 검색성, 접근성, 상호운용성, 재활용성 4개와 각각의 측정지표 총 20개를 도출하였다. 그리고 Google Analytics, YouTube 광고료 책정 기준, 서울특별시, Altmetrics의 사례를 분석하여 연구데이터에 대한 이용자 경험 기반의 유용성 측정지표 12개를 도출하였다. 평가척도와 측정지표에 대한 타당성과 신뢰성 검정을 위해 연구데이터의 잠재적 이용자 164명을 대상으로 설문조사를 실시하였다. 평가척도의 타당성 검정을 위해 KMO Bartlett 분석을 하였으며, 측정지표의 성분분석을 위해 주성분 분석과 베리맥스 회전분석법을 사용하였다. 내재적 평가척도의 경우 4개 척도 모두 KMO Bartlett의 타당성 값을 충족시켰으며, 평가척도에 대한 측정지표의 성분분석 결과 모두 단일 성분으로 나타나 현재의 척도로 해당 지표에 대한 설명이 가능하였다. 그러나 이용자 경험 기반의 12개 측정지표의 성분분석 결과는 2개 성분으로 나누어지는 것으로 나타나 각각을 활용도와 참여도라는 개념의 2개 평가척도로 구분하였다. Cronbach's alpha 계수에 의한 신뢰도 측정 결과 6개의 평가척도 모두 0.6 이상의 측정치를 충족시키는 것으로 나타났다.

Keywords

Acknowledgement

Grant : 국가연구데이터플랫폼의 메타데이터 품질 및 유용성 평가모델 연구

Supported by : 한국과학기술정보연구원(KISTI)

본 연구는 2019년 한국과학기술정보연구원(KISTI)의 위탁연구 과제로 수행한 "국가연구데이터플랫폼의 메타데이터 품질 및 유용성 평가모델 연구"의 일부분임.

References

  1. 강병서, 김계수 (2009). (SPSS 17.0) 사회과학 통계분석. 서울: 한나래.
  2. Kim, Eun-Jung, & Nam, Tae-Woo (2012). Factor analysis of effects on research data collection. Journal of the Korean Society for Information Management, 29(2), 27-44. http://dx.doi.org/10.3743/KOSIM.2012.29.2.027
  3. Kim, Jun-Seop, Kim, Sun-Tae, & Choi, Sang-Ki (2019). The functional requirements of core elements for research data management and service. Journal of the Korean Society for Library and Information Science, 53(3), 317-344. http://dx.doi.org/10.4275/KSLIS.2019.53.3.317
  4. Kim, Ji-Hyun (2015). A study on the perceptions of university researchers on data management and sharing. Journal of the Korean Society for Library and Information Science, 49(3), 413-436. http://dx.doi.org/10.4275/KSLIS.2015.49.3.413
  5. Park, Mi-Young, Ahn, In-Ja, & Nam, Seung-Joo (2018). A study on the analysis of research data management and sharing of science & technology government-funded research institutes. Journal of the Korean Biblia Society for Library and Information Science, 29(4), 319-344. http://dx.doi.org/10.14699/kbiblia.2018.29.4.319
  6. Seoul Metropolitan Government (2015). Developing indicators for public data use in seoul city. Seoul: Seoul Metropolitan Government
  7. 송지준 (2008). 논문작성에 필요한 SPSS/AMOS 통계분석방법. 서울: 21세기사.
  8. You, Sa-Rah (2019). Reconsideration of research framework for RRM in the perspective of linked open data. Journal of the Korean Society for Library and Information Science, 53(3), 101-120. http://dx.doi.org/10.4275/KSLIS.2019.53.3.101
  9. Cho, Jane (2016). Study about research data citation based on DCI (Data Citation Index). Journal of the Korean Society for Library and Information Science, 50(1), 189-207. http://dx.doi.org/10.4275/KSLIS.2016.50.1.189
  10. Choi, Li-Jin, & Jung, Young-Mi (2019). A study on the legal interoperability guidelines for research data. In Proceedings of Summet, Meeting of Korean Library And Information Science Society, 2019. 5. 24, Gyeongsangbuk-do: Kyungpook National University Global Plaza, 241-250.
  11. Abran, A., Khelifi, A., Suryn, W., & Seffah, A. (2003, April). Consolidating the ISO usability models. In Proceedings of 11th international software quality management conference. 23-25.
  12. Dietrich, D., Gray, J., McNamara, T., Poikola, A., Pollock, P., Tait, J., & Zijlstra, T. (2009). Open data handbook. Retrieved from http://opendatahandbook.org/guide/en/what-is-open-data/
  13. Elsevier (2015). 10 aspects of highly effective research data. Retrieved from https://www.elsevier.com/connect/10-aspects-of-highly-effective-research-data
  14. Engineering and Physical Sciences Research Council (n.d.). EPSRC policy framework on research data. Retrieved from https://epsrc.ukri.org/about/standards/researchdata/
  15. European Commission (n.d.). Facts and Figures for open research data. Retrieved from https://ec.europa.eu/info/research-and-innovation/strategy/goals-research-and-innovation-policy/open-science/open-science-monitor/facts-and-figures-open-research-data_en
  16. Executive Office of the President of the United States (2013). Open Data Policy-Managing Information as an Asset. Washington, D.C.
  17. Hicksa, D., Woutersb, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015). Bibliometrics: The leiden manifesto for research metrics. Nature, 520, 429-31. https://doi.org/10.1038/520429a
  18. ISO/IEC 9126 (2001). Quality characteristics and guidelines for the user. Geneva: International Organization for Standardization.
  19. Pilat, D., & Fukasaku, Y. (2007). OECD principles and guidelines for access to research data from public funding. Data Science Journal, 6, OD4-OD11. https://doi.org/10.2481/dsj.6.OD4
  20. Swan, A., & Brown, S. (2008). To share or not to share: Publication and quality assurance of research data outputs. A report commissioned by the research information network.
  21. University of Leicester (2012.09.04.). Research Data - Definitions. Retrieved from https://www2.le.ac.uk/services/research-data/rdm/what-is-rdm/research-data
  22. Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., ... & Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3. https://doi.org/10.1038/sdata.2016.18