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Challenges and Categorizations of Research Data Curation in Social Science: Focusing on the Repository’s Data Quality Review

  • Journal of the Korean Society for Library and Information Science
  • 2025, 59(1), pp.333-354
  • DOI : 10.4275/KSLIS.2025.59.1.333
  • Publisher : 한국문헌정보학회
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : January 19, 2025
  • Accepted : February 19, 2024
  • Published : February 28, 2025

Park, Sukhoon 1 HyeJin Kim 2 Jimin Shin 2 HEO HYE OK 2 Seokho Kim 3

1서울대학교 사회학과
2서울대학교 한국사회과학자료원
3서울대학교

Excellent Accredited

ABSTRACT

This study systematically analyzes and categorizes the challenges found in deposited research data by focusing on the appraisal and selection phases of the data curation process. While the importance of data curation for enhancing the value of research data and promoting data reuse has been emphasized, there has been a lack of empirical research on repositories’ data curation practices. This study reviews international repositories’ guidelines to identify quality assessment types and criteria and applies them to analyze 166 long-term non-archived datasets from Korea Social Science Data Archive (KOSSDA). The analysis reveals five types of challenges: dataset completeness, data integrity, file format, data documentation, and legal/ethical issues. Dataset completeness and legal/ethical issues are the most frequent and difficult challenges to resolve independently. This study contributes to a better understanding of the repositories’ data curation process by analyzing the challenges identified during data appraisal and selection phases through concrete criteria.

Citation status

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