생명과학분야 학술논문의 전문에 나타난 연구데이터의 공유, 재이용, 인용 분석
Data Sharing, Reuse, and Citation in Biological Research: An Analysis of Full-Text Literature
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초록
본 연구의 목적은 생명과학 분야 학술논문의 전문(full-text)에 나타난 연구데이터의 공유, 재이용, 인용의 관례을 분석하는 것이다. 연구데이터 공유의 역사가 상대적으로 오래된 생명과학 분야를 대상으로 하였다. 데이터의 수집은 Clarivate Analytics사의 Data Citation Index(DCI)와 Web of Science(WoS)의 연구분야(research area)를 대상으로 하였다. 학술논문의 전문을 분석하기 위하여 연구데이터의 공유, 재이용, 인용을 지시하는 단어 및 구문을 이용하여 반자동 텍스트 검색 기술(semi-automatic text searching techniques)을 활용하고 내용분석(content-analysis)을 실시하였다. 생명과학분야는 공식적인 데이터 인용(formal data citation)이 4.62%로 비공식적인 데이터 인용(informal data citation) 95.38%로 보다 널리 퍼져 있었다. 즉, 생명과학분야에서의 데이터 공유자는 학술논문에서 저자가 받는 학술 크레딧을 연구데이터의 공유에서는 받지 못하고 있음을 확인할 수 있었다. 학술논문에서의 비공식적인 데이터 인용의 위치가 많은 빈도수는 본문, 보충자료, 참고문헌, 감사의글(acknowledgements), 각주, 초록 순이었다. 학술논문에서는 데이터의 재이용(47.8%)이 데이터의 공유(22.1%)보다 2배 이상 많이 출현하였다. 본 연구의 공헌은 데이터 공유, 재이용, 인용의 현상을 학술논문의 전문을 통해서 분석함으로써 연구데이터 인용의 실제적인 현상을 파악했다는 점이다.
Abstract
This study aims to examine data sharing, reuse, and citation practices in academic literature within the biological sciences, a field with a well-established tradition of data sharing. Data were sourced from Clarivate Analytics’ Data Citation Index (DCI) and the Web of Science (WoS). Semi-automatic text-searching techniques were used to identify terms and phrases related to data sharing, reuse, and citation, followed by an in-depth content analysis of full texts. The findings reveal that informal data citations (4.62%) are substantially more prevalent than formal data citations (95.38%) in biological science literature. Informal citations most frequently appear in the main text, followed by supplementary materials, references, acknowledgments, footnotes, and abstracts. Data reuse (47.8%) was observed to occur approximately twice as often as data sharing (22.1%) in academic literature. This prevalence of informal data citation suggests that data sharers often do not receive the same academic recognition as bibliographic authors. By analyzing data sharing, reuse, and citation practices in the full texts of academic literature, this study contributes valuable insights to the field of research data citation.
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