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How research data is cited in scholarly literature: A case study of HINTS
Author(s) -
Yoon JungWon,
Chung EunKyung,
Lee Jae Yun,
Kim Jihyun
Publication year - 2019
Publication title -
learned publishing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.06
H-Index - 34
eISSN - 1741-4857
pISSN - 0953-1513
DOI - 10.1002/leap.1213
Subject(s) - citation , computer science , information retrieval , web of science , world wide web , data science , library science , medline , political science , law
This study investigated how Health Information National Trends Survey (HINTS) data from the U.S. National Cancer Institute (NCI) was cited in the scholarly literature. It addressed the following research questions: (1) What patterns of citations exist among authors of research articles using HINTS data? and (2) How is the citation format of HINTS data characterized? We collected scholarly articles that used HINTS data as primary or secondary data for analysis from Web of Science databases and HINTS publications on the NCI website. Among the resulting 250 articles, we identified citations to HINTS data themselves (data citations) and those to HINTS‐related documents (data‐related citations). Among the 250 articles, 156 articles (62.4%) cited HINTS data or HINTS‐related documents; only 29 articles (11.6%) cited HINTS data, while 127 (50.8%) cited HINTS‐related documents. Both data and data‐related citations increased over time. Data citation format varied, and 13 different compositions of citation elements were identified. Author, Title, and Location (URL) were common elements. The frequent use of URLs is undesirable due to URL instability. Furthermore, the data citations showed not only various compositions of citation elements but also ill‐defined element formats. Standardized citation formats are therefore needed.