Journal article
Data set mentions and citations: A content analysis of full‐text publications
Journal of the Association for Information Science and Technology, v 69(1), pp 32-46
Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This study provides evidence of data set mentions and citations in multiple disciplines based on a content analysis of 600 publications in PLoS One. We find that data set mentions and citations varied greatly among disciplines in terms of how data sets were collected, referenced, and curated. While a majority of articles provided free access to data, formal ways of data attribution such as DOIs and data citations were used in a limited number of articles. In addition, data reuse took place in less than 30% of the publications that used data, suggesting that researchers are still inclined to create and use their own data sets, rather than reusing previously curated data. This paper provides a comprehensive understanding of how data sets are used in science and helps institutions and publishers make useful data policies.
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Details
- Title
- Data set mentions and citations: A content analysis of full‐text publications
- Creators
- Mengnan Zhao - College of Computing and Informatics, Drexel UniversityErjia Yan - College of Computing and Informatics, Drexel UniversityKai Li - College of Computing and Informatics, Drexel University
- Publication Details
- Journal of the Association for Information Science and Technology, v 69(1), pp 32-46
- Publisher
- Wiley
- Number of pages
- 15
- Grant note
- National Consortium for Data Science (Data Fellows Award)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000418157900004
- Scopus ID
- 2-s2.0-85030148690
- Other Identifier
- 991014976813304721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Information Science & Library Science