Measuring the impact of health research data in terms of data citations by scientific publications

Yongmei Bai and Jian Du ()
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Yongmei Bai: Peking University Health Science Center, Peking University
Jian Du: Peking University

Scientometrics, 2022, vol. 127, issue 12, No 5, 6893 pages

Abstract: Abstract Health is a representative domain data-driven research since health research data are growingly generated at a massive scale. There is an intuitive logic that the degree to which disease burden and the number of data resources align. In order to figure out disease-specific data sharing and reuse level, we took the number of data records and their citations in the scientific literature in the Data Citation Index platform as approximate indicators. The results indicated that only a small percentage (7.5%) of health data records had received documented citations by scientific publications. We find the level of data sharing and reuse varies across diseases. Our study suggested that the more socioeconomic burden and the more research funding, the more likely scientific data for diseases will be produced and made available. But such a correlation could not be observed for the activity of data reuse. Secondary reuse of scientific data is a complex behavior.

Keywords: Data records; Data sharing and reuse; Incidence; Disability Adjusted Life Years (DALYs); Funding (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11192-022-04559-4

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