Preprint Article: “Assessment of Transparency Indicators Across the Biomedical Literature: How Open is Open?”
The following preprint was posted today (October 30, 2020) on bioRxiv.
Despina G Contopoulos-Ioannidis
Kevin W Boyack
Berlin Insitute of Health
Joshua David Wallach
Yale School of Public Health
John P. A. Ioannidis
Recent concerns about the reproducibility of science have led to several calls for more open and transparent research practices and for the monitoring of potential improvements over time. However, with tens of thousands of new biomedical articles published per week, manually mapping and monitoring changes in transparency is unrealistic. We present an open-source, automated approach to identify five indicators of transparency (data sharing, code sharing, conflicts of interest disclosures, funding disclosures and protocol registration) and apply it across the entire open access biomedical literature of 2.75 million articles on PubMed Central. Our results indicate remarkable improvements in some (e.g. conflict of interest disclosures, funding disclosures), but not other (e.g. protocol registration, code sharing) areas of transparency over time, and map transparency across fields of science, countries, journals and publishers. This work has enabled the creation of a large, integrated, and openly available database to expedite further efforts to monitor, understand and promote transparency and reproducibility in science.
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About Gary Price
Gary Price (firstname.lastname@example.org) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.