Sharing Detailed Research Data Is Associated with Increased Citation Rate

Abstract

BackgroundSharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available.Principal FindingsWe examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p = 0.006) associated with a 69% increase in citations, independently of journal impact factor, date of publication, and author country of origin using linear regression.SignificanceThis correlation between publicly available data and increased literature impact may further motivate investigators to share their detailed research data.

Data archiving – editorial

“…Because data archiving enables verification, extension, and re-use, it increases interest in the research and invites citation and collaboration. Not only are papers accompanied by publicly archived data cited more frequently (Piwowar et al 2007), but the datasets themselves are often highly cited.…”

Web indicators for research evaluation. Part 3: books and non standard outputs

“…All of these could indirectly help to encourage data sharing by recognising popular datasets and creators. This recognition already occurs indirectly to some extent because a study of 85 cancer microarray clinical trial publications with shared datasets showed that just under half of the trials with publicly available data received about 85% of the aggregate citations and clinical trials with publicly shared data were cited around 70% more frequently than those without (Piwowar;Day;Fridsma, 2007). Thomson Reuters launched its Data Citation Index in 2012 to index "a significant number of the world's leading data repositories of critical interest to the scientific community, including over two million data studies and datasets" and so dataset citation analysis is likely to become routine and simple when this matures.…”

A Collaborative Framework for Data Management Services: The Experience of the University of California

“…Identifiers also provide the mechanism behind data citation, which in turn powers data sharing and re-use, as well as allowing other researchers to provide credit and attribution for the original researcher (Piwowar et al 2007). EZID, a tool developed by CDL and available to UC campuses and external institutions, enables easy creation and maintenance of long-term identifiers.…”