Assessment of the impact of shared brain imaging data on the scientific literature

Abstract

Data sharing is increasingly recommended as a means of accelerating science by facilitating collaboration, transparency, and reproducibility. While few oppose data sharing philosophically, a range of barriers deter most researchers from implementing it in practice. To justify the significant effort required for sharing data, funding agencies, institutions, and investigators need clear evidence of benefit. Here, using the International Neuroimaging Data-sharing Initiative, we present a case study that provides direct evidence of the impact of open sharing on brain imaging data use and resulting peer-reviewed publications. We demonstrate that openly shared data can increase the scale of scientific studies conducted by data contributors, and can recruit scientists from a broader range of disciplines. These findings dispel the myth that scientific findings using shared data cannot be published in high-impact journals, suggest the transformative power of data sharing for accelerating science, and underscore the need for implementing data sharing universally.

The citation advantage of linking publications to research data

“…This is a known problem more generally: DAS contain links to data (and software) repositories only too rarely [17][18][19]. Nevertheless there are benefits to data sharing [20][21][22]. It is known that, for example, the biomedical literature in PubMed has shown clear signs of improvement in the transparency and reproducibility of results over recent years, including sharing data [23].…”

The Adolescent Data Hub: The Largest Catalog of Open Access Data on Adolescents Living in Low‐ and Middle‐Income Countries

“…Data-sharing behaviors appear to have increased during the past decade, but many researchers still consider their own lack of expertise on data management and curation a roadblock to consistent implementation (Tenopir et al 2015). Some researchers might also have concerns about their ability to publish using secondary data; however, an analysis of bibliometric data on a neuroscience open-data initiative found that secondary analyses of shared data were published in moderate-to highimpact journals at frequencies comparable to primary data analyses (Milham et al 2018). Trends toward increased data sharing, especially when supported by institutional structure, provide an opportunity to accelerate collaboration across disciplines, drive more efficient use of resources, and ultimately facilitate the generation of more evidence for decision-makers.…”

Data Reuse and the Social Capital of Open Science

“…While this seems to be a difficult calculation to make, sharing data has a number of obvious benefits. Not only does open data lead to immediate prestige [18,23], but can result in the accumulation of longer-term payoffs as well [16,24]. This comes in the form of citations, successful replications, and the remixing of data sets.…”