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

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. Data sharing is recognized as a way to promote scientific collaboration and reproducibility, but some are concerned over whether research based on shared data can achieve high impact. Here, the authors show that neuroimaging papers using shared data are no less likely to appear in top-ranked journals.

数据共享作为一种通过促进合作、提高透明度和可重复性来加速科学发展的手段，越来越受到推崇。虽然从理念上来说很少有人反对数据共享，但一系列障碍使得大多数研究人员在实践中无法实施。为了证明共享数据所需的巨大努力是合理的，资助机构、科研机构和研究人员需要明确的受益证据。在此，我们利用国际神经影像数据共享倡议，展示了一个案例研究，它提供了开放共享对脑成像数据使用以及由此产生的经同行评审的出版物的影响的直接证据。我们证明，公开共享的数据可以扩大数据贡献者所进行的科学研究的规模，并能吸引来自更广泛学科领域的科学家。这些发现打破了使用共享数据的科学发现无法在高影响力期刊上发表的谣言，表明了数据共享对加速科学发展的变革力量，并强调了普遍实施数据共享的必要性。 数据共享被认为是促进科学合作和可重复性的一种方式，但一些人担心基于共享数据的研究是否能产生重大影响。在此，作者表明使用共享数据的神经影像学论文同样有可能出现在顶级期刊上。