International Neuroinformatics Coordinating Facility, Stockholm, Sweden.
Gigascience. 2012 Jul 12;1(1):9. doi: 10.1186/2047-217X-1-9.
There is growing recognition of the importance of data sharing in the neurosciences, and in particular in the field of neuroimaging research, in order to best make use of the volumes of human subject data that have been acquired to date. However, a number of barriers, both practical and cultural, continue to impede the widespread practice of data sharing; these include: lack of standard infrastructure and tools for data sharing, uncertainty about how to organize and prepare the data for sharing, and researchers' fears about unattributed data use or missed opportunities for publication. A further challenge is how the scientific community should best describe and/or reference shared data that is used in secondary analyses. Finally, issues of human research subject protections and the ethical use of such data are an ongoing source of concern for neuroimaging researchers.One crucial issue is how producers of shared data can and should be acknowledged and how this important component of science will benefit individuals in their academic careers. While we encourage the field to make use of these opportunities for data publishing, it is critical that standards for metadata, provenance, and other descriptors are used. This commentary outlines the efforts of the International Neuroinformatics Coordinating Facility Task Force on Neuroimaging Datasharing to coordinate and establish such standards, as well as potential ways forward to relieve the issues that researchers who produce these massive, reusable community resources face when making the data rapidly and freely available to the public. Both the technical and human aspects of data sharing must be addressed if we are to go forward.
人们越来越认识到数据共享在神经科学中的重要性，尤其是在神经影像学研究领域，以便充分利用迄今为止获得的大量人类受试者数据。然而，一些实际的和文化上的障碍继续阻碍着数据共享的广泛实践；这些障碍包括：缺乏数据共享的标准基础设施和工具，不确定如何组织和准备数据进行共享，以及研究人员担心数据被非归因使用或错失发表机会。另一个挑战是科学界应该如何最好地描述和/或引用在二次分析中使用的共享数据。最后，研究人员对人类研究对象保护和此类数据的道德使用问题持续感到担忧。
一个关键问题是共享数据的生产者如何以及应该得到承认，以及科学的这一重要组成部分将如何使个人在学术生涯中受益。虽然我们鼓励该领域利用这些数据发布机会，但使用元数据、来源和其他描述符的标准至关重要。本评论概述了国际神经信息学协调设施神经影像学数据共享工作组协调和建立这些标准的努力，以及为解决产生这些大规模、可重复使用的社区资源的研究人员在将数据快速和免费提供给公众时所面临的问题的潜在方法。如果我们要向前发展，就必须解决数据共享的技术和人为方面的问题。
