Sharing Neuron Data: Carrots, Sticks, and Digital Records.
Sharing Neuron Data: Carrots, Sticks, and Digital Records.
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DOI：
10.1371/journal.pbio.1002275
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发表时间：
2015-10
期刊：
影响因子：
9.8
通讯作者：
Ascoli GA
中科院分区：
文献类型：
--
作者：
Ascoli GA
常规数据共享极大地有利于几个科学学科，如分子生物学，粒子物理学和天文学。相比之下，神经科学数据仍然很少共享，这极大地限制了二次发现的潜力和研究进展的加速。尽管神经科学各子领域对数据共享的态度并不统一，但数据共享实践的广泛采用将需要社区的文化转变。轴突和树突形态的数字重建构成了一种特别“可共享”的数据。公共存储库NeuroMorpho.org的流行表明数据共享可以使用户和贡献者受益。数据可用性的增加也在催化基层发展和互补资源、研究工具和社区倡议的自发整合。然而，即使在这个罕见的成功领域，更多的数据仍然是未共享的，而不是共享的。我们作为NeuroMorpho.org的开发者和管理者的经验表明，关于共享（或不共享）数据的期望和后果的更大透明度，以及公开披露哪些数据集是共享的，哪些不是，可能会加速向社区范围的数据共享过渡。基于他在神经元形态数字重建方面的长期经验，Giorgio Ascoli阐述了改变神经科学界对数据共享的文化阻力的好处和挑战以及解决方案。
Routine data sharing is greatly benefiting several scientific disciplines, such as molecular biology, particle physics, and astronomy. Neuroscience data, in contrast, are still rarely shared, greatly limiting the potential for secondary discovery and the acceleration of research progress. Although the attitude toward data sharing is non-uniform across neuroscience subdomains, widespread adoption of data sharing practice will require a cultural shift in the community. Digital reconstructions of axonal and dendritic morphology constitute a particularly “sharable” kind of data. The popularity of the public repository NeuroMorpho.Org demonstrates that data sharing can benefit both users and contributors. Increased data availability is also catalyzing the grassroots development and spontaneous integration of complementary resources, research tools, and community initiatives. Even in this rare successful subfield, however, more data are still unshared than shared. Our experience as developers and curators of NeuroMorpho.Org suggests that greater transparency regarding the expectations and consequences of sharing (or not sharing) data, combined with public disclosure of which datasets are shared and which are not, may expedite the transition to community-wide data sharing. Based on his long experience with digital reconstructions of neuronal morphologies, Giorgio Ascoli articulates the benefits and challenges of—and solutions for—changing the cultural resistance to data sharing in the neuroscience community.