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摘要翻译：
神经科学家现在能够在时空尺度上以惊人的速度获取数据。然而，我们利用现有数据集、工具和智力能力的能力受到技术挑战的阻碍。加速科学发现的主要障碍与公平数据原则相对应：可查找性、数据的全球访问、软件互操作性和可复制/可重用性。我们进行了一次黑客马拉松，致力于在这些步骤上取得进展。这份手稿是一份总结这些成就的技术报告，我们希望作为一个例子，说明专注、深思熟虑的黑客马拉松对我们快速发展的领域的进步的有效性。
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英文标题：
《NeuroStorm: Accelerating Brain Science Discovery in the Cloud》
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作者：
Gregory Kiar, Robert J. Anderson, Alex Baden, Alexandra Badea, Eric W.
Bridgeford, Andrew Champion, Vikram Chandrashekhar, Forrest Collman, Brandon
Duderstadt, Alan C. Evans, Florian Engert, Benjamin Falk, Tristan Glatard,
William R. Gray Roncal, David N. Kennedy, Jeremy Maitin-Shepard, Ryan A.
Marren, Onyeka Nnaemeka, Eric Perlman, Sharmishtaas Seshamani, Eric T.
Trautman, Daniel J. Tward, Pedro Antonio Vald\'es-Sosa, Qing Wang, Michael I.
Miller, Randal Burns, Joshua T. Vogelstein
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最新提交年份：
2018
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capacities is hampered by technical challenges. The key barriers to accelerating scientific discovery correspond to the FAIR data principles: findability, global access to data, software interoperability, and reproducibility/re-usability. We conducted a hackathon dedicated to making strides in those steps. This manuscript is a technical report summarizing these achievements, and we hope serves as an example of the effectiveness of focused, deliberate hackathons towards the advancement of our quickly-evolving field.
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PDF链接：
https://arxiv.org/pdf/1803.03367
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