Brain scientists are now capable of collecting more data in a single experiment than researchers a generation ago might have collected over an entire career. Indeed, the brain itself seems to thirst for more and more data. Such digital information not only comprises individual studies but is also increasingly shared and made openly available for secondary, confirmatory, and/or combined analyses. Numerous web resources now exist containing data across spatiotemporal scales. Data processing workflow technologies running via cloud-enabled computing infrastructures allow for large-scale processing. Such a move toward greater openness is fundamentally changing how brain science results are communicated and linked to available raw data and processed results. Ethical, professional, and motivational issues challenge the whole-scale commitment to data-driven neuroscience. Nevertheless, fueled by government investments into primary brain data collection coupled with increased sharing and community pressure challenging the dominant publishing model, large-scale brain and data science is here to stay.

中文翻译：

---

连接大脑和数据科学

脑科学家现在能够在一次实验中收集到比上一代研究人员在整个职业生涯中收集到的数据还要多的数据。事实上，大脑本身似乎渴望越来越多的数据。此类数字信息不仅包括个人研究，而且越来越多地共享并公开用于二次、验证和/或组合分析。现在存在大量包含跨时空尺度数据的网络资源。通过支持云的计算基础设施运行的数据处理工作流技术允许大规模处理。这种更加开放的举措正在从根本上改变脑科学结果的传播方式以及与可用原始数据和处理结果的联系方式。伦理、专业和动机问题挑战着对数据驱动的神经科学的整体承诺。然而，在政府对初级大脑数据收集的投资的推动下，加上分享的增加和挑战主导出版模式的社区压力，大规模的大脑和数据科学将继续存在。