As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. These archives provide researchers with tools to store, share, and reanalyze neurophysiology data though the means of accomplishing these objectives differ. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. While many tools are available to reanalyze data on and off the archives' platforms, this article features Reproducible Analysis and Visualization of Intracranial EEG (RAVE) toolkit, developed specifically for the analysis of intracranial signal data and integrated with the discussed standards and archives. Neuroelectrophysiology data archives improve how researchers can aggregate, analyze, distribute, and parse these data, which can lead to more significant findings in neuroscience research.

翻译：随着数据共享日益普及，三大支柱——档案库、标准和分析工具——已成为促进数据高效共享与协作的关键组成部分。本文比较了四个免费提供的颅内神经电生理数据存储库：BRAIN计划数据档案库（DABI）、神经生理学数据集成分布式档案库（DANDI）、OpenNeuro和Brain-CODE。这些档案库为研究人员提供了存储、共享和重新分析神经生理学数据的工具，尽管实现这些目标的方式有所不同。脑成像数据结构（BIDS）和跨边界神经数据（NWB）被这些档案库采用，通过实施通用标准使数据更易于研究人员访问。虽然已有众多工具可在档案库平台内外重新分析数据，但本文重点介绍了可重复性颅内脑电图分析与可视化工具包（RAVE），该工具包专为颅内信号数据分析而开发，并与上述标准和档案库实现集成。颅内神经电生理数据档案库改善了研究人员对数据的聚合、分析、分发和解析方式，从而可能推动神经科学研究取得更重要的成果。