Department of Neuroscience, Division of Biology and Medicine, Brown University, Providence, Rhode Island 02912.
The Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, Rhode Island 02912.
J Neurosci. 2024 Sep 18;44(38):e0381242024. doi: 10.1523/JNEUROSCI.0381-24.2024.
Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience research. Neurodata Without Borders (NWB), a standard language for neurophysiology data, has recently emerged as a powerful solution for data management, analysis, and sharing. We here discuss our labs' efforts to implement NWB data science pipelines. We describe general principles and specific use cases that illustrate successes, challenges, and non-trivial decisions in software engineering. We hope that our experience can provide guidance for the neuroscience community and help bridge the gap between experimental neuroscience and data science. Key takeaways from this article are that (1) standardization with NWB requires non-trivial design choices; (2) the general practice of standardization in the lab promotes data awareness and literacy, and improves transparency, rigor, and reproducibility in our science; (3) we offer several feature suggestions to ease the extensibility, publishing/sharing, and usability for NWB standard and users of NWB data.
神经科学研究已经发展到生成越来越大且复杂的实验数据集,而高级数据科学工具在神经科学研究中发挥着核心作用。Neurodata Without Borders (NWB) 是一种神经生理学数据的标准语言,最近已成为数据管理、分析和共享的强大解决方案。我们在这里讨论了我们实验室实施 NWB 数据科学管道的努力。我们描述了通用原则和具体用例,说明了软件工程中的成功、挑战和非平凡决策。我们希望我们的经验可以为神经科学界提供指导,并帮助弥合实验神经科学和数据科学之间的差距。本文的主要收获是:(1) 使用 NWB 进行标准化需要进行非平凡的设计选择;(2) 实验室中的标准化实践促进了数据意识和素养,提高了我们科学的透明度、严谨性和可重复性;(3) 我们提出了一些功能建议,以简化 NWB 标准的可扩展性、发布/共享和可用性,以及 NWB 数据的用户体验。