DANDI: Distributed Archives for Neurophysiology Data Integration

DANDI：神经生理学数据集成的分布式档案

• 批准号: 9795271
• 负责人: Satrajit Sujit Ghosh
• 金额: $ 134.97万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9795271
• 关键词: Address; Adoption; Architecture; Archives; Atlases; Award; BRAIN initiative; Brain; Cells; Client; Collaborations; Communities; Computer software; Data; Data Collection; Data Provenance; Data Set; Data Storage and Retrieval; Decision Making; Development; Devices; Encapsulated; Excision; FAIR principles; Fostering; Future; Human; Imagery; Improve Access; Individual; Informatics; Infrastructure; Ingestion; Institutes; Institution; Interdisciplinary Study; Internet; Intuition; Laboratories; Link; Metadata; Morphologic artifacts; Nervous system structure; Neurosciences; Problem Solving; Process; Protocols documentation; Provider; Publishing; Registries; Reproducibility; Research; Research Personnel; Research Project Grants; Resources; Retrieval; Route; Sample Size; Science; Scientific Inquiry; Scientist; Services; Software Engineering; Standardization; Students; System; Technical Expertise; Technology; Thinking; Time; Training Support; Training and Education; Visualization software; Work; application programming interface; base; citizen science; cloud platform; cluster computing; college; community building; computational neuroscience; computerized data processing; computing resources; data access; data archive; data exchange; data format; data integration; data submission; experience; experimental study; high school; interoperability; neurophysiology; open data; open source; operation; preservation; resilience; tool; web interface

Neuroscientific data contain information from an incredible diversity of species, are generated by a plethora of devices, and encapsulate the results of scientific thinking and decision making. Most of this generated data remains confined within laboratories and is not accessible to the broader scientific community. The research projects awarded under the Brain Initiative are generating a diverse collection of data that can transform and accelerate the pace of discovery. These datasets are large--ranging in size from GBs to PBs-- and represent diverse data types and assorted metadata. To integrate, rather than further isolate, these numerous efforts there is a need to archive, preserve, share, and process data in a way that is meaningful to neuroscience researchers. Any technological solution should reduce redundancy of storage and computation, allow computing near data, and provide easy, but protected when appropriate, access to researchers or citizen scientists. Given the scale of these initiatives and the range of sample sizes and data types, any solution should also consider the broad range of individual technical expertise in the community and therefore allow easy engagement with and ingestion into an archive, while supporting education and training of the scientists in using these technologies. To solve these problems, we propose ​DANDI: Distributed Archives for Neurophysiology Data Integration.​We leverage our team’s extensive experience in informatics, standards development, software engineering, community building, and leverage a robust open-source software stack to create this archive. The archive will lower barriers for neuroscientists by using the ​Neurodata Without Borders (NWB; ​http://nwb.org​) standard as a consistent data format, by providing interoperability with other standards, and by providing robust tools and convenient Web interfaces to interact with the archive. DANDI will: 1) ​provide a cloud platform for versioned neurophysiology data storage for the purposes of collaboration, archiving, and preservation. 2) ​provide easy to use tools for neurophysiology data submission and access in the archive; and 3) facilitate adoption of NWB via standardized applications for data ingestion, visualization and processing. ​We will work with local investigators, the broader neurophysiology community, and with federal and other funders to determine how long and which pieces of data will be stored in DANDI. The archive will also use state of the art data distribution technologies to increase redundancy and fault tolerance, and allow distributed computing across cloud and local computing resources. Consequently the effort will significantly reduce the barrier between laboratories and the cloud, fostering collaboration and data exchange. Overall, we aim to leverage our collective expertise to create and support an NWB-based neurophysiology archive that seamlessly integrates with and enhances current researcher workflows, lowers barriers for scientific inquiry and collaboration, and preserves information for wide reuse.

神经科学方面的数据包含来自令人难以置信的物种多样性的信息，这是由多种多样的 设备，并封装科学思维和决策的结果。大多数生成的数据 仍然局限于实验室，不可能被更广泛的科学界进入。研究 根据《大脑倡议》授予的项目正在生成潜水员的数据，这些数据可以转换和 加速发现的速度。从GB到PBS，这些数据集的大小很大 - 代表 多种数据类型和各种元数据。为了整合而不是进一步隔离，这些众多努力 有必要以对神经科学有意义的方式存档，保存，共享和处理数据 研究人员。任何技术解决方案都应减少存储和计算的冗余，允许 计算近数据，并在适当的情况下提供简单但受到保护，可与研究人员或公民访问 科学家。考虑到这些计划的规模以及样本量和数据类型的范围，任何解决方案均应 还要考虑社区中广泛的个人技术专业知识，因此可以轻松 参与并摄入档案，同时支持科学家的教育和培训 使用这些技术。为了解决这些问题，我们提出了Dandi：分布式档案 神经生理学数据集成。我们利用团队在信息，标准方面的丰富经验 开发，软件工程，社区建设并利用强大的开源软件堆栈 创建这个档案。该档案将通过使用无边界的神经科来降低神经科学家的障碍 （NWB; http://nwb.org）标准作为一致的数据格式，通过提供与其他的互操作性 标准，以及提供强大的工具和方便的Web接口来与存档交互。丹迪 意志：1）为版本的神经生理学数据存储提供云平台 协作，存档和保存。 2）提供易于使用神经生理学数据提交的工具 并在档案中访问； 3）通过标准化应用程序促进NWB进行数据摄入， 可视化和处理。我们将与当地研究人员，更广泛的神经生理学界合作， 并有了联邦和其他资金，以确定将在Dandi存储多长时间以及哪些数据。 档案还将使用最先进的数据分发技术来增加冗余和故障 公差，并允许在云和本地计算资源上分布式计算。因此 努力将大大减少实验室与云之间的障碍，从而促进协作和数据 交换。总体而言，我们旨在利用我们的集体专业知识来创建和支持基于NWB的 神经生理档案库无缝地与当前的研究人员工作流无缝集成，降低 科学探究与协作的障碍，并保留信息以进行广泛的重复使用。