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: 9981835
• 负责人: Satrajit Sujit Ghosh
• 金额: $ 127.76万
• 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/9981835
• 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; 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; 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 ingestion; data integration; data submission; diverse data; experience; experimental study; high school; interoperability; large datasets; 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.

神经科学数据包含来自令人难以置信的物种多样性的信息，是由大量的 设备，并封装科学思维和决策的结果。这些生成的大部分数据 这些信息仍然局限在实验室内，无法向更广泛的科学界提供。研究 根据大脑计划授予的项目正在产生各种各样的数据，这些数据可以改变和 加快发现的步伐。这些数据集很大，大小从GB到PB不等， 不同的数据类型和各种元数据。整合而不是进一步孤立， 需要以一种对神经科学有意义的方式来归档、保存、共享和处理数据 研究人员任何技术解决方案都应该减少存储和计算的冗余， 计算近距离数据，并为研究人员或公民提供方便但在适当时受到保护的访问 科学家考虑到这些计划的规模以及样本大小和数据类型的范围，任何解决方案都应该 还考虑到社区中广泛的个人技术专长，因此可以轻松地 参与和吸收档案，同时支持教育和培训科学家， 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。我们利用我们团队在信息学、标准化、 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。该档案将通过使用神经数据无国界为神经科学家降低障碍 (NWB; http://nwb.org）标准作为一致的数据格式，通过提供与其他 标准，并通过提供强大的工具和方便的Web界面与存档进行交互。丹迪 将：1）为版本化神经生理学数据存储提供云平台， 协作、归档和保存。2)提供易于使用的神经生理学数据提交工具 以及在档案中的访问;以及3）通过用于数据摄取的标准化应用程序促进NWB的采用， 可视化和处理。 我们将与当地的研究人员，更广泛的神经生理学社区， 并与联邦和其他资助者确定数据将在DANDI存储多久以及哪些数据。 档案馆还将使用最先进的数据分发技术，以增加冗余和故障 容差，并允许跨云和本地计算资源的分布式计算。从而 这项工作将大大减少实验室和云之间的障碍，促进协作和数据 交易所总体而言，我们的目标是利用我们的集体专业知识，建立和支持一个基于新世界银行的 神经生理学档案与当前研究人员工作流程无缝集成并增强， 科学探究和合作的障碍，并保存信息以供广泛重用。