Data Science Core

数据科学核心

• 批准号: 10696188
• 负责人: Tatyana O. SHARPEE
• 金额: $ 23.47万
• 依托单位: SALK INSTITUTE FOR BIOLOGICAL STUDIES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10696188
• 关键词: 3-Dimensional; Anatomy; Architecture; Atlases; Behavior; Cells; Cervical; Cervical spinal cord structure; Cervical spine; Communities; Consumption; Coupled; Data; Data Files; Data Science Core; Data Set; Elbow; Electrophysiology (science); Ensure; Forelimb; Foundations; Gene Expression; Goals; Image; Individual; Industry Standard; Information Dissemination; Infrastructure; Internet; Interneurons; Joints; Kinetics; Label; Limb structure; Maps; Measurement; Measures; Mechanics; Metadata; Modeling; Molecular; Motor; Motor Activity; Motor Neurons; Movement; Mus; Muscle; Musculoskeletal; Neurons; Neurosciences; Physiological; Positioning Attribute; Protocols documentation; Research Project Grants; Resources; Services; Side; Spinal; Synapses; System; Techniques; Thoracic spinal cord structure; Vertebral column; Viral; Visualization; Visualization software; Wild Type Mouse; Work; Wrist; base; cloud storage; data dissemination; data format; data sharing; data sharing networks; data visualization; design; digital; digital object identifier; experimental study; in vivo; kinematics; limb movement; member; models and simulation; mouse genetics; multimodality; open source; operation; optogenetics; recruit; sharing platform; single-cell RNA sequencing; tool; transcriptome sequencing; user-friendly; web based interface; web based software

Project Summary: Data Science Resource Core The central purpose of the Data Science Resource Core is to construct and implement digital infrastructure that can warehouse, integrate, visualize, and allow interaction with the data products of the three specific aims. This digital infrastructure will be implemented in the form of a multi-tier services-oriented architecture, reusing an open source neuroscience data sharing platform. Where possible, industry standard third party tools and services will be leveraged as a foundation for our work, to avoid rebuilding any components that are already well designed and easy to use. The products of the other Research Projects will be collected via protocols that are amenable to digital representation. These will then be unified via spatial registration in a common coordinate system. Ensuring that the data have appropriate landmarks and that measurements of the spatial extent of key images is a core operation for this endeavor. With data whose content are appropriate for unification, it will subsequently be determined which digital format representation is most appropriate for each data type, with the goal of making them easy to present in an online interface for the consumption of the broader scientific community. Data files with the appropriate format will be made available on cloud storage on the public internet. From here, a user-friendly web-based interface will be designed and implemented on top of a platform for neuroscience data visualization, that itself reuses best-in-class open source visualization software for the web. The interface will ensure that users can easily navigate between individual data sets and also can visualize relationships between data sets across the domains from the other Research Projects. The interface will enable the user to explore data collected about the major interneuron classes, as well as neurons in the major motor pools via mouse click. To encourage broad sharing of the data resources we produce, high quality metadata will be created to include with the data that conveys its provenance. Data products will be enabled to have their own digital object identifiers (DOIs), incorporate compatibility with ORCID ids, and embed RRIDs into the system as necessary. Core data products will further be shared through key federally supported data sharing resources and by applying best practices to data format and dissemination techniques used.

项目摘要：数据科学资源核心 数据科学资源核心的核心目的是构建和实施数字基础架构 这可以仓库，整合，可视化并允许与三个特定目标的数据产品进行交互。 该数字基础架构将以多层服务架构的形式实施 开源神经科学数据共享平台。在可能的情况下，行业标准的第三方工具和 服务将被利用为我们工作的基础，以避免重建所有已经存在的组件 精心设计且易于使用。其他研究项目的产品将通过协议收集 适合数字代表。然后，这些将通过共同的空间注册统一 坐标系。确保数据具有适当的地标和空间的测量 关键图像的程度是这项工作的核心操作。与内容适合的数据 统一，随后将确定哪种数字格式表示最适合每个形式 数据类型，目的是使它们易于在在线界面中呈现以供消耗 更广泛的科学界。具有适当格式的数据文件将在云存储上提供 公共互联网。从这里开始，将设计和实现一个基于Web的用户友好型界面 神经科学数据可视化的平台，该平台本身可以重用一流的开源可视化 网络软件。该界面将确保用户可以轻松地在各个数据集之间导航和 还可以从其他研究项目中可视化整个域之间数据集之间的关系。这 接口将使用户能够探索有关主要中间神经元类的数据以及神经元 在主要的电机池中，通过鼠标命中。为了鼓励广泛共享我们生产的数据资源，高 将创建质量元数据，以包括传达其出处的数据。数据产品将是 启用了自己的数字对象标识符（DOIS），将兼容性与OrcID ID合并，并嵌入 必要时进入系统。核心数据产品将通过关键联邦支持进一步共享 数据共享资源并通过将最佳实践应用于所使用的数据格式和传播技术。