Data Science Core

数据科学核心

• 批准号: 9815386
• 负责人: Tatyana O. SHARPEE
• 金额: $ 31.95万
• 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/9815386
• 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; Data Set; Dimensions; Elbow; Electrophysiology (science); Ensure; Forelimb; Foundations; Gene Expression; Genetic; Goals; Image; Imagery; 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; Resource Sharing; Resources; Services; Side; Spinal; System; Techniques; Thoracic spinal cord structure; Viral; Visualization software; Work; Wrist; base; cloud storage; data format; data science resource; data sharing; data visualization; design; digital; digital object identifier; experimental study; in vivo; kinematics; limb movement; member; models and simulation; multimodality; open source; operation; optogenetics; recruit; single-cell RNA sequencing; tool; transcriptome sequencing; user-friendly; web based interface

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.

项目总结：数据科学资源核心