Neuroimaging Informatics Tools and Resources Clearinghouse Outreach, Infrastructure, and Content Maintenance

项目摘要/摘要 神经影像信息学工具和资源信息中心(NITRC：www.nitrc.org)是一个成熟的 和获奖(2009年度卓越政府奖和2015年度HHSInnovates奖)的信息和 支持与广泛的神经成像领域及其开发人员和社区相关的资源 用户。NITRC资源(NITRC-R)上托管的资源包括软件、硬件和数据集，其中 其他资产。NITRC的目的是为神经科学研究人员提供一个完整的解决方案 查找、开发和共享神经成像和神经信息学软件工具、查找和 共享大规模静息状态和结构成像数据集，并在 高性能计算环境。NITRC将继续作为一个框架，研究人员可以 识别软件和数据，并将其无缝交付给基于云的计算资源进行处理。 这将通过执行旨在提供：1)内容和用户维护的目标来实现 用于已建立的NITRC-R、IR和CE环境；2)基础设施维护 开发和部署环境；3)现有域中的内容扩展，并确定 可以接受NITRC支持的新领域；以及4)对已建立的 NITRC用户群。这一持续的努力将极大地增强向 大规模数据集正在成为神经科学研究的中流砥柱，并促进更具可重复性 通过加强资源共享，开展出版活动。

Project Summary/Abstract The Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC: www.nitrc.org) is an established and award-winning (2009 Excellence.gov award and 2015 HHSInnovates award) repository of information and support for resources relevant to a broad set of neuroimaging domains and their communities of developers and users. Resources hosted on NITRC Resources (NITRC-R) include software, hardware, and datasets, among other assets. The purpose of NITRC is to provide neuroscience researchers with a complete solution to the problem of finding, developing, and sharing neuroimaging and neuroinformatics software tools, finding and sharing large-scale resting state and structural imaging datasets, and manipulating the software and the data in high-performance computing environments. NITRC will continue to be a framework where researchers can identify software and data and seamlessly deliver them to a cloud-based computational resource for processing. This will be accomplished through the execution of aims designed to provide: 1) Content and user maintenance for the established NITRC-R, IR and CE environments; 2) infrastructure maintenance for the complete development and deployment environments; 3) content expansion in the existing domains, and identification of new areas that are amenable to NITRC support; and 4) outreach, documentation, and support for the established NITRC user base. This continued effort will greatly enhance the delivery of high-performance computing to the large-scale datasets that are becoming the mainstay of neuroscience research and promote more reproducible publication practices through enhanced resource sharing.