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

项目总结/摘要 神经影像信息学工具和资源交换所（NITRC：www.nitrc.org）是一个建立在 和屡获殊荣的（2009年Excellence.gov奖和2015年HHSInnovates奖）信息库， 支持与广泛的神经成像领域及其开发人员社区相关的资源， 用户.托管在NITRC Resources（NITRC-R）上的资源包括软件、硬件和数据集， 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， 寻找，开发和共享神经成像和神经信息学软件工具的问题，寻找和 共享大规模的静息状态和结构成像数据集，并在 高性能计算环境。NITRC将继续成为一个框架，研究人员可以 识别软件和数据，并将它们无缝地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以下内容的目标来实现：1）内容和用户维护 用于已建立的NITRC-R、IR和CE环境; 2）用于完整的 开发和部署环境; 3）现有领域的内容扩展， 新的领域，适合NITRC的支持;和4）外展，文件，并支持既定的 NITRC用户群。这一持续的努力将极大地增强高性能计算向 大规模数据集正在成为神经科学研究的支柱，并促进更可重复的 通过加强资源共享，采取出版做法。

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.