Collaborative Brain Mapping: Tools for Sharing

描述（由申请人提供）：研究中心之间的数据共享对于当代脑成像研究越来越重要，因为它们涉及大量的受试者和复杂的分析协议，需要高度专业化的专业知识。我们的长期目标是通过使远程研究人员能够在机构之间共享数据并使用在分布式资源上执行的适当算法分析数据来促进脑成像研究。有许多困难的数据管理和技术挑战限制了数据共享环境的成功。而不是试图开发一个全面的和一般的解决方案，我们建议开发一套开放的，可互操作的，可移植的软件工具，解决目前限制努力共享和分析脑成像数据的关键问题。基于多年来为合作者提供脑成像专业知识的基础上，我们提出解决我们反复遇到的问题，这些问题目前限制了脑成像研究的进展。我们建议开发经过验证的工具，使合作者能够远程访问各种数据分析方法和数据库。我们将创建基于Web的工具来执行多机构研究，并提供对在分布式计算资源上执行的复杂数据处理协议的访问。有三个具体目标。1)利用访问控制系统实现基于网络的数据采集和管理，包括考虑受试者知情同意限制和研究者施加的条件，以促进多机构研究的数据汇集。该系统将在不同格式和模式之间转换数据文件，以便数据可以在分析程序和数据库之间一致地使用。它还将根据机构特定的协议对图像和元数据进行匿名处理。2)开发一个知道数据类型和出处的系统，以便它可以智能地在不同的分析程序之间进行仲裁。该系统将收集经验丰富的实验室人员在使用各种工具方面的专业知识，并协助新用户设计适当的分析策略。3)创建元算法，通过智能地组合来自多个算法的结果来提高神经成像分析技术的鲁棒性。拟议办法将提供一套工具，解决数据共享和利用方面的重大问题。由此产生的信息技术将是可扩展的，并适用于其他科学数据共享问题。

DESCRIPTION (provided by applicant): Sharing data between research centers is increasingly important for contemporary brain imaging studies because they involve large numbers of subjects and complex analysis protocols that require highly specialized expertise. Our long-term objective is to facilitate brain-imaging research by enabling remote researchers to pool data between institutions and to analyze data using the appropriate algorithms executing on distributed resources. There are a number of difficult data management and technology challenges that have limited the success of data sharing environments. Rather than attempt to develop a comprehensive and general solution, we propose to develop a set of open, interoperable, and portable software tools that address critical issues currently limiting efforts to share and analyze brain-imaging data. Building upon years of providing brain-mapping expertise to collaborators, we propose to solve problems that we repeatedly encounter and that currently limit progress in brain imaging research. We propose to develop validated tools that enable collaborators to remotely access a variety of data analysis methods and databases. We will create web-based tools to perform multi-institutional studies, and provide access to complex data processing protocols executing on distributed computing resources. There are three specific aims. 1) Enable the web based acquisition and management of data utilizing an access control system that includes consideration of subject consent limits and investigator imposed conditions to facilitate data pooling for multi-institutional studies. This system will convert data files between different formats and schemas so that data can be used consistently between analysis programs and databases. It will also anonymize images and metadata according to institution-specific protocols. 2) Develop a system that is aware of data type and provenance so that it may act intelligently to arbitrate between different analysis programs. This system will capture the expertise of experienced lab personnel in the usage of various tools and assist new users in designing appropriate analytic strategies. 3) Create meta-algorithms that improve the robustness of techniques for neuroimaging analysis by intelligently combining the results from multiple algorithms. The proposed approach will provide a set of tools that address significant problems in data sharing and utilization. The resulting information technology will be scalable and applicable to other scientific data sharing problems.