US-German Data Sharing: Integrating Distributed Data Resources to Enable New Research Approaches in Neuroscience

该项目寻求开发描述和管理神经科学数据的新方法，以加速神经科学许多领域的科学进步，并加深对大脑的了解。该项目将生产软件工具，以实现分布式数据的注释和集成，并帮助利用当前大型项目产生的丰富数据，如欧洲的人脑项目和美国的大脑倡议。这些结果将影响到医学应用领域，如脑机接口、传感器假体设备，以及计算机视觉等应用领域。此外，所开发的方法可能可以推广到生物学和医学的其他领域，在这些领域，传统僵化的数据组织方法是不适用的。这可能会导致发现疾病的病因和治疗方法，否则就不会有这样的发现。包含大脑活动记录的神经生理学数据正变得越来越普遍地在网络上分享，但它们仍然很难使用。为了提高共享神经生理学数据集的可用性，将开发一个标准化和可扩展的系统，用于使用理解数据所需的元数据对数据进行注释。此外，语义网技术将被用于跨网络上分散的位置来表示、索引和集成数据和元数据。改善共享神经生理学数据的元数据组织将是实现跨数据集集成的研究的关键，例如新类型的荟萃分析或数据挖掘方法。该项目建立在项目合作伙伴CRCNS.org和G-NODE.org创建的神经生理学数据的现有在线资源，以及INCF神经生理学数据共享工作队以前的工作基础上。在加州大学伯克利分校和LMU慕尼黑的年度暑期课程中培训国际学生和研究人员将改善职业机会，使不同学科的个人能够在神经科学方面取得发现和进步。德国联邦教育和研究部(BMBF)正在资助一个配套项目。

This project seeks to develop new methods of describing and managing neuroscience data in order to accelerate scientific progress in many fields of neuroscience and deepen understanding of the brain. The project will produce software tools to enable annotation and integration of distributed data and help leverage the wealth of data emerging from current large-scale projects such as the Human Brain Project in Europe and the BRAIN Initiative in the US. These results will impact medical application areas such as brain machine interfaces, devices for sensor prosthetics and also application areas such as computer vision. Further, the methods developed might be generalizable to other domains of biology and medicine where traditional rigid approaches for organizing data are inapplicable. This could lead to the discovery of causes and treatments of diseases that would not have been made otherwise.Neurophysiology data, which contain recordings of brain activity, are becoming more commonly shared on the web but they are still very hard to use. To improve the usability of shared neurophysiology data sets, a standardized and expandable system will be developed for annotating the data with metadata required for their understanding. Furthermore, semantic web technology will be employed to represent, index, and integrate data and metadata, across distributed locations on the web. Improving the organization of metadata for shared neurophysiology data will be key for enabling studies that integrate across data sets, such as new types of meta-analyses or data mining methods. This project builds on existing online resources for neurophysiology data created by the project partners, CRCNS.org and G-NODE.org, and on pervious work by the INCF neurophysiology data sharing task force. Training of international students and researchers in annual summer courses at UC Berkeley and LMU Munich will improve career opportunities that allow individuals across disciplines to make discoveries and advancements in neuroscience. A companion project is being funded by the Federal Ministry of Education and Research, Germany (BMBF).