Advanced Computer Architectures Group, Department of Computer Science, University of York, Heslington, York YO10 5DD, UK.
Philos Trans A Math Phys Eng Sci. 2010 Sep 13;368(1926):4147-59. doi: 10.1098/rsta.2010.0147.
The Code Analysis Repository & Modelling for E-Neuroscience (CARMEN) project aims to enable broad sharing of resources, through the provision of a secure, online environment for storage and curation of data, analysis code and experimental protocols, together with the ability to execute data analysis. While the CARMEN system is initially focused on electrophysiology data, it is equally applicable to many domains outside neuroscience. Metadata are essential for a system such as CARMEN that has the potential to store thousands of data collections and analysis codes; without metadata, resource discovery, interpretation, evaluation and re-use would be severely impeded. Therefore, when any resource (data, service or workflow) is added to the system, users must provide adequate descriptions. These descriptions form a metadata repository that is searchable to allow users to find any kind of resource held in the system, assuming that the user has appropriate access rights. This paper discusses and explores the project's approach to implementing such a metadata repository that meets both system requirements and user expectations. Initial approaches were refined after user evaluations, and a more practical approach was followed that better aligned with the aims of the users and the project as a whole.
电子神经科学资源分析与建模(CARMEN)项目旨在通过提供一个安全的在线环境来存储和管理数据、分析代码和实验方案,并执行数据分析,从而实现资源的广泛共享。虽然 CARMEN 系统最初专注于电生理学数据,但它同样适用于神经科学以外的许多领域。对于像 CARMEN 这样的系统来说,元数据是必不可少的,因为它有可能存储数千个数据集和分析代码;如果没有元数据,资源发现、解释、评估和重用将受到严重阻碍。因此,当向系统添加任何资源(数据、服务或工作流)时,用户必须提供足够的描述。这些描述构成了一个可搜索的元数据存储库,允许用户查找系统中保存的任何类型的资源,前提是用户具有适当的访问权限。本文讨论并探讨了该项目实现符合系统要求和用户期望的元数据存储库的方法。在用户评估后,对初始方法进行了改进,并采用了更实用的方法,使其更符合用户和整个项目的目标。