DataFed：通过联邦数据管理实现可重复研究
DataFed: Towards Reproducible Research via Federated Data Management
摘要：
科学研究的日益协作和全球化的性质，加上需要共享数据和数据量的爆炸式增长，迫切需要一个科学数据管理系统。一个SDMS提出了一个逻辑和整体的数据视图，大大简化和授权数据组织，策展，搜索，共享，传播等，我们提出DataFed -一个轻量级的，分布式的SDMS，跨越一个松散耦合的科学设施网络内的存储系统的联邦。与现有的SDMS产品不同，DataFed使用高性能和可扩展的用户管理和数据传输技术，简化了DataFed的部署、维护和扩展。DataFed提供基于Web和命令行的界面来管理数据并与复杂的科学工作流程集成。DataFed通过在所需环境中可靠地分段正确的数据，代表了迈向可重复科学研究的一步。
英文摘要：
The increasingly collaborative, globalized nature of scientific research combined with the need to share data and the explosion in data volumes present an urgent need for a scientific data management system (SDMS). An SDMS presents a logical and holistic view of data that greatly simplifies and empowers data organization, curation, searching, sharing, dissemination, etc. We present DataFed -- a lightweight, distributed SDMS that spans a federation of storage systems within a loosely-coupled network of scientific facilities. Unlike existing SDMS offerings, DataFed uses high-performance and scalable user management and data transfer technologies that simplify deployment, maintenance, and expansion of DataFed. DataFed provides web-based and command-line interfaces to manage data and integrate with complex scientific workflows. DataFed represents a step towards reproducible scientific research by enabling reliable staging of the correct data at the desired environment.
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