基于Duckling协作库(CLB)的生物医学研究数据云服务

Kejun Dong, Ji Li, Kai Nan, Wilfred W. Li
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引用次数: 0

摘要

科学研究的快速发展导致了前所未有的数据泛滥,并在数据互操作性、认证和协作方面带来了重大挑战。协作库(CLB)旨在通过建立统一、健壮和可扩展的数据存储库来管理和整理数百万个数据文件,特别是支持实验性数据协作和基于时间轴的数据生命周期管理。它最近作为Duckling的一个组件发布,Duckling是一个由中国科学院(CAS)开发的开源协作环境工具包,在许多学科中被广泛采用。在本文中,我们介绍了在更新的CLB体系结构中用于数据同步和快照的新开发组件。我们还使用新的数据云服务模块(CLB+)扩展了CLB,这些模块支持从云到用户工作空间的数据映射和同步。CLB+是作为CLB插件实现的,CLB插件提供来自计算机辅助药物发现(CADD)工作流的生物医学研究云服务接口,用于基于集成的虚拟筛选。CLB灵活的插入式架构使生物医学研究数据云环境原型的开发变得非常容易。许多其他电子科学应用程序可能以类似的方式利用或扩展数据生命周期管理中的CLB功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biomedical Research Data Cloud Services with Duckling Collaboration LiBrary (CLB)
Rapid advances in scientific research have led to unprecedented data deluge and significant challenges in data interoperability, certification and collaboration. The Collaboration LiBrary (CLB) is designed to manage and collate millions of data files by setting up a unified, robust, and scalable data repository, especially in support of experimental data collaboration and timeline-based data life cycle management. It has recently been released as a component of Duckling, an open-source collaboration environment toolkit developed by the Chinese Academy of Sciences (CAS) and widely adopted in many disciplines. In this paper, we present newly developed components for data synchronization and snapshots in an updated architecture for CLB. We have also extended CLB with new data cloud service modules (CLB+) that enables data mapping and synchronization from the cloud to user workspace. CLB+ is implemented as CLB plugins that provide interfaces with biomedical research cloud services from a computer aided drug discovery (CADD) workflow for ensemble-based virtual screening. The flexible plug in architecture of CLB makes it easy to develop a prototype biomedical research data cloud environment. Many other e-science applications may leverage or expand CLB functionalities in data life cycle management in a similar fashion.
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