Collaborative Scientific Workflow Composition as a Service: An Infrastructure Supporting Collaborative Data Analytics Workflow Design and Management

Jia Zhang, Q. Bao, Xiaoyi Duan, Shiyong Lu, Lijun Xue, Runyu Shi, P. Tang
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引用次数: 5

Abstract

The need for collaborative data analytics increases significantly when confronted with the challenges of big data. Although workflow tools offer a formal way to define, automate, and repeat multi-step computational procedures, designing complex data processing workflow requires collaboration from multiple people with complementary expertise. Existing tools are not suitable to support collaborative design of comprehensive workflows. To address such a challenge, this paper reports the design and development of a software infrastructure with the capability of supporting collaborative data-oriented workflow composition and management, adding a key component to existing cyberinfrastructure that will support big data collaboration through the Internet. A collaborative provenance query model (CPM) is presented together with graph-based patterns and algebra. A hypergraph theory-based provenance mining technique is reported. The research extends an existing open-source workflow tool, by adding system-level facilities to support human interaction and cooperation that are essential for an effective and efficient scientific collaboration.
协同科学工作流组合即服务:支持协同数据分析工作流设计和管理的基础设施
面对大数据的挑战,协作数据分析的需求显著增加。尽管工作流工具提供了一种正式的方式来定义、自动化和重复多步计算过程,但设计复杂的数据处理工作流需要来自具有互补专业知识的多个人员的协作。现有的工具不适合支持全面工作流的协作设计。为了应对这一挑战,本文报告了软件基础设施的设计和开发,该软件基础设施具有支持协作数据导向工作流组合和管理的能力,为现有的网络基础设施增加了一个关键组件,该组件将通过互联网支持大数据协作。提出了一种基于图的模式和代数的协同溯源查询模型(CPM)。报道了一种基于超图理论的物源挖掘技术。该研究扩展了现有的开源工作流工具,增加了系统级设施,以支持对有效和高效的科学协作至关重要的人类交互和合作。
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