使用Whole Tale平台实现数据密集型研究的复制
Toward Enabling Reproducibility for Data-Intensive Research using the Whole Tale Platform
摘要：
Whole Tale http://wholetale.org是一个基于网络的开源平台，用于支持科学研究社区的“故事”的创建，共享，执行和验证。故事是可执行的研究对象，捕获代码，数据和环境以及重新创建科学研究计算结果所需的叙述和工作流程信息。创建可再现的研究对象，使再现性，透明度和重新执行的计算实验需要大量的计算资源或利用海量数据是一个特别具有挑战性的开放问题。我们描述了机遇，挑战和解决方案，以促进数据和计算密集型研究的可重复性，我们称之为“规模的故事”，使用整个故事计算平台。我们强调了前端响应需求方面的挑战和解决方案，当前中间件设计和实现的差距，网络限制，容器化和数据访问。最后，我们讨论了在包装便携式数据密集型故事计算实验实现的挑战，并概述了未来的工作。
英文摘要：
Whole Tale http://wholetale.org is a web-based, open-source platform for reproducible research supporting the creation, sharing, execution, and verification of "Tales" for the scientific research community. Tales are executable research objects that capture the code, data, and environment along with narrative and workflow information needed to re-create computational results from scientific studies. Creating reproducible research objects that enable reproducibility, transparency, and re-execution for computational experiments requiring significant compute resources or utilizing massive data is an especially challenging open problem. We describe opportunities, challenges, and solutions to facilitating reproducibility for data- and compute-intensive research, that we call "Tales at Scale," using the Whole Tale computing platform. We highlight challenges and solutions in frontend responsiveness needs, gaps in current middleware design and implementation, network restrictions, containerization, and data access. Finally, we discuss challenges in packaging computational experiment implementations for portable data-intensive Tales and outline future work.
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