处理科学工作流的可重用性和可再现性

Sérgio Lifschitz, Luciana S. A. Gomes, S. Rehen
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引用次数: 7

摘要

科学工作流程管理系统(SWfMS)被广泛地用于表示和执行科学实验。SWfMS的一个特别的特性受到了科学界的广泛关注,那就是自动捕获来源数据。这允许用户跟踪有关哪些资源和参数用于获得此类结果的信息,以及用于验证和发布实验的其他重要信息。在目前的工作中,我们提出了一种建模和存储由SWfMS执行的工作流所消耗和产生的数据的方法。这种方法有两个主要目标:它的目的是(i)支持实验的严格再现性,以及(ii)通过保留有关其起源的信息来允许生成的工件的重用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dealing with reusability and reproducibility for scientific workflows
Scientific Workflow Management Systems (SWfMS) are being widely used to represent and execute scientific experiments. One particular SWfMS feature that has received much attention by the scientific community is the automatic capture of provenance data. This allows users to track information about which resources and parameters were used to obtain such results, but also other important information to validate and publish an experiment. In the present work, we propose an approach for modeling and storing data that is consumed and produced by workflows executed by SWfMS. This approach has two main objectives: it aims (i) to support the strict reproducibility of an experiment and (ii) to allow the reuse of produced artifacts by keeping information about its origin.
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