Static analysis of Taverna workflows to predict provenance patterns
Static analysis of Taverna workflows to predict provenance patterns
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对 Taverna 工作流程进行静态分析以预测来源模式
DOI：
10.1016/j.future.2017.01.004
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Alper P
中科院分区：
文献类型：
--
作者：
Alper P
Workflows have found adoption in scientific domains particularly due to their automation and provenance features. Using workflows scientists can repeat analyses with different input parameters and later use provenance to access and compare results based on these respective parameters. A common assumption is that by designing an analysis as a workflow we get parameter-to-result traceability for free by using workflow provenance. This assumption holds for cases of coarse-grained traceability where an entire workflow is subjected to repetition and all workflow parameters contribute to all results. However, this assumption is not guaranteed to hold for cases requiring finer grained traceability: where a workflow is configured with collections of parameters and analyses within a workflow are repeated with combinations of parameters from collections. In this paper we identify two dimensions that affect fine-grained traceability: (1)Factorial Design, which is the level of granularity in modelling parameters/data in workflows and in provenance that is supported by a workflow system; and (2) the practice of scientists in successfully encodingFactorial Designinto workflows. Taverna is a workflow system that provides extensive features for factorial design. However it also supports a free approach to workflow design which means that scientists may create workflows which could break traceability in provenance when they run. Using a real-world Taverna workflow we show how broken traceability manifests in provenance, rendering it ineffective for accessing workflow outputs derived from particular input parameters. In order to prevent broken traceability from occurring we describe a rule-based static analysis technique which operates over workflow descriptions and anticipates patterns in provenance. Our rules exploit the well-defined execution behaviour in the Taverna system. In order to understandFactorial Designsupport in workflow systems in general, we provide a comparative survey. We conclude that other workflow systems also provide constructs forFactorial Design, and, similar to Taverna, they too are prone to broken traceability.
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DOI：
10.1145/1346237.1346239
发表时间：
2006-11
期刊：
--
影响因子：
--
作者：
Khalid Belhajjame;S. Embury;N. Paton;R. Stevens;C. Goble
通讯作者：
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DOI：
--
发表时间：
2012
期刊：
Workshop on the Theory and Practice of Provenance
影响因子：
--
作者：
Saumen C. Dey;Sven Köhler;S. Bowers;Bertram Ludäscher
通讯作者：
Bertram Ludäscher
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DOI：
--
发表时间：
2014
期刊：
International Provenance and Annotation Workshop
影响因子：
--
作者：
Saumen C. Dey;Sven Köhler;S. Bowers;Bertram Ludäscher
通讯作者：
Bertram Ludäscher
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DOI：
--
发表时间：
2009
期刊：
Cluster Computing
影响因子：
--
作者：
V. Curcin;M. Ghanem;Yike Guo
通讯作者：
Yike Guo
影响因子：
7
作者：
Giardine, B;Riemer, C;Nekrutenko, A
通讯作者：
Nekrutenko, A