Mining Workflow Repositories for Improving Fragments Reuse

Harmassi, Mariem; Grigori, Daniela; Belhajjame, Khalid

doi:10.1007/978-3-319-27932-9_7

Cited by 4 publications

(1 citation statement)

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“…First-of-all, in the previous section, approaches such as [66,67,68] have been mentioned as possibilities to reduce the complexity of workflows and make them easier to understand, allowing to hide over technical parts of workflows. Other approaches either reduce the (structural) complexity of workflows, by detecting fragments to be modified such as DistillFlow [73](dedicated to Taverna) or have mined workflow fragments to be reused [74]. More generally speaking, there is a crucial need to imagine approaches and provide concrete tools able to guide workflow design, with the aim of providing reproducible-friendly workflows that are reusable.…”

Section: On Workflow Reuse and Reproducibilitymentioning

confidence: 99%

Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities

Cohen-Boulakia

Belhajjame

Collin

et al. 2017

Future Generation Computer Systems

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With the development of new experimental technologies, biologists are faced with an avalanche of data to be computationally analyzed for scientific advancements and discoveries to emerge. Faced with the complexity of analysis pipelines, the large number of computational tools, and the enormous amount of data to manage, there is compelling evidence that many if not most scientific discoveries will not stand the test of time: increasing the reproducibility of computed results is of paramount importance. The objective we set out in this paper is to place scientific workflows in the context of reproducibility. To do so, we define several kinds of reproducibility that can be reached when scientific workflows are used to perform experiments. We characterize and define the criteria that need to be catered for by reproducibility-friendly scientific workflow systems, and use such criteria to place several representative and widely used workflow systems and companion tools within such a framework. We also discuss the remaining challenges posed by reproducible scientific workflows in the life sciences. Our study was guided by three use cases from the life science domain involving in silico experiments. (Résumé d'auteur

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Section: On Workflow Reuse and Reproducibilitymentioning

confidence: 99%