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1 ZENITH - Scientific Data Management LIRMM - Laboratoire d-Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée 2 LRI - Laboratoire de Recherche en Informatique 3 IBC - Institut de Biologie Computationnelle 4 LAMSADE - Laboratoire d-analyse et modélisation de systèmes pour l-aide à la décision 5 Plateforme bioinformatique GenOuest Rennes UR1 - Université de Rennes 1, Plateforme Génomique Santé Biogenouest®, Inria Rennes – Bretagne Atlantique , IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires 6 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, Centre de coopération internationale en recherche agronomique pour le développement CIRAD : UMR51 7 CHU Nantes 8 SSOLEIL - Synchrotron SOLEIL 9 DIADE - Diversité, adaptation, développement des plantes 10 Institut Pasteur Paris 11 UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales 12 IFB-CORE - Institut Français de Bioinformatique - UMS CNRS 3601

Abstract : 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 repro-ducibility 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.

Keywords : Reproducibility Scientific Workflows Provenance Packaging environments





Autor: Sarah Cohen-Boulakia - Khalid Belhajjame - Olivier Collin - Jérôme Chopard - Christine Froidevaux - Alban Gaignard - Konrad Hin

Fuente: https://hal.archives-ouvertes.fr/



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