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1 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 2 IBC - Institut de Biologie Computationnelle 3 UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales 4 LEPSE - Écophysiologie des Plantes sous Stress environnementaux 5 MISTEA - Mathématiques, Informatique et STatistique pour l-Environnement et l-Agronomie 6 ZENITH - Scientific Data Management LIRMM - Laboratoire d-Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée 7 ENSAPLV - École nationale supérieure d-architecture de Paris-La Villette 8 CRISAM - Inria Sophia Antipolis - Méditerranée 9 LRI - Laboratoire de Recherche en Informatique

Abstract : Plant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges , in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time as it is the case when phenomic traits are measured manually, such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data. In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middle-ware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained using provenance information is kept as simple as possible for end-users.

Keywords : OpenAlea Grid computing Provenance Phenomics Scientic Work ows





Autor: Christophe Pradal - Simon Artzet - Jerome Chopard - Dimitri Dupuis - Christian Fournier - Michael Mielewczik - Vincent Negre - Pa

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



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