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Descripción
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| Reusing and repurposing scienti?c work ows for novel scienti ?c experiments is nowadays facilitated by work ow repositories. Such repositories allow scientists to ?nd existing work ows and re-execute them. However, work ow input parameters often need to be adjusted to the research problem at hand. Adapting these parameters may become a daunting task due to the in?nite combinations of their values in a wide range of applications. Thus, a scientist may preferably use an automated optimization mechanism to adjust the work- ow set-up and improve the result. Currently, automated optimizations must be started from scratch as optimization meta-data are not stored together with work ow provenance data. This important meta-data is lost and can neither be reused nor assessed by other researchers. In this paper we present a novel approach to capture optimization meta-data by extending the Research Object model and reusing the W3C standards. We validate our proposal through a realworld use case taken from the biodivertsity domain, and discuss the exploitation of our solution in the context of existing e-Science infrastructures. | |
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Internacional
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Si |
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Nombre congreso
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the 8th Workshop on Workflows in Support of Large-Scale Science at SC13 International Conference for High Performance Computing, Networking, Storage and Analysis |
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Tipo de participación
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960 |
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Lugar del congreso
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Denver, Colorado USA |
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Revisores
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Si |
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ISBN o ISSN
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978-1-4503-2502-8 |
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DOI
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Fecha inicio congreso
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17/11/2013 |
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Fecha fin congreso
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17/11/2013 |
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Desde la página
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28 |
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Hasta la página
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37 |
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Título de las actas
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Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science |