On specifying and sharing scientific workflow optimization results using research objects

  • Authors:

  • Sonja Holl;Daniel Garijo;Khalid Belhajjame;Olav Zimmermann;Renato De Giovanni;Matthias Obst;Carole Goble

  • Affiliations:

  • Jülich Supercomputing Centre, Jülich, Germany;Universidad Politécnica de Madrid;University of Manchester, UK;Jülich Supercomputing Centre, Jülich, Germany;Reference Center on Environmental Information, Campinas SP, Brazil;University of Gothenburg, Sweden;University of Manchester, UK

  • Venue:
  • WORKS '13 Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science
  • Year:
  • 2013

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Abstract

Reusing and repurposing scientific workflows for novel scientific experiments is nowadays facilitated by workflow repositories. Such repositories allow scientists to find existing workflows and re-execute them. However, workflow input parameters often need to be adjusted to the research problem at hand. Adapting these parameters may become a daunting task due to the infinite combinations of their values in a wide range of applications. Thus, a scientist may preferably use an automated optimization mechanism to adjust the workflow set-up and improve the result. Currently, automated optimizations must be started from scratch as optimization meta-data are not stored together with workflow 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 real-world use case taken from the biodivertsity domain, and discuss the exploitation of our solution in the context of existing e-Science infrastructures.