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@INPROCEEDINGS{Holl:276255,
      author       = {Holl, Sonja and Garijo, Daniel and Belhajjame, Khalid and
                      Zimmermann, Olav and De Giovanni, Renato and Obst, Matthias
                      and Goble, Carole},
      title        = {{O}n specifying and sharing scientific workflow
                      optimization results using research objects},
      publisher    = {ACM Press New York, New York, USA},
      reportid     = {FZJ-2015-06718},
      pages        = {28-37},
      year         = {2013},
      comment      = {Proceedings of the 8th Workshop on Workflows in Support of
                      Large-Scale Science - WORKS '13 - ACM Press New York, New
                      York, USA, 2013. - ISBN 9781450325028 -
                      doi:10.1145/2534248.2534251},
      booktitle     = {Proceedings of the 8th Workshop on
                       Workflows in Support of Large-Scale
                       Science - WORKS '13 - ACM Press New
                       York, New York, USA, 2013. - ISBN
                       9781450325028 -
                       doi:10.1145/2534248.2534251},
      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.},
      month         = {Nov},
      date          = {2013-11-17},
      organization  = {8th Workshop on Workflows in Support
                       of Large-Scale Science, Denver
                       (Colorado), 17 Nov 2013 - 17 Nov 2013},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {899 - ohne Topic (POF3-899)},
      pid          = {G:(DE-HGF)POF3-899},
      typ          = {PUB:(DE-HGF)8},
      doi          = {10.1145/2534248.2534251},
      url          = {https://juser.fz-juelich.de/record/276255},
}