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| Hauptseite > Publikationsdatenbank > On specifying and sharing scientific workflow optimization results using research objects > print |
| Hauptseite > Publikationsdatenbank > On specifying and sharing scientific workflow optimization results using research objects > print |
| 001 | 276255 | ||
| 005 | 20210129220827.0 | ||
| 024 | 7 | _ | |a 10.1145/2534248.2534251 |2 doi |
| 037 | _ | _ | |a FZJ-2015-06718 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Holl, Sonja |0 P:(DE-Juel1)132139 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a 8th Workshop on Workflows in Support of Large-Scale Science |g WORKS 2013 |c Denver |d 2013-11-17 - 2013-11-17 |w Colorado |
| 245 | _ | _ | |a On specifying and sharing scientific workflow optimization results using research objects |
| 260 | _ | _ | |c 2013 |b ACM Press New York, New York, USA |
| 295 | 1 | 0 | |a 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 |
| 300 | _ | _ | |a 28-37 |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1448364502_32101 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 520 | _ | _ | |a 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. |
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| 700 | 1 | _ | |a Garijo, Daniel |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Belhajjame, Khalid |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Zimmermann, Olav |0 P:(DE-Juel1)132307 |b 3 |u fzj |
| 700 | 1 | _ | |a De Giovanni, Renato |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Obst, Matthias |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Goble, Carole |0 P:(DE-HGF)0 |b 6 |
| 773 | _ | _ | |a 10.1145/2534248.2534251 |
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