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FragFlow: automated fragment detection in scientific workflows
Garijo Verdejo, Daniel and Corcho, Oscar and Gil, Yolanda and Gutman, Boris A. and Dinov, Ivo D. and Thompson, Paul and Toga, Arthur W.
FragFlow: automated fragment detection in scientific workflows.
In: "10th IEEE International Conference on e-Science", 20-24 Oct 2014, Guaruja, Sao Paulo, Brasil. ISBN 978-1-4799-4288-6. pp. 281-290.
||FragFlow: automated fragment detection in scientific workflows
Garijo Verdejo, Daniel
Gutman, Boris A.
Dinov, Ivo D.
Toga, Arthur W.
Presentation at Congress or Conference
||10th IEEE International Conference on e-Science
||20-24 Oct 2014
||Guaruja, Sao Paulo, Brasil
|Title of Book:
||eScience 2014: proceedings
||Scientific workflow; Workflow fragment; Workflow
reuse; LONI pipeline
||E.T.S. de Ingenieros Informáticos (UPM)
|Creative Commons Licenses:
||Recognition - No derivative works - Non commercial
Scientific workflows provide the means to define,
execute and reproduce computational experiments. However,
reusing existing workflows still poses challenges for workflow
designers. Workflows are often too large and too specific to reuse
in their entirety, so reuse is more likely to happen for fragments
of workflows. These fragments may be identified manually by
users as sub-workflows, or detected automatically. In this paper
we present the FragFlow approach, which detects workflow
fragments automatically by analyzing existing workflow corpora
with graph mining algorithms. FragFlow detects the most
common workflow fragments, links them to the original
workflows and visualizes them. We evaluate our approach by
comparing FragFlow results against user-defined sub-workflows
from three different corpora of the LONI Pipeline system. Based
on this evaluation, we discuss how automated workflow fragment
detection could facilitate workflow reuse.
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