@inproceedings{86d61b59bd354e1c81b19ab287df0ae2,
title = "FragFlow automated fragment detection in scientific workflows",
abstract = "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.",
keywords = "LONI pipeline, scientific workflow, workflow fragment, workflow reuse",
author = "Daniel Garijo and Oscar Corcho and Yolanda Gil and Gutman, {Boris A.} and Dinov, {Ivo D.} and Paul Thompson and Toga, {Arthur W.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 10th IEEE International Conference on eScience, eScience 2014 ; Conference date: 20-10-2014 Through 24-10-2014",
year = "2014",
month = dec,
day = "2",
doi = "10.1109/eScience.2014.32",
language = "English",
series = "Proceedings - 2014 IEEE 10th International Conference on eScience, eScience 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "281--289",
booktitle = "Proceedings - 2014 IEEE 10th International Conference on eScience, eScience 2014",
address = "United States",
}