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Scientific Workflows: Moving Across Paradigms

Published: 12 December 2016 Publication History
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  • Abstract

    Modern scientific collaborations have opened up the opportunity to solve complex problems that require both multidisciplinary expertise and large-scale computational experiments. These experiments typically consist of a sequence of processing steps that need to be executed on selected computing platforms. Execution poses a challenge, however, due to (1) the complexity and diversity of applications, (2) the diversity of analysis goals, (3) the heterogeneity of computing platforms, and (4) the volume and distribution of data.
    A common strategy to make these in silico experiments more manageable is to model them as workflows and to use a workflow management system to organize their execution. This article looks at the overall challenge posed by a new order of scientific experiments and the systems they need to be run on, and examines how this challenge can be addressed by workflows and workflow management systems. It proposes a taxonomy of workflow management system (WMS) characteristics, including aspects previously overlooked. This frames a review of prevalent WMSs used by the scientific community, elucidates their evolution to handle the challenges arising with the emergence of the “fourth paradigm,” and identifies research needed to maintain progress in this area.

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    cover image ACM Computing Surveys
    ACM Computing Surveys  Volume 49, Issue 4
    December 2017
    666 pages
    ISSN:0360-0300
    EISSN:1557-7341
    DOI:10.1145/3022634
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    • Sartaj Sahni
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    © 2016 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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    Publication History

    Published: 12 December 2016
    Accepted: 01 September 2016
    Revised: 01 May 2016
    Received: 01 March 2015
    Published in CSUR Volume 49, Issue 4

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