Scientific Workflows: Business as Usual?
Identifieur interne : 000371 ( Istex/Curation ); précédent : 000370; suivant : 000372Scientific Workflows: Business as Usual?
Auteurs : Bertram Lud Scher [États-Unis] ; Mathias Weske [Allemagne] ; Timothy Mcphillips [États-Unis] ; Shawn Bowers [États-Unis]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2009.
Abstract
Abstract: Business workflow management and business process modeling are mature research areas, whose roots go far back to the early days of office automation systems. Scientific workflow management, on the other hand, is a much more recent phenomenon, triggered by (i) a shift towards data-intensive and computational methods in the natural sciences, and (ii) the resulting need for tools that can simplify and automate recurring computational tasks. In this paper, we provide an introduction and overview of scientific workflows, highlighting features and important concepts commonly found in scientific workflow applications. We illustrate these using simple workflow examples from a bioinformatics domain. We then discuss similarities and, more importantly, differences between scientific workflows and business workflows. While some concepts and solutions developed in one domain may be readily applicable to the other, there remain sufficiently many differences that warrant a new research effort at the intersection of scientific and business workflows. We close by proposing a number of research opportunities for cross-fertilization between the scientific workflow and business workflow communities.
Url:
DOI: 10.1007/978-3-642-03848-8_4
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<front><div type="abstract" xml:lang="en">Abstract: Business workflow management and business process modeling are mature research areas, whose roots go far back to the early days of office automation systems. Scientific workflow management, on the other hand, is a much more recent phenomenon, triggered by (i) a shift towards data-intensive and computational methods in the natural sciences, and (ii) the resulting need for tools that can simplify and automate recurring computational tasks. In this paper, we provide an introduction and overview of scientific workflows, highlighting features and important concepts commonly found in scientific workflow applications. We illustrate these using simple workflow examples from a bioinformatics domain. We then discuss similarities and, more importantly, differences between scientific workflows and business workflows. While some concepts and solutions developed in one domain may be readily applicable to the other, there remain sufficiently many differences that warrant a new research effort at the intersection of scientific and business workflows. We close by proposing a number of research opportunities for cross-fertilization between the scientific workflow and business workflow communities.</div>
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