A scientific workflow is the description of a process for accomplishing a scientific objective, usually expressed in terms of tasks and their dependencies [5]. While workflows have a long history in the database community as well as in business process modeling (where they are also known as business workflows), and despite some early works on scientific workflows [3,10], the area has only recently begun to fully flourish (e.g., see [1,2,9,7,4,11]). Similar to scientific data management which has different characteristics from traditional business data management [8], scientific workflows exhibit new challenges and opportunities that distinguish them from business workflows. We present an overview of these challenges and opportunities, covering a number of issues such as different models of computation, scalable data and process management, and data provenance and lineage handling in scientific workflows. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Ludäscher, B. (2009). What makes scientific workflows scientific? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5566 LNCS, p. 217). https://doi.org/10.1007/978-3-642-02279-1_16
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