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Scientific Workflow

The Internet has changed forever the way in which science will be done. Worldwide scientific collaborations, such as Globus, and specific projects, such as GriPhyN, are beginning to use internet access to create opportunities for scientists to make data available to worldwide communities, thereby enabling expedited collaborations among geographically distributed researchers. While this creates opportunities through the broader availability of more comprehensive scientific analyses, it also creates risks arising from uncertainty about the way in which internet-accessed data were produced and the appropriate ways in which they can be used. Scientific workflow is the application of workflow technology to scientific endeavours, and is becoming recognized as a valuable approach for assisting scientists in accessing and analyzing data.

Our approach builds upon the hypothesis that complex scientific analyses are in fact intricate processes whose important subtleties should be captured with the help of process definition capabilities. While at some high, abstract level scientific processes might be modeled as simple graphs, which may be visually appealing, we believe that such simplistic models omit important process details. Our hypothesis is that process definition formalism should be used to define scientific processes thereby enabling the use of tools to analyze, verify, and execute them.

Recent Publications

Supporting Undo and Redo in Scientific Data Analysis
Xiang Zhao, Emery R. Boose, Yuriy Brun, Barbara Staudt Lerner, Leon J. Osterweil, 5th USENIX Workshop on the Theory and Practice of Provenance (TaPP '13), Lombard, IL, April 2-3, 2013. (UM-CS-2013-015)

[ PDF ] [ Slides ]

Provenance and Quality Control in Sensor Networks
Barbara Lerner, Emery Boose, Leon J. Osterweil, Aaron Ellison, Lori A. Clarke, In Proceedings of the Environmental Information Management Conference (EIM 2011), Santa Barbara, CA, September 28-29, 2011. (UM-CS-2011-047)

[ PDF ]

Clear and Precise Specification of Ecological Data Management Processes and Dataset Provenance
Leon J. Osterweil, Lori A. Clarke, Aaron. M. Ellison, Emery R. Boose, Rodion Podorozhny, Alexander Wise, IEEE Transactions on Automation Science and Engineering, Vol.7, No 1, 2010, pp 189-195. (UM-CS-2010-014)

[ IEEE ] [ PDF ]

Experience in Using a Process Language to Define Scientific Workflow and Generate Dataset Provenance
Leon J. Osterweil, Lori A. Clarke, Rodion Podorozhny, Alexander Wise, Emery Boose, Aaron M. Ellison, Julian Hadley, ACM SIGSOFT 16th International Symposium on Foundations of Software Engineering, November 2008, pp. 319-329. (UM-CS-2008-05)

This is an updated version of UM-CS-2008-05, originally dated March 2008.

[ ACM ] [ PDF ] [ Slides ]


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