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Issue No. 03 - May/June (2008 vol. 10)
ISSN: 1521-9615
pp: 22-29
Lawrence Gibbons , Cornell University
Peter Wittich , Cornell University
Mirek Riedewald , Cornell University
Andrew Dolgert , Cornell University
Gregory J. Sharp , Cornell University
Christopher D. Jones , Cornell University
Daniel Riley , Cornell University
Valentin Kuznetsov , Cornell University
The adoption of large-scale distributed computing for high-energy physics presents new opportunities and challenges for physicists analyzing the data from the Large Hadron Collider experiments. With petabytes of data to manage, accessed by thousands of systems and used by thousands of collaborators, effective provenance is critical to the understanding of how the physics results were produced. In this article, the authors discuss several uses of data provenance in high-energy physics workflows and the opportunities for improvements in data analysis workflows that result from decentralized provenance collection and fine-grained object annotations.
Provenance, physics, scientific databases, metadata
Lawrence Gibbons, Peter Wittich, Mirek Riedewald, Andrew Dolgert, Gregory J. Sharp, Christopher D. Jones, Daniel Riley, Valentin Kuznetsov, "Provenance in High-Energy Physics Workflows", Computing in Science & Engineering, vol. 10, no. , pp. 22-29, May/June 2008, doi:10.1109/MCSE.2008.81
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