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A Distributed Approach to Computational Earthquake Science: Opportunities and Challenges
Sept.-Oct. 2012 (vol. 14 no. 5)
pp. 31-42
Andrea Donnellan, Jet Propulsion Laboratory, NASA
Jay Parker, Jet Propulsion Laboratory, NASA
Margaret Glasscoe, Jet Propulsion Laboratory, NASA
Eric De Jong, Jet Propulsion Laboratory, NASA
Marlon Pierce, Indiana University
Geoffrey Fox, Indiana University
Dennis McLeod, University of Southern California
John Rundle, University of California, Davis
Lisa Grant Ludwig, University of California, Irvine
Advances in understanding earthquakes require the integration of models and multiple distributed data products. Increasingly, data are acquired through large investments, and utilizing their full potential requires a coordinated effort by many users, independent researchers, and groups who are often distributed both geographically and by expertise.
Index Terms:
Earthquakes,Data models,Computational modeling,Global Positioning System,Analytical models,Time series analysis,Deformable models,Predictive models,scientific computing,Web services interoperability,Earth and atmospheric sciences,computational earthquake science
Andrea Donnellan, Jay Parker, Margaret Glasscoe, Eric De Jong, Marlon Pierce, Geoffrey Fox, Dennis McLeod, John Rundle, Lisa Grant Ludwig, "A Distributed Approach to Computational Earthquake Science: Opportunities and Challenges," Computing in Science and Engineering, vol. 14, no. 5, pp. 31-42, Sept.-Oct. 2012, doi:10.1109/MCSE.2012.59
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