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Accessing and Visualizing scientific spatiotemporal dataThis paper discusses work done by JPL 's Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids These tools do one or more of the following tasks visualize local data sets for local users, visualize local data sets for remote users, and access and visualize remote data sets The tools are used for various types of data, including remotely sensed image data, digital elevation models, astronomical surveys, etc The paper attempts to pull some common elements out of these tools that may be useful for others who have to work with similarly large data sets.
Document ID
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Katz, Daniel S.
Bergou, Attila
Berriman, Bruce G.
Block, Gary L.
Collier, Jim
Curkendall, David W.
Good, John
Husman, Laura
Jacob, Joseph C.
Laity, Anastasia
Li, Peggy P.
Miller, Craig
Prince, Tom
Siege, Herb
Williams, Roy
Date Acquired
August 23, 2013
Publication Date
June 21, 2004
Meeting Information
Meeting: 16th International Conference on Scientific and Statistical Database Management
Location: Santorini
Country: Greece
Start Date: June 21, 2004
Distribution Limits
data sets
multiple computing resources

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