Accessing and visualizing scientific spatiotemporal data

This 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.