Managing Big Data for Scientific Visualization
Published 1 January 2015
Michael Cox, David Ellsworth
Citations119
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TL;DR
This section offers some structure to understand what has been done to manage big data for engineering and scientific visualization, and to understand and go forward in areas that may prove fruitful.
Abstract
Many areas of endeavor have problems with big data. Some classical business applications have faced big data for some time (e.g. airline reservation systems), and newer business applications to exploit big data are under construction (e.g. data warehouses, federations of databases). While engineering and scientific visualization have also faced the problem for some time, solutions are less well developed, and common techniques are less well understood. In this section we offer some structure to understand what has been done to manage big data for engineering and scientific visualization, and to understand and go forward in areas that may prove fruitful. With this structure as backdrop, we discuss the work that has been done in management of big data, as well as our own work on demand-paged segments for fluid flow visualization.
Keywords
Computer ScienceDecision Sciences
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