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The study of time-evolving phenomena is fundamental to the understanding
of complex physical or chemical processes found in many areas of science
and engineering. High-resolution numerical models used to simulate these
processes are capable of generating torrents of data. Scientific
visualization has become an essential tool for aiding researchers in
the analysis of vast data sets. Yet, existing visualization technology
lacks capability for adequately addressing time-varying data,
particularly those that are large in both the spatial and temporal
domains.
In recognition of this technology gap, the U.S. National Science
Foundation (NSF) has awarded an Information Technology Research (ITR)
grant aimed at advancing the state-of-the-art in time-varying data
analysis. The grant recipients, JPL, Ohio State University, NCAR, Tokyo
University, and U.C. Davis, will collaborate over five years towards
this purpose.
Areas of focus for this award include:
- Simulation-time and post-processing data reduction
- Temporal and spatial feature extraction
- Highly optimized rendering methods coupled with novel interaction
techniques
- Commodity-hardware, desktop solutions
In addition to the research areas targeted, a significant component of
this award will be the development of the most promising research
advancements into freely available, end-user tools. NCAR will lead this
tool building effort as well as conduct research in the area of
progressive data access schemes
More information about VAPOR may be found on the VAPOR web site.
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