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2007 IEEE Symposium on Visual Analytics Science and Technology
Sunfall: A Collaborative Visual Analytics System for Astrophysics
Sacramento, CA, USA
October 30-November 01
ISBN: 978-1-4244-1659-2
Cecilia R. Aragon, Lawrence Berkeley National Laboratory. E-Mail: aragon@hpcrd.lbl.gov
Stephen J. Bailey, Lawrence Berkeley National Laboratory. E-Mail: sjbailey@lbl.gov
Sarah Poon, Space Sciences Laboratory. E-Mail: sspoon@lbl.gov
Karl J. Runge, Space Sciences Laboratory. E-Mail: kjrunge@lbl.gov
Rollin C. Thomas, Lawrence Berkeley National Laboratory. E-Mail: rcthomas@lbl.gov
Computational and experimental sciences produce and collect ever-larger and complex datasets, often in large-scale, multi-institution projects. The inability to gain insight into complex scientific phenomena using current software tools is a bottleneck facing virtually all endeavors of science. In this paper, we introduce Sunfall, a collaborative visual analytics system developed for the Nearby Supernova Factory, an international astrophysics experiment and the largest data volume supernova search currently in operation. Sunfall utilizes novel interactive visualization and analysis techniques to facilitate deeper scientific insight into complex, noisy, high-dimensional, high-volume, time-critical data. The system combines novel image processing algorithms, statistical analysis, and machine learning with highly interactive visual interfaces to enable collaborative, user-driven scientific exploration of supernova image and spectral data. Sunfall is currently in operation at the Nearby Supernova Factory; it is the first visual analytics system in production use at a major astrophysics project.
Citation:
Cecilia R. Aragon, Stephen J. Bailey, Sarah Poon, Karl J. Runge, Rollin C. Thomas, "Sunfall: A Collaborative Visual Analytics System for Astrophysics," vast, pp.219-220, 2007 IEEE Symposium on Visual Analytics Science and Technology, 2007
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