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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
| ASCII Text | x | ||
| Cecilia R. Aragon, Stephen J. Bailey, Sarah Poon, Karl J. Runge, Rollin C. Thomas, "Sunfall: A Collaborative Visual Analytics System for Astrophysics," 2012 IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 219-220, 2007 IEEE Symposium on Visual Analytics Science and Technology, 2007. | |||
| BibTex | x | ||
| @article{ 10.1109/VAST.2007.4389026, author = {Cecilia R. Aragon and Stephen J. Bailey and Sarah Poon and Karl J. Runge and Rollin C. Thomas}, title = {Sunfall: A Collaborative Visual Analytics System for Astrophysics}, journal ={2012 IEEE Conference on Visual Analytics Science and Technology (VAST)}, volume = {0}, year = {2007}, isbn = {978-1-4244-1659-2}, pages = {219-220}, doi = {http://doi.ieeecomputersociety.org/10.1109/VAST.2007.4389026}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 IEEE Conference on Visual Analytics Science and Technology (VAST) TI - Sunfall: A Collaborative Visual Analytics System for Astrophysics SN - 978-1-4244-1659-2 SP219 EP220 A1 - Cecilia R. Aragon, A1 - Stephen J. Bailey, A1 - Sarah Poon, A1 - Karl J. Runge, A1 - Rollin C. Thomas, PY - 2007 VL - 0 JA - 2012 IEEE Conference on Visual Analytics Science and Technology (VAST) ER - | |||
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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