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Title: Sunfall: a collaborative visual analytics system for astrophysics

Sunfall: a collaborative visual analytics system for astrophysics 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.
Authors: ; ; ; ; ;
Publication Date:
OSTI Identifier:934993
Report Number(s):LBNL-657E
TRN: US200815%%76
DOE Contract Number:DE-AC02-05CH11231
Resource Type:Conference
Data Type:
Resource Relation:Conference: SciDAC Conference, Seattle, July 14-18, 2008
Research Org:Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
Sponsoring Org:Computational Research Division
Country of Publication:United States
Subject: 79; 97; ALGORITHMS; ASTROPHYSICS; EXPLORATION; IMAGE PROCESSING; LEARNING; PRODUCTION visual analytics, collaborative, astrophysics, workflow, image processing