Grist: Grid-based Data Mining for Astronomy
Abstract
The Grist project is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed grid services controlled by a work ow system, compliant with standards emerging from the grid computing, web services, and virtual observatory communities. This new technology is being used to find high redshift quasars, study peculiar variable objects, search for transients in real time, and fit SDSS QSO spectra to measure black hole masses. Grist services are also a component of the "hyperatlas" project to serve high-resolution multi-wavelength imagery over the Internet. In support of these science and outreach objectives, the Grist framework will provide the enabling fabric to tie together distributed grid services in the areas of data access, federation, mining, subsetting, source extraction, image mosaicking, statistics, and visualization.
Additional Information
Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, and was sponsored by the National Science Foundation through an agreement with the National Aeronautics and Space Administration. Also available: arXiv:astro-ph/0411589 v1 19 Nov 2004Attached Files
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Additional details
- Eprint ID
- 28227
- Resolver ID
- CaltechCACR:2005.118
- NASA/JPL/Caltech
- NSF
- Created
-
2006-02-15Created from EPrint's datestamp field
- Updated
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2020-03-09Created from EPrint's last_modified field
- Caltech groups
- Center for Advanced Computing Research
- Series Name
- ASP Conference Series
- Series Volume or Issue Number
- XXX