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Grist: Grid-based Data Mining for Astronomy

Jacob, Joseph C. and Katz, Daniel S. and Miller, Craig D. and Walia, Harshpreet and Williams, Roy and Djorgovski, S. George and Graham, Matthew and Mahabal, Ashish and Babu, Jogesh and Vanden Berk, Daniel E. and Nichol, Robert (2005) Grist: Grid-based Data Mining for Astronomy. In: Astronomical Data Analysis Software and Systems XIV. ASP Conference Series. No.XXX. Astronomical Society of the Pacific , San Francisco, CA, P1.3.8. http://resolver.caltech.edu/CaltechCACR:2005.118

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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.


Item Type:Book Section
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 2004
Group:Center for Advanced Computing Research
Record Number:CaltechCACR:2005.118
Persistent URL:http://resolver.caltech.edu/CaltechCACR:2005.118
Usage Policy:You are granted permission for individual, educational, research and non-commercial reproduction, distribution, display and performance of this work in any format.
ID Code:28227
Collection:CaltechCACR
Deposited By: Imported from CaltechCACR
Deposited On:15 Feb 2006
Last Modified:26 Dec 2012 14:32

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