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An Architecture for Scaling NVO Services to TeraGrid
Technical Report. [CaltechCACR:2005.108]
Roy Williams, Bob Hanisch, Joe Jacob, Ray Plante and Alex Szalay (2005)
(PDF)
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Virtual Observatory: From Concept to Implementation
In: Science with Wavelengths on Human Scales, ASPCS, vol. 3xx. ASPCS
S. G. Djorgovski and R. Williams
(PDF)
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The UltraLight Project: The Network as an Integrated and Managed Resource in Grid Systems for High Energy Physics and Data Intensive Science
In: Computing in Science and Engineering, Grid Computing issue.
Harvey Newman, Julian Bunn, Richard Cavanaugh, Iosif Legrand, Steven Low, Shawn McKee, Dan Nae, Sylvan Ravot, Conrad Steenberg, Xun Su, Michael Thomas, Frank van Lingen and Yang Xia (2005)
Abstract: We describe the NSF-funded UltraLight project. The project’s goal is to meet the data-intensive computing challenges of the next generation of particle physics experiments with a comprehensive, network-focused agenda. In particular we argue that instead of treating the network traditionally, as a static, unchanging and unmanaged set of inter-computer links, we instead will use it as a dynamic, configurable, and closely monitored resource, managed end-to-end, to construct a next-generation global system able to meet the data processing, distribution, access and analysis needs of the high energy physics (HEP) community. While the initial UltraLight implementation and services architecture is being developed to serve HEP, we expect many of UltraLight’s developments in the areas of networking, monitoring, management, and collaborative research, to be applicable to many fields of data intensive e-science. In this paper we give an overview of, and motivation for the UltraLight project, and provide early results within different working areas of the project. his work is partly supported by the Department of Energy grants: DE-FC02-01ER25459, DE-FG03-92-ER40701, DE-AC02-76CH03000 as part of the Particle Physics DataGrid project, DE-FG02-04ER-25613 as part of Lambda Station, and by the National Science Foundation grants: ANI-0230967, PHY-0218937, PHY-0122557, PHY-0427110, ANI-0113425, ANI-0230967, EIA-0303620, by the ARO grants: DAAD19-02-1-0283, F49620-03-1-0119 and the AFOSR grants: F49620-03-1-0119.
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Virtual Observatory: From Concept to Implementation
In: Science with Wavelengths on Human Scales. ASPCS, vol. 3xx. ASPCS.
S. G. Djorgovski and R. Williams
Abstract: We review the origins of the Virtual Observatory (VO) concept, and the current status of the efforts in this field. VO is the response of the astronomical community to the challenges posed by the modern massive and complex data sets. It is a framework in which information technology is harnessed to organize, maintain, and explore the rich information content of the exponentially growing data sets, and to enable a qualitatively new science to be done with them. VO will become a complete, open, distributed, web-based framework for astronomy of the early 21st century. A number of significant efforts worldwide are now striving to convert this vision into reality. The technological and methodological challenges posed by the information-rich astronomy are also common to many other fields. We see a fundamental change in the way all science is done, driven by the information technology revolution.
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Time Domain Explorations With Digital Sky Surveys
In: Astronomical Data Analysis Software and Systems XIV. Astronomical Society of the Pacific Conference Series (XXX). Astronomical Society of the Pacific, San Francisco, CA, P2.2.7.
Ashish A. Mahabal, S. G. Djorgovski, M. J. Graham, Priya Kollipara, Benjamin Granett, Elisabeth Krause, Roy Williams, M. Bogosavljevic, C. Baltay, D. Rabinowitz, A. Bauer, P. Andrews, N. Ellman, S. Duffau, J. Jerke, A. Rengstorf, R. Brunner, J. Musser, S. Mufson and M. Gebhard
Abstract: One of the new frontiers of astronomical research is the exploration of time variability on the sky at different wavelengths and flux levels. We have carried out a pilot project using DPOSS data to study strong variables and transients, and are now extending it to the new Palomar-QUEST synoptic sky survey. We report on our early findings and outline the methodology to be implemented in preparation for a real-time transient detection pipeline. In addition to large numbers of known types of highly variable sources (e.g., SNe, CVs, OVV QSOs, etc.), we expect to find numerous transients whose nature may be established by a rapid follow-up. Whereas we will make all detected variables publicly available through the web, we anticipate that email alerts would be issued in the real time for a subset of events deemed to be the most interesting. This real-time process entails many challenges, in an effort to maintain a high completeness while keeping the contamination low. We will utilize distributed Grid services developed by the GRIST project, and implement a variety of advanced statistical and machine learning techniques.
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Grist: Grid-based Data Mining for Astronomy
In: Astronomical Data Analysis Software and Systems XIV. Astronomical Society of the Pacific Conference Series (XXX). Astronomical Society of the Pacific, San Francisco, CA, P1.3.8.
Joseph C. Jacob, Daniel S. Katz, Craig D. Miller, Harshpreet Walia, Roy Williams, S. George Djorgovski, Matthew Graham, Ashish Mahabal, Jogesh Babu, Daniel E. Vanden Berk and Robert Nichol (2005)
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. 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