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May 2004 Some Statistical and Computational Challenges, and Opportunities in Astronomy
G. Jogesh Babu, S. George Djorgovski
Statist. Sci. 19(2): 322-332 (May 2004). DOI: 10.1214/088342304000000774


The data complexity and volume of astronomical findings have increased in recent decades due to major technological improvements in instrumentation and data collection methods. The contemporary astronomer is flooded with terabytes of raw data that produce enormous multidimensional catalogs of objects (stars, galaxies, quasars, etc.) numbering in the billions, with hundreds of measured numbers for each object. The astronomical community thus faces a key task: to enable efficient and objective scientific exploitation of enormous multifaceted data sets and the complex links between data and astrophysical theory. In recognition of this task, the National Virtual Observatory (NVO) initiative recently emerged to federate numerous large digital sky archives, and to develop tools to explore and understand these vast volumes of data. The effective use of such integrated massive data sets presents a variety of new challenging statistical and algorithmic problems that require methodological advances. An interdisciplinary team of statisticians, astronomers and computer scientists from The Pennsylvania State University, California Institute of Technology and Carnegie Mellon University is developing statistical methodology for the NVO. A brief glimpse into the Virtual Observatory and the work of the Penn State-led team is provided here.


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G. Jogesh Babu. S. George Djorgovski. "Some Statistical and Computational Challenges, and Opportunities in Astronomy." Statist. Sci. 19 (2) 322 - 332, May 2004.


Published: May 2004
First available in Project Euclid: 14 January 2005

zbMATH: 1100.85500
MathSciNet: MR2146945
Digital Object Identifier: 10.1214/088342304000000774

Rights: Copyright © 2004 Institute of Mathematical Statistics


Vol.19 • No. 2 • May 2004
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