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research-article

The sloan digital sky survey

Published: 01 March 1999 Publication History

Abstract

Astronomy is about to undergo a major paradigm shift, with data sets becoming larger and more homogeneous, designed for the first time in a top-down fashion. In a few years, it might be much easier for astronomers to "dial-up" a part of the sky, when they need a rapid observation, rather than wait for several months to access a (sometimes quite small) telescope. With several projects in multiple wavelengths underway-such as the SDSS, Galex, 2MASS, GSC-2, POSS2, Rosat, First, and Denis projects, each surveying a large fraction of the sky-the concept of having a digital sky, with multiple, terabyte-size databases interoperating seamlessly no longer seems outlandish. As more and more catalogs are added and linked to the existing ones in coming years and query engines become more sophisticated, astronomers will have to be just as familiar with mining data as with observing on telescopes.As a major part of that effort, the Sloan Digital Sky Survey will digitally map about half of the northern sky in five filter bands from ultraviolet to near infrared; we expect it to detect over 200 million objects in this area. Simultaneously, the project will measure redshifts for the brightest 1 million galaxies. (A redshift is the spectral displacement of a celestial body toward longer wavelengths caused by the Doppler effect or the source's gravitational field; the higher the redshift value, the more distant the object from Earth, hence the farther back in time.) In doing so, the SDSS will revolutionize astronomy, increasing the amount of information made available to researchers by several orders of magnitude. The resultant archive available for scientific research will be large (exceeding several terabytes) and complex-including textual information, derived parameters, multiband images, and spectra. The catalog will let astronomers study the universe's evolution in greater detail and should serve as the standard reference for the next several decades. As this article describes, the potential scientific impact of the survey is stunning, but to realize its potential, data must be turned into knowledge. As I'll indicate, this is not easy, for the survey's information content will be several times larger than the entire text contained in the Library of Congress.

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  • (2015)Enhancing Parallel Data Loading for Large Scale Scientific DatabaseProceedings, Part II, of the 15th International Conference on Algorithms and Architectures for Parallel Processing - Volume 952910.1007/978-3-319-27122-4_11(149-162)Online publication date: 18-Nov-2015
  • (2009)Category detection using hierarchical mean shiftProceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/1557019.1557112(847-856)Online publication date: 28-Jun-2009
  • (2003)Migrating a Multiterabyte Archive from Object to Relational DatabasesComputing in Science and Engineering10.1109/MCISE.2003.12258575:5(16-29)Online publication date: 1-Sep-2003

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Published In

cover image Computing in Science and Engineering
Computing in Science and Engineering  Volume 1, Issue 2
March-April 1999
92 pages
ISSN:1521-9615
Issue’s Table of Contents

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IEEE Educational Activities Department

United States

Publication History

Published: 01 March 1999

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  • (2015)Enhancing Parallel Data Loading for Large Scale Scientific DatabaseProceedings, Part II, of the 15th International Conference on Algorithms and Architectures for Parallel Processing - Volume 952910.1007/978-3-319-27122-4_11(149-162)Online publication date: 18-Nov-2015
  • (2009)Category detection using hierarchical mean shiftProceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/1557019.1557112(847-856)Online publication date: 28-Jun-2009
  • (2003)Migrating a Multiterabyte Archive from Object to Relational DatabasesComputing in Science and Engineering10.1109/MCISE.2003.12258575:5(16-29)Online publication date: 1-Sep-2003

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