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Title:
Brave New World: Data Intensive Science with SDSS and the VO
Authors:
Thakar, A. R.; Szalay, A. S.; O'Mullane, W.; Nieto-Santisteban, M.; Budavari, T.; Li, N.; Carliles, S.; Haridas, V.; Malik, T.; Gray, J.
Affiliation:
AA(JHU), AB(JHU), AC(JHU), AD(JHU), AE(JHU), AF(JHU), AG(JHU), AH(JHU), AI(JHU), AJ(Microsoft Research)
Publication:
American Astronomical Society Meeting 205, #113.01; Bulletin of the American Astronomical Society, Vol. 36, p.1541
Publication Date:
12/2004
Origin:
AAS
Bibliographic Code:
2004AAS...20511301T

Abstract

With the advent of digital archives and the VO, astronomy is quickly changing from a data-hungry to a data-intensive science. Local and specialized access to data will remain the most direct and efficient way to get data out of individual archives, especially if you know what you are looking for. However, the enormous sizes of the upcoming archives will preclude this type of access for most institutions, and will not allow researchers to tap the vast potential for discovery in cross-matching and comparing data between different archives. The VO makes this type of interoperability and distributed data access possible by adopting industry standards for data access (SQL) and data interchange (SOAP/XML) with platform independence (Web services).

As a sneak preview of this brave new world where astronomers may need to become SQL warriors, we present a look at VO-enabled access to catalog data in the SDSS Catalog Archive Server (CAS): CasJobs - a workbench environment that allows arbitrarily complex SQL queries and your own personal database (MyDB) that you can share with collaborators; OpenSkyQuery - an IVOA (International Virtual Observatory Alliance) compliant federation of multiple archives (OpenSkyNodes) that currently links nearly 20 catalogs and allows cross-match queries (in ADQL - Astronomical Data Query Language) between them; Spectrum and Filter Profile Web services that provide access to an open database of spectra (registered users may add their own spectra); and VO-enabled Mirage - a Java visualizatiion tool developed at Bell Labs and enhanced at JHU that allows side-by-side comparison of SDSS catalog and FITS image data.

Anticipating the next generation of Petabyte archives like LSST by the end of the decade, we are developing a parallel cross-match engine for all-sky cross-matches between large surveys, along with a 100-Terabyte data intensive science laboratory with high-speed parallel data access.

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