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Proceedings Paper

Holistic approach to data management at the Issac Newton Group
Author(s): James R. Lewis; Nicholas A. Walton
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Paper Abstract

The Isaac Newton Group comprises three telescopes: the 4.2m William Herschel Telescope, the 2.5m Isaac Newton Telescope, and the 1.0m Jacobus Kaptyen Telescope. The operational capability of the ING has been increased by integrating the fault reporting system with the archiving of data. All data obtained from the telescope are automatically archived and stored on-line in a 500 slot CDROM jukebox. The flexible image transport system headers are stripped, stored in a Sybase database and are available immediately for inspection via a web-based user interface. Users have the option to save files to disc for FTP download and display the data using a standard image tool. After six months the original data are sent from the ING to the RGO Astronomy Data Center in Cambridge. The ING science archive may be interrogated, and the data is available for general download. The ING fault database is also implemented as a Sybase database. In addition to standard features, links can be made to individual data files. These can be subsequently downloaded from the archive on request. This system greatly aids in ensuring the integrity of data obtained across the ING telescopes and helps engineers when analyzing many kinds of faults. Access to data on-line is being exploited in automating the dissemination of data obtained during service observing. Pipeline processed data will also be integrated into the system. In order to handle increased data flows with new larger CCD arrays, a system based on high capacity DVD disks is planned.

Paper Details

Date Published: 3 July 1998
PDF: 10 pages
Proc. SPIE 3349, Observatory Operations to Optimize Scientific Return, (3 July 1998); doi: 10.1117/12.316496
Show Author Affiliations
James R. Lewis, Royal Greenwich Observatory (United Kingdom)
Nicholas A. Walton, Isaac Newton Group (United Kingdom)


Published in SPIE Proceedings Vol. 3349:
Observatory Operations to Optimize Scientific Return
Peter J. Quinn, Editor(s)

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