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Paper: Data and Metadata Management at the Keck Observatory Archive
Volume: 495, Astronomical Data Analysis Software and Systems XXIV (ADASS XXIV)
Page: 535
Authors: Berriman, G. B.; Holt, J. M.; Mader, J. A.; Tran, H. D.; Goodrich, R. W.; Gelino, C. R.; Laity, A. C.; Kong, M.; Swain, M. A.
Abstract: A collaboration between the W. M. Keck Observatory (WMKO) in Hawaii and the NASA Exoplanet Science Institute (NExScI) in California, the Keck Observatory Archive (KOA) was commissioned in 2004 to archive data from WMKO, which operates two classically scheduled 10 m ground-based telescopes. The data from Keck are not suitable for direct ingestion into the archive since the metadata contained in the original FITS headers lack the information necessary for proper archiving. The data pose a number of challenges for KOA: different instrument builders used different standards, and the nature of classical observing, where observers have complete control of the instruments and their observations, lead to heterogeneous data sets. For example, it is often difficult to determine if an observation is a science target, a sky frame, or a sky flat. It is also necessary to assign the data to the correct owners and observing programs, which can be a challenge for time-domain and target-of-opportunity observations, or on split nights, during which two or more principle investigators share a given night. In addition, having uniform and adequate calibrations is important for the proper reduction of data. Therefore, KOA needs to distinguish science files from calibration files, identify the type of calibrations available, and associate the appropriate calibration files with each science frame. We describe the methodologies and tools that we have developed to successfully address these difficulties, adding content to the FITS headers and “retrofitting" the metadata in order to support archiving Keck data, especially those obtained before the archive was designed. With the expertise gained from having successfully archived observations taken with all eight currently active instruments at WMKO, we have developed lessons learned from handling this complex array of heterogeneous metadata. These lessons help ensure a smooth ingestion of data not only for current but also future instruments, as well as a better experience for the archive user.
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