Data Mining Challenges in Synoptic Sky Surveys

Details Data Mining Challenges in Synoptic Sky Surveys Data Mining Challenges in Synoptic Sky Surveys

Jan 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21523105d&link_type=abstract

American Astronomical Society, AAS Meeting #215, #231.05; Bulletin of the American Astronomical Society, Vol. 42, p.595

Astronomy and Astrophysics

Astronomy

Scientific paper

Digital synoptic sky surveys are rapidly becoming the major data generators in astronomy, bringing us into the Petascale regime; this trend will continue with the future facilities such as the LSST and SKA. In addition to all of the data processing and knowledge extraction challenges inherited from the traditional, one-time panoramic sky surveys, and the substantial increase in data volumes, this new generation of sky surveys brings an additional complexity and demands, due to the presence of the time axis, and the requirements of a real-time processing, transient event detection, classification, and follow-up. Two sets of challenges stand out: dynamical, iterative classification of transient events given the sparse and heterogeneous information available for them; and an automated prioritization and decision making for follow-up observations. We will describe some of the novel approaches to these problems, based on our work with the PQ and CRTS sky surveys, and other data streams.

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