SIMBAD references

We describe the design and implementation of a software system for producing, managing, and analyzing catalogs from the digital scans of the Second Palomar Observatory Sky Surveys. The system (SKICAT) integrates new and existing packages for performing the full sequence of tasks from raw pixel processing, to object classification, to the matching of multiple, overlapping Schmidt plates and CCD calibration frames. We describe the relevant details of constructing SKITCAT plate, CCD, matched, and object catalogs. Plate and CCD catalogs are generated from images, while the latter are derived from existing catalogs. A pair of programs complete the majroity of plate and CCD processing in an automated, pipeline fashion, with the user required to execute a minimal number of pre- and post-processing procedures. We apply a modified version of FOCAS for the detection and photometry, and new software for matching catalogs on an object by object basis. SKICAT employs modern machine learning techniques, such as decision trees, to perform automatic star-galaxy-artifact classification with a > 90% accuracy down to ∼1^m above the plate detection limit. The system also provides a variety of tools for interactively querying and analyzing the resulting object catalogs.