1. The GAVO Cross-Matcher Application Hans-Martin Adorf, Gerard Lemson, Wolfgang Voges GAVO, Max-Planck-Institut für extraterrestrische Physik, Garching b. München, Germany Abstract: Catalogue matching is a key application of a virtual observatory. Its main purpose is object identification, classification and SED-construction, but it can also be used for cross-validating catalogues. The GAVO cross-matcher is a multi-archive, multi-server, multi-catalogue, statistical matcher, operating on astrometric coordinates and individual associated uncertainties. Based on a “private catalogue” of sky-positions, the matcher queries one or more distributed archives (currently SDSS and VizieR). From the primary match- results hypothetical combinations of counterparts, the “match-candidates”, are formed. The statistical properties of each match-candidate are computed, and a reduced chi-squared criterion is employed for discriminating against unlikely counterpart combinations. For each surviving match-candidate, the cross-matcher assembles astrometric, photometric and auxiliary information in CSV- or VOTable-formatted files. The GAVO cross-matcher application serves as a test-bed for exploring and refining the process of statistical catalogue- matching. The application is in beta-test status, and has already successfully been used in a scientific project (Komossa et al. 2005, submitted). Operations The operation of any matcher requires three major phases: 1.Specification of the match request: the user provides a list of input positions, along with a selection of the archives, archive servers, catalogues to query, and columns to retrieve from each catalogue. The specification also requires some parameters such as catalogue-specific search radii, and a discrimination threshold. 2.Execution of the match request: the matcher starts a thread for each query. When all queries have returned a result, the matcher carries out a deterministic match (left outer join in a database) followed by a statistical discrimination. The matcher produces a comprehensive match table and different views: a summary view, an astrometry view, and a photometry view. Each row is labeled by an ID uniquely identifying a match candidate. 3.Assessment of the match results: the user inspects the number of counterparts returned from each catalogue, investigates match ambiguities, views images and maps, and possibly modifies the match parameters. Features The GAVO matcher (Fig. 1) uses a “private” list of input positions, works with existing archives (currently VizieR and SDSS) that are accessed via HTTP, uses a local metadata file for archive, server, and catalogue description (Fig. 2), Offers a GUI editor supporting the formulation of a match request (Fig. 3), queries multiple catalogue servers in parallel (Fig. 4) using catalogue-specific search radii, uses individual astrometric uncertainties for statistical matching, and automatically generates several table views (Fig.5) from the comprehensive match result. Fig. 1: The upper half of the diagram shows the dataflow through the GAVO multi-catalogue matcher which takes an input list of sky positions, queries multiple catalogues from the VizieR and SDSS archives, and produces a comprehensive match result. Intermediate results are stored in an in- memory database, which is also used for deterministic matching. The lower half of the diagram shows the foreseen integration of the matcher with a future SED-assembly module. Summary Scientific catalogue matching is a complex process. It is important to involve astronomers with scientific matching projects as early as possible. A rich client GUI application (Figs. 2 & 3) facilitates the matching process. Multi-catalogue matching generates tables with numerous columns – typically 200 or more. Users are easily overwhelmed by the amount of data generated. Different tabular views (Fig. 5) support the assessment of match candidates. Results are available in different formats including VOTable, directly viewable via VOPlot. An augmented visualization tool is needed in order to assess match-candidates, particularly when counterpart ambiguities arise. A separate detailed technical report is available containing our observations and recommendations concerning catalogue matching. Demo The GAVO catalogue cross-matcher is being demonstrated at this conference. Fig. 2: The manager GUI facilitates the specification and control of the matching process. The left panel allows access to the local file system containing match configuration and result files. The upper right panel allows viewing of input and output data. (Here a portion of the archive metadata file is shown, specifying details of servers and catalogues.) The lower right panel shows logger information. Fig. 3: A GUI editor supports the specification of a complex match request. The editor reads the archive metadata from a local multi-archive.xml file. The user may select catalogues from archives, and select table columns from catalogues. The editor generates a multi-archive match query file. Fig. 4: A monitor shows how the matching process progresses. Catalogue information is displayed along with server description and run-time statistics. A failed query will automatically be re-submitted to a different server. Fig. 5: The summary view of the comprehensive match result. Each row contains a different match- candidate and is labeled with a unique ID. Several match candidates can be identified that are related to the same input position (matching ambiguity). A reduced chi-squared metric permits a statistical discrimination against the inclusion of unlikely counterparts into a match candidate.