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Astro-Wise meeting

Astro-Wise meeting. Kapteyn Institute, Groningen 06./07. May 2004 Wolfgang Voges, Hans-Martin Adorf, Gerard Lemson, GAVO. Overview. General questions Demos Areas of common interest Image combination Catalogue matching Source classification Expertise Specific questions Suggestions.

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Astro-Wise meeting

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  1. Astro-Wise meeting Kapteyn Institute, Groningen 06./07. May 2004 Wolfgang Voges, Hans-Martin Adorf, Gerard Lemson, GAVO

  2. Overview • General questions • Demos • Areas of common interest • Image combination • Catalogue matching • Source classification • Expertise • Specific questions • Suggestions

  3. General questions • What are the scientific goals of the AstroWise/OmegaCAM project? • What are the use cases/science drivers? • What data/information do astronomers want/need from AstroWise, and in what form? • What data/information does AstroWise want from the outside world, and in what form? • How can VO help?

  4. Demos • MCMCS download manager • ClassX matcher & classifer • SED classifier • Client-server application

  5. Demos (2) • AstroWise “data mining” Web-GUI • Raw pixel data – calibrated images – catalogues • Similar to “AW database-objectviewer” • GAVO Manager for AstroWise data mining • Rich client to navigate in complex data spaces • Allows local user-interaction with the data • Plug-ins ?

  6. Areas of common interest • Image combination • Catalogue matching • Source classification • …

  7. Image combination • Registration • Resampling (regridding) • For visualization - for quantitative analysis? • Difficulties • Resolution mismatch • Geometric distortion correction • Noise • We might be interested and do have some expertise ...

  8. Catalogue matching • Matching (associating) • Central task • fuzzy matching increasingly important with increasing # of catalogues (disambiguation, pruning) • Important quantities • Surface density of sources • Astrometric uncertainties • Auxiliary data (e.g. flux) • We are interested and do have expertise ...

  9. Source classification • Important (obviously) • Can help in resolving matching ambiguities • Often goal-directed/goal-dependant • Often objective classification is not wanted! • We are interested and do have expertise ...

  10. Expertise (1) • Technology • Image combination • Catalogue matching • Statistical pattern recognition & classification • GRID computing • Web-services (REST + SOAP) + registries • Globus TK, also SGE, P2P • J2EE • GUIs (HTML + JSP thin clients; rich clients)

  11. Expertise (2) • Technology (ctnd.) • Databases • Methodology • Data modeling • Data analysis • Expert systems (forward-chaining, back-chaining) • Optimization (e.g. workflow planning & scheduling) • Astronomy

  12. Specific questions • User interaction • How complex is the interaction with the system? • Scope • What is a reasonable project? • Technology • Which could/should we use? • Architecture • How could/should it look like?

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