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Prologue

Prologue. Major VO objective: “Data at your fingertips” (Lawrence) VO-user’s desire: “going backstage” Data quality assessment by user (talk Gilmore) “how did the data-provider arrive at its final result exactly?” Diamond-in-haystack searches

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Prologue

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  1. Prologue • Major VO objective: “Data at your fingertips” (Lawrence) • VO-user’s desire: “going backstage” • Data quality assessment by user (talk Gilmore) • “how did the data-provider arrive at its final result exactly?” • Diamond-in-haystack searches • Upper-limits, swamping by false positives, homogenizing psf-dependent photometry (talk Kuijken) • Statistics of large datasets • Interaction with raw/intermediate data (e.g., weak lensing: Kuijken) • Comparing different routes of analysis (talk Wolk)

  2. The Astro-Wise systemA Federated Information Accumulator for Astronomy Gijs Verdoes Kleijn OmegaCEN, Kapteyn Groningen, NLfor the Astro-Wise Consortium Coordinator TerapixParis OAC Naples Kapteyn InstituteGroningen Sternwarte(+MPE)Munich (National WideField data centers D,F,I,NL and ESO)

  3. The Astro-Wise systemA Federated Information Accumulator for Astronomy Gijs Verdoes Kleijn OmegaCEN, Kapteyn Groningen, NLfor the Astro-Wise Consortium • Has built the Astro-Wise system: • combining {archiving+processing+scientific analysis} of optical wide-field imaging • EU FP5 RTD 5 year programme (parallel to AVO) • Funding dec 2006, other funding until 2009 • And has started using it for science

  4. Dissemminating results Calibration Archiving (raw+final) Quality control User tuned research Motivation Astro-Wise project • Wide Field Imaging now and future : • NOAO-MOSAICI, CTIO-MOSAICII, ESO-WFI/VIMOS, Magellan-IMACS, LaPalma-WFC, CFHT-MegaCAM, Subaru-SuprimeCAM,…, VISTA, OmegaCAM, Pan-Starrs, LSST,… • Optimize scientific return from Wide Field Imaging: • Facilitate (un)forseen uses of calibrated and raw Tera/Petabyte data sets by global pools of collaborators and resources • This requires enabling changes at any time in: • Physical parameters (e.g., instrument/atmosphere) • Improved algorithms • Improved insight in 1. or 2. • And requires a single integrated information system Integrated Information system

  5. The Astro-Wise approach: • Objects with • Attributes • Methods

  6. The Astro-Wise approach: • Objects with • Attributes • Methods • Link all dependencies of objects

  7. The Astro-Wise Environment • DATABASE • LINKS • METADATA images • CATALOGS • Contains “ALL input/output” Methods/Algorithms In on-line repository Python (wrapped) • DATA SERVER: • Images: • Calibration & science • Raw & final CPUs

  8. Benefits from integrated dynamic database relevant for VO • Both final and raw products accessible • Objects are linked, all bits are traced: • on-the fly re-processing • Built–in workflow • Easy publishing for VO (to be implemented) • Public data already viewable via web tools • Own compute GRID operational • A federated integrated-system: • Naturally serves global collaborative projects • Scalable: image server/database/compute GRID resources can grow via federation • Mydb environment operational for individual research • Quick scripting: many tasks are “5 Line Scripts” • Fully user tunable – own provided algorithms/scripts allowed • Python: existing software can be wrapped (implemented for Sextractor, swarp, being implemented for GALPHOT, GALFIT)

  9. A flavor of available tools • Data processing: web & command-line

  10. A flavor of available tools

  11. A flavor of available tools • Cut-out server

  12. Status • Astro-Wise system operational in :Groningen, Leiden, Nijmegen, Munich, Bonn, Bochum, Paris, Napoli, Santiago • Astro-Wise will serve: • OmegaCAM surveys • KIDS (Kuijken) • VESUVIO (Galaxy cluster imaging) • OmegaTrans (planet transits) • OmegaWhite (close binary stars) • And plans to support • MegaCAM@CFHT, • Coma legacy Survey ACS • LOFAR

  13. Prologue revisited • Major VO objective: “Data at your fingertips” (Lawrence) • VO-user’s desire: “going backstage” • Data quality assessment by user • “how did the data-provider arrive at its final result exactly?” • Diamond-in-haystack searches • Upper-limits, swamping by false positives, homogenizing psf-dependent photometry (Gilmore, Kuijken) • Statistics of large datasets • Interaction with raw/intermediate data (e.g., weak lensing: Kuijken) • Comparing different routes of analysis (Wolk)

  14. SummaryAstro-Wise: a federated information accumulator for astronomy • “Raw and final data at your fingertips” • traces every bit of final data back to raw data bits • Raw data are sacred • processed data are derivatives continuously adding information to the system • The system is scalable: can be done via federation Find me at IVOA stand to see Astro-Wise working or Contact me for personal demo or Visit www.astro-wise.org or Next astro-wise workshop 20-23 November 2006

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