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CDS , F.Bonnarel, A.Oberto et all. LSIIT , M.Louys, C.Collet IAP , P.Didelon, Y.Mellier, E.Bertin

IDHA : Images Distribuées Hétérogènes pour l’Astronomie Distribution of Heterogeneous Image data in Astronomy. CDS , F.Bonnarel, A.Oberto et all. LSIIT , M.Louys, C.Collet IAP , P.Didelon, Y.Mellier, E.Bertin QUB , F.Murtagh ACI-GRID project. Images in astronomy.

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CDS , F.Bonnarel, A.Oberto et all. LSIIT , M.Louys, C.Collet IAP , P.Didelon, Y.Mellier, E.Bertin

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  1. IDHA : Images Distribuées Hétérogènes pour l’AstronomieDistribution of Heterogeneous Image data in Astronomy CDS, F.Bonnarel, A.Oberto et all. LSIIT, M.Louys, C.Collet IAP, P.Didelon, Y.Mellier, E.Bertin QUB, F.Murtagh ACI-GRID project

  2. Images in astronomy • Metadata definition for image sets in diverse archives. • Multicolor image analysis for object recognition and cross identification. M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  3. Metadata for astronomical images • Goal: To provide a model for astronomical image data: • General in content: supports the information available in different archive servers (observatories, surveys). • Logical in design: includes the different steps of data production, from raw measurements to final products. • Science-oriented:well-suited to user query types. • Strategy: • UML model, XML data description. M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  4. From Data Model to XML description • The Data Model : • It is a road-map to identify and describe the different kinds of information available on images and their relationships. • Metadata can deal with: • Observation process, instruments,reduction process, image storage and distribution. http://alinda.u-strasbg.fr/IDHA/lastmodel M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  5. The XML documents • Describe partial views of the DM • Correspond to user queries • Object  resource in a V0table • Attributes  Field of a table • Simple queriesObservingProgram.xml ObservingGroup.xml ProcObservation.xml M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  6. Structuring image description • Collections of images  factorize common information. • Goods demogoods_idha2.xml M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  7. IDHA data model development plan • Sketch out a model description of astronomical image data . • Implement and test the model and XML description in the context of the Aladin server. • Compare/Extend to other archives • Test it for the AVO/Goods demo(Jan03). • Ask for more input and criticism. M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  8. Problems: • Factorize general information for data collections (uniqueness, simplicity) • Allow different levels of detail • Coarse to fine according to the user’s goal: visualise, process, cross-identify, etc… • Data models in the VO context : Homogenize object names and attributes • Define a dictionary/thesaurus? • Tag content with UCDs ? M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  9. feedback Observation Reduction Visualisation Interpretation V0 Tools Instrument Scientific goal Technique Build in VO evolution • Data (image) interpretation is the result of a process. • Support versionning, on the fly calibration, ... M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

  10. Conclusion • Common modeling effort exists in the IVOA. (DM Boston meeting) • Develop compatible metadata objects in the UML/XML framework. • Define the properties of a VO recommended datamodel. Next steps: • Compare data models and identify common concepts. • Define some standardized vocabulary and/or tagging method to describe common metadata. M.Louys, Data Models for astronomical images, Nov.28-29, 2002 LSIIT

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