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MIZAR : space in the pocket

MIZAR : space in the pocket. Fabien Lavignotte. Telespazio. CNES. Jean Christophe Malapert. San Sebastien, 21 june 2013. Summary. 1. Context. 2. MIZAR presentation. 3. Technical details. Context. Use case : Data quality.

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MIZAR : space in the pocket

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  1. MIZAR : space in the pocket Fabien Lavignotte Telespazio CNES Jean Christophe Malapert San Sebastien, 21 june 2013

  2. Summary 1 Context 2 MIZAR presentation 3 Technicaldetails

  3. Context

  4. Use case : Data quality

  5. Use case : Stellar Evolution (Spectral energy distribution)

  6. Use case : Stellarevolution (temporal detection)

  7. Asteroiddetection (by temporal comparison or by superimposing a referencecatalog)

  8. Use case : Find an objectname and related publications

  9. How to aggregate information comingfromdifferent data providers Images Instrument Footprints Object catalogs Spectra

  10. Why a webGL application ? Web : High accessibility, connectfromeverywhere 3D : A globe => no distortionat pole webGL : Use of graphicalcard power

  11. Summary 1 Context 2 MIZAR presentation 3 Technicaldetails

  12. Mizar MIZAR • Module for Interactive viZualization in AstronomicalRepositories http://sitools2.sourceforge.net/ Release date : December

  13. Mizar, its architecture

  14. Mizar’sfeatures Browsing Background Images Queryform « survey » coverage& intersection CSP & SIAP Use itsown information services Configuration Open source

  15. Summary 1 Context 2 MIZAR presentation 3 Technicaldetails

  16. GlobWeb • Virtual globe in WebGL3D • Developed by TPZF as a R&D project • Licence LGPLv3 • https://github.com/TPZF/GlobWeb

  17. GlobWeb for astronomical data «AstroWeb » • « Inside » the virtual globe • Same algorithmes but… • Specifictiling for astronomical data • HEALPix

  18. HEALPix • Map the sphere to 12 base “pixels” • Quadtree subdivision of each base pixel • Properties • Areas of all pixels at a given resolution are identical • Pixels are distributed on lines of constant latitude

  19. GlobWeb for astronomical data • Observations • Points or polygons • Received as GeoJSON • High data volumetry : • Thousand of visible observations • Automatic batch of points and polygons per HEALPixtile • Bucket to batch points and polygons sharing the same style

  20. Managing data volumetry • Point clustering • Given a data distribution • MOC • Multi-Ordercoverage

  21. Display astronomical image • FITS • Flexible Image Transport System • ASCII header + binary data • High dynamic range data • Float support needed • Basic tonemapping (Linear, Log) • zScaleused in astronomy

  22. GlobWeb : architecture • Base class

  23. GlobWeb : architecture • Base class

  24. GlobWeb usage Usage • PlanetObserverdemonstration • ESA prototype : EoliWebGL • MIZAR • ESA ngEO • InterAtlasdemonstration

  25. Questions ?

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