Multidimensional Data in the VO
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Multidimensional Data in the VO

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Multidimensional Data in the VO Multidimensional Data in the VO Presentation Transcript

  • Multidimensional Data in the Virtual Observatory Jose Enrique Ruiz del Mazo Tutora: Dr. Lourdes Verdes-Montenegro IAA - CSIC Máster FISYMAT Trabajo de Investigación Tutelada Universidad de Granada Diciembre 2010
  • SUMMARYContext• The AMIGA project• The Virtual Observatory• Multidimensional Data in Astronomy• AMIGA VO ContributionsGeneric Datasets• Data Discovery• Data AccessGeneric Dataset Discovery Service• Input Parameters• Query Response• ImplementationConclusions and Future Work
  • AMIGAAnalysis of the interstellar Medium of Isolated GAlaxiesPI : Dr. Lourdes Verdes-MontenegroIAA-CSIC, IRAMhttp://amiga.iaa.esObs. Marseille, Obs. Paris, CfA, ASIAA, MPIfA, IAC,Univ. Alabama, Mc Donald Observatory, Arcetri, UNAM,Kapteyn Astronomical Institute Need of a statistically significant sample of isolated galaxies, in order to provide a baseline to compare with the behaviour of galaxies in denser environments Multiλ analysis ~1000 galaxias + Need of intensive and complex analysis of 3D data 2D spatial + 1 Velocity
  • VIRTUAL OBSERVATORYThe Virtual Observatory is an infrastructure of interoperable data and services.IVOA provides technical standards for :• Providers to share data and services• Developers of applications to discover the services, find and access the dataThe final goal is that astronomers use this data infrastructure in a seamless way
  • VIRTUAL OBSERVATORYThe Virtual Observatory is an infrastructure of interoperable data and services.IVOA provides technical standards for :• Providers to share data and services• Developers of applications to discover the services, find and access the dataThe final goal is that astronomers use this data infrastructure in a seamless way
  • VIRTUAL OBSERVATORYThe Virtual Observatory is an infrastructure of interoperable data and services.IVOA provides technical standards for :• Providers to share data and services• Developers of applications to discover the services, find and access the dataThe final goal is that astronomers use this data infrastructure in a seamless way
  • VIRTUAL OBSERVATORYThe Virtual Observatory is an infrastructure of interoperable data and services.IVOA provides technical standards for :• Providers to share data and services• Developers of applications to discover the services, find and access the dataThe final goal is that astronomers use this data infrastructure in a seamless way
  • MULTIDIMENSIONAL DATAObservational Techniques• Radiointerferometry• Integral Field Spectroscopy• Multi Object Spectroscopy• Fabry-Perot Instruments• OTF Imaging Credit Stephen Todd and Douglas Pierce-Price Credit M. Westmoquette
  • AMIGA VO CONTRIBUTIONSAMIGA Catalog• ConeSearch Service• Web InterfaceRADAMSRadio Astronomy Data Model for Single-dish telescopesJuan de Dios Santader-VelaRobledo DSS-63 VO Archive• ConeSearch Service• SSA Service• Web InterfaceTAPASTelescope Archive for Public Access SystemIRAM-30m VO Archive• ConeSearch Service• Web Interface
  • GENERIC DATASETSTyped Datasets SIMPLE ACCESS PROTOCOLS• Tabular Data• 1D Spectra• 2D Images• 3D Cubes• Time Series
  • GENERIC DATASETSTyped Datasets SIMPLE ACCESS PROTOCOLS• Tabular Data• 1D Spectra• 2D Images• 3D Cubes• Time SeriesGeneric / MultiTyped DatasetsComplex data associations of different individual typesSurvey Field• Spectral data cube• 2D projections/extractions of the cube• Source catalog computed from the 2-D continuum• Some extracted spectra of objects in the field
  • GENERIC DATASETSTyped Datasets SIMPLE ACCESS PROTOCOLS• Tabular Data• 1D Spectra• 2D Images• 3D Cubes• Time SeriesGeneric / MultiTyped DatasetsComplex data associations of different individual typesSurvey Field• Spectral data cube• 2D projections/extractions of the cube• Source catalog computed from the 2-D continuum• Some extracted spectra of objects in the field
  • DATA DISCOVERYAssociated Data Collections• Simple Access Protocols perform discovery of associated data• Present IVOA models provide full description• REF-ID mechanism in VOTable allow association of data• RESOURCE mechanism in VOTable allow metadata extension
  • DATA DISCOVERYAssociated Data Collections• Simple Access Protocols perform discovery of associated data• Present IVOA models provide full description• REF-ID mechanism in VOTable allow association of data• RESOURCE mechanism in VOTable allow metadata extensionIssues• Original data products can be very large, worsening transfer rates and latency• Clients applications do not support all native observatory-dependent formats• Users are often not interested in the whole product but in a smaller portion
  • DATA DISCOVERYAssociated Data Collections• Simple Access Protocols perform discovery of associated data• Present IVOA models provide full description• REF-ID mechanism in VOTable allow association of data• RESOURCE mechanism in VOTable allow metadata extensionIssues• Original data products can be very large, worsening transfer rates and latency• Clients applications do not support all native observatory-dependent formats• Users are often not interested in the whole product but in a smaller portionVirtual Data from Uniformly Sampled Datasets• Data generated on-the-fly at access time based on user demands• Discovery implies negotiation with the service for access methods• WCS metadata needed for most virtual data generation
  • DATA ACCESSVirtual Data generation may requireasynchronous services deployed ondistributed GRID architecturesWhole datasetFiltering/FlaggingSpectrum extraction2D slices extractionDimensional reductionCutout 3D sub-cubeGeneral 2D projectionGeneral 3D projectionGeneral 2D slices through a 3D cubeComplex transformations
  • GDS DISCOVERY INPUTSREQUEST=queryData SPECRES SPATRESPOS TIMERES RESOLUTIONSIZE FLUXLIMITBAND SNR PRECISIONTIME VARAMPL SENSITIVITYPOL FLUXCALIB COVERAGEFORMAT WAVECALIB ASTCALIBREDSHIFTREGION PUBIDINTERSECT CREATORID PUBLISHER COLLECTIONTARGETNAME MTIMETARGETCLASS TARGETTYPE TOP MAXREC SERVICE COMPRESS RUNID
  • GDS DISCOVERY OUTPUTQueryAssociationAccessDataSet: Declaration of Spatial, Time and Polarization Axis CONSISTENCYDataIDProvenance: BeamMajorAxis, BeamMinorAxis, BeamPositionAngle INSTRUMENTALCurationTarget: VelocityDerived: DerivedVelocity, VelocityStatError, VelocityConfidence PHYSICS VarAmplStatError, VarAmplConfidenceCoordSys: RedshiftFrameUcdChar.SpatialAxisChar.SpectralAxisChar.TimeAxis CONSISTENCYChar.FluxAxis: FluxAverage, FluxMin, FluxSaturation, FluxSupportExtentChar.PolarizationAxis PHYSICS
  • GDS IMPLEMENTATION
  • GDS IMPLEMENTATION
  • GDS IMPLEMENTATION
  • accessData
  • getCapabilities
  • CONCLUSIONS• Study of the state of the art of both MultiD data in Astronomy and Protocols in the VO• Determine the best strategy for discovery and access of complex MultiD datasets• Propose Discovery Method for a GDS conceived in the less possible intrusive way• Reuse of existing VO Data Models and VO Protocols with minor modifications• Implementation of the proposed Discovery Method for a GDS
  • FUTURE WORK• Virtual Data generation and accesData standards needed• Achieve final IVOA recommendation for MultiD discovery and access VO protocols• Upcoming facilities will provide 3D datacubes and services to access and use them• getCapabilities method is key for interoperability among services• Conception and development of VO Scientific Workflows for 3D Data Analysis• EU funded project Wf4Ever Advanced Workflow Preservation Technologies for Enhanced Sience