Presentation on theme: "IVOA, Kyoto May 16-20 20051 Simple Spectral Access SSA Query Interface Doug Tody (NRAO) Markus Dolensky (ESO) Et. al. International V IRTUAL O BSERVATORY."— Presentation transcript:
IVOA, Kyoto May Simple Spectral Access SSA Query Interface Doug Tody (NRAO) Markus Dolensky (ESO) Et. al. International V IRTUAL O BSERVATORY
IVOA, Kyoto May Concepts - Dataset-oriented Data object type –Spectrum, TimeSeries, SED Dataset creation type –AtlasWhole datasets, uniform survey data –Pointed Whole datasets, variable instrumental data –Cutout Subset, data samples are not modified –Resampled Subset, data samples computed by service Dataset derivation –Observed An observation –Composite Combination of several observations –Simulated Simulated observation made from real data –Synthetic Data from a theoretical model
IVOA, Kyoto May Concepts - Role of data model Multiple data models –VO spectral data model –external data models (project data in archive) Active data model mediation –map external data into VO data model –may involve some loss of project-specific information –but this is generally not needed for analysis –enables general multiwavelength analysis Separation of data model and data representation –same data object can be represented in multiple ways –multiple output formats (VOTable, FITS, text, etc.) Document-oriented vs object API
IVOA, Kyoto May Compliance Minimally compliant service –Implements HTTP GET interface –Input: at least POS, SIZE, FORMAT –Output: all MUST-provide metadata –Support for 1+ compliant output data format (e.g., VOTable) –Service metadata query Fully compliant –Input: all SHOULD-provide parameters –Output: all MUST-provide parameters Advanced service –Multiple interfaces (GET, WS, ADQL eventually) –Additional optional or service-defined input/output parameters –Can return data in any whatever format the client wants
IVOA, Kyoto May Basic Usage Simple query –POS, SIZE - like cone search –Possibly refined by spectral or time bandpass, etc. –Most metadata in query response is optional Data retrieval –URL-based –Get back a dataset (normally VOTable or FITS) –In simplest case could be wavelength, flux as text (for Spectrum) –Or external data pass-through
IVOA, Kyoto May Query Interface Mandatory query parameters –POSRA, DEC (ICRS) –SIZEdiameter (decimal degrees) –FORMATVOTable, fits, xml, text, graphics, html, external Should other parameters be mandatory? –e.g., BANDPASS, TIME, SPECRES, APERTURE
IVOA, Kyoto May Query Interface Recommended query parameters –BANDPASSwave1,wave2 (meters in vacuum; source or observer) –TIME data1,date2 (epoch in decimal years UTC) –APERTURE approx spatial resolution (decimal degrees) –SPECRES spectral resolution (meters) –TOP number of top-ranked records to return Should other parameters be recommended? –e.g., SNR, OBJTYPE, COLLECTION, CREATORID, PUBID
IVOA, Kyoto May Query Interface Optional parameters –OBJTYPEmandatory if service returns multiple object types –COLLECTIONdata collection identifier (short name) –CREATORID creator-assigned dataset identifier (at most 1) –PUBIDpublisher-assigned dataset identifier (at most N) –COMPRESSenable compression (for both data _and_ queries?) –SNR signal-to-noise ratio –REDSHIFT redshift range (dlambda/lambda) –TARGETCLASSstar, galaxy, pulsar, PN, QSO, AGN, etc.
IVOA, Kyoto May Query Interface Service-defined parameters –Service may define additional parameters describe in service metadata –Query-by-Utype has been suggested probably better to just do ADQL; need expressions etc.
IVOA, Kyoto May Query Response Format –VOTable –Utype used to identify interface elements Includes both protocol and data model –Standard metadata is in a flat table Optional extension metadata may be included
IVOA, Kyoto May Query Response Classes of query metadata –Query metadataDescribes the query itself –Dataset metadataDescribes data object; object-specific –Target metadata Astronomical target –Curation metadata External identification of dataset –Characterization Coverage, Accuracy, Frame, etc. –Instrument metadata Service-defined; hard to standardize –Access metadata Describes how to access the dataset
IVOA, Kyoto May Query Response Query Metadata –Query.ScoreHow well object matches query –Query.LNameLogical name (identifier) –Query.LNameKeyLogical name key (id-ref) Example: LName="MyObj123" LNameKey="server,format"
IVOA, Kyoto May Query Response Dataset Metadata –Dataset.Type Spectrum, TimeSeries, SED, etc. –Dataset.DataModel DM name, e.g., "SSA-V0.90" –Dataset.Title Brief descriptive title of dataset –Dataset.SSA.NSamples Total samples in dataset Dataset.SSA.Aperture Characteristic aperture diameter –Dataset.SSA.TimeAxis TimeCoord axis (external data) –.SSA.SpectralAxis SpectralCoord axis (external data) –Dataset.SSA.FluxAxis Flux axis (external data) –Dataset.CreationType atlas, pointed, cutout, resampled –Dataset.Derivation observed, composite, simulated, synthetic
IVOA, Kyoto May Query Response Target Metadata –Target.NameName of astronomical object –Target.Class Target class (star, galaxy, QSO, etc.) –Target.SpectralClassSpectral class (e.g., 'O', 'B', etc.) –Target.Redshift Nominal redshift for object –Derived.VarAmpl Variability amplitude (fraction 0-1) –Derived.SNR Observed signal to noise ratio
IVOA, Kyoto May Query Response Curation Metadata –Curation.CollectionData collection name (identifier) –Curation.Creator Creator identify (identifier) –Curation.CreatorID Creator-assigned dataset identifier –Curation.PublisherID Publisher-assigned dataset identifier –Curation.Date Dataset creation date (ISO date string) –Curation.Version Dataset version (within same ID)
IVOA, Kyoto May Query Response Characterization1 - Coverage –.Location.SpatialPosition (e.g., RA, DEC) –.Location.Time Observation time characteristic value –.Location.Spectral Spectral bandpass characteristic value –.Location.Spectral.BandID Bandpass ID (band or filter name) –.Bounds.Spatial Aperture footprint (polygon on sky) –.Bounds.Time Low/High time values –.Bounds.Spectral Low/High spectral values –.Bounds.Flux Limiting flux, saturation limit (Jansky) –.Fill.Spatial Spatial sampling filling factor (0-1) –.Fill.Time Time sampling filling factor (0-1) –.Fill.Spectral Spectral sampling filling factor (0-1)
IVOA, Kyoto May Query Response Characterization2 - Accuracy –Accuracy.*.Calibrateduncalibrated, relative, absolute –Accuracy.*.Resolution Resolution of measured signal –Accuracy.*.StatErr Statistical error (measured) –Accuracy.*.SysErr Systematic error (estimated) ('*' = Spatial, Time, Spectral, Flux)
IVOA, Kyoto May Query Response Characterization3 - Reference Frames –Frame.Spatial.TypeCoordinate frame (default ICRS) –Frame.Spatial.Equinox Coordinate system equinox (J2000) –Frame.Time.System Timescale (TT) –Frame.Time.SIDim SI factor and dimension –Frame.Spectral.SIDim SI factor and dimension –Frame.Flux.SIDim SI factor and dimension –Frame.Flux.UCD UCD of flux value (flux type) (These apply only to the query response) (SIDim metadata still under construction)
IVOA, Kyoto May Query Response Instrument Metadata –Instrument.NameInstrument name (identifier) –Instrument.Exposure Total exposure time (seconds) –Instrument. Service-defined Notes –Optional; provided for instrumental data collections –In general, Collection, Bounds.Time, etc. are preferred –In general Instrument metadata is service-defined –Use Observation model as a starting point
IVOA, Kyoto May Query Response Access Metadata –Access.ReferenceData access URL –Access.Format MIME type of returned dataset –Access.Size Approximate dataset size (bytes) –Access.Server Server endpoint URL Staging support goes here in the future –e.g., will dataset access require asynchronous staging –estimated cost to construct dataset
IVOA, Kyoto May Service Metadata Usage –Describe service type and capabilities –Characterize service (data resources served, coverage, etc.) –Describe interface (optional query parameters) Interface –Requires new service metadata query method –Returns resource metadata descriptor (XML) Issue: –Registry resource descriptor (XML) or VOTable as in SIA?
IVOA, Kyoto May SSA/SED Data Model Issues #1 What is the overall concept? –SSA sees Datasets of several types Spectrum, TimeSeries, SED are all top-level Dataset objects Most metadata in the query response applies to all datasets –SED Model SED model sees Spectrum, TimeSeries as special case of SED Model a class of spectral data or model SEDs? Segment is core of spectral (SED) data model
IVOA, Kyoto May SSA/SED Data Model Issues #2 Subclassing vs aggregation –Class root is Dataset –Subclass Image, Spectrum, etc. –Aggregate component data models to model each type dataset Component Models –Why [SSA,SED].Segment.Coverage instead of just Coverage? –Query, Dataset, Curation, Coverage, etc. are components –Can be reused in both SSA query response and in dataset object