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12 Oct 2003VO Tutorial, ADASS Strasbourg, 20031 Data Access Layer (DAL) Tutorial Doug Tody, National Radio Astronomy Observatory T HE US N ATIONAL V IRTUAL.

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Presentation on theme: "12 Oct 2003VO Tutorial, ADASS Strasbourg, 20031 Data Access Layer (DAL) Tutorial Doug Tody, National Radio Astronomy Observatory T HE US N ATIONAL V IRTUAL."— Presentation transcript:

1 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20031 Data Access Layer (DAL) Tutorial Doug Tody, National Radio Astronomy Observatory T HE US N ATIONAL V IRTUAL O BSERVATORY

2 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20032 Agenda –DAL Overview and Concepts (Doug Tody) –Server, Client HowTo How to Implement the DAL Cone Search and SIA services (Gretchen Greene) How to Navigate VO Datasets Using VO Protocols (Tom McGlynn) –How to Adapt Existing Archives to SIA The XMM-Newton and ISO Cases (Pedro Osuna) CDS Aladin Image Service and Client Viewer (Francois Bonnarel)

3 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20033 DAL Overview and Concepts What is the Data Access Layer (DAL)? –portal for VO applications development –consists of a family of data access services –services provide access to both data and computation –services integrate other VO technologies VOTable, ADQL, data models, UCD, etc. What DAL enables –distributed, multiwavelength data analysis applications –applications may be either end-user, or VO analysis services

4 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20034 DAL Architecture Usage –registry used to discover services –DAL services provide access to VO resources –distributed client applications use these services Access Protocols –data access protocols define each service –access protocols are neutral middleware not a user interface! implementation not constrained (e.g., language, technology) server, client not constrained Information Model –information model independent of low level protocol –HTTP GET now, Web, Grid services later –service back-end can be of any complexity

5 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20035 Family of DAL Services Service Types –image, table, spectrum, time series, etc. Data model-based data access –each services implements a specific data model –the same data can be viewed via different services e.g., event list or visibility data as image or spectrum

6 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20036 Current DAL Services Cone search –access to astronomical catalogs –simple query based on position, search radius –returns a VOTable containing results Simple Image Access (SIA) –uniform access to image archives –atlas and pointed image archives –image cutouts, image mosaics –image is returned as a FITS file or graphics file Simple Spectral Access (SSA) –currently being specified –access to 1D spectra and SEDs –spectra is returned as ascii, VOTable, FITS

7 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20037 Basic DAL Service Interface Registry used to discover services or data –registry query is optional –data query will locate services providing desired data –service query will find services by type Data query against specific service –returns a VOTable listing datasets which satisfy query Dataset access –returns an individual object of the specified type –service metadata query –describes the capabilities of an individual service

8 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20038 Key Concepts Data discovery –find data based on its type and attributes Data provenance –what is this data and where did it come from? Data characterization –observation time, spectral bandpass, resolution, sensitivity, etc. Virtual data –data is generated upon demand to match query (e.g., image cutout) –server-side analysis or transformation functions Data models, data mediation –map external data into a VO data model (image, spectrum, etc.) –map VO data model to a client API –necessary to deal with heterogeneous, multiwavelength data

9 12 Oct 2003VO Tutorial, ADASS Strasbourg, 20039 DAL Roadmap Future evolution of the DAL services –broader range of services –spectra, time series, NDimage, etc. –service sophistication will evolve as VO technology develops and as reference code becomes available Grid computing –component frameworks –distributed, scalable computation (uniprocessor, cluster, grid) –astronomical data analysis components execute in any context –integrate VO with everyday astronomical data analysis


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