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Web + VO + Database Technologies = HLA Footprints

Web + VO + Database Technologies = HLA Footprints. STScI : Gretchen Greene, Steve Lubow, Brian McLean, Rick White and the HLA Team JHU : Alex Szalay and Tamas Budavari NVO. Astronomical Application.

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Web + VO + Database Technologies = HLA Footprints

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  1. Web + VO + Database Technologies = HLA Footprints STScI: Gretchen Greene, Steve Lubow, Brian McLean, Rick White and the HLA Team JHU: Alex Szalay and Tamas Budavari NVO

  2. Astronomical Application Archival Research is a value added product to observation planning as well as data mining • HasHST observed in this location of the sky? • Which wavelength?, how long?, what instrument?, what was the exact coverage with respect to object XYZ? • Show the coverage for a high level product, e.g. Hubble Deep Field, GOODS mosaics, ALL overlapping ACS exposures of a specific field • I have a transient even (e.g. VOEvent notification), what is the coverage in HST? • How does HST coverage compare to another observatory coverage? • Large scale distributed spatial queries • NVO search portal

  3. HST Footprints in the HLA • HLA Footprints are spatially precise geometric descriptions of the HST observed areas in the sky • Current holdings include reprocessed ACS fields (~20% of the completed observations), all sky WFPC2 and STIS • In transition are NICMOS, remaining ACS, FOS & GHRS • Collaborations in process with NICMOS grism spectra, SPITZER…. • Accessible via web client or programmatic interfaces

  4. Widespread Footprint Development The (GALEX) MAP - (adaptable to other missions) • GALEX (STScI ) • NOAO VO Portal • Aladin(via APT) • IVOA (International Virtual Observatory) note for Footprint Overlay specification • VOServices (JHU) Sky section or image plane: pans, zooms, downloads data.

  5. Web components • Web portal built on a suite of web services (SOAP, http) using SOA • Reusable components mostly in form of XML • User requirements reduced significantly • Network access & a browser (FIREFOX) • No installation required • Technologies are independent of platformand consistent with everyday lifestyle • XML, XSLT processors, Javascript, ASPX • Performance on the web client looks favorable • accept delay or switch to server side processing for large scale requests • Javascript security issues require proxy management

  6. HLA Web Portal - Footprints Javascript UI manager (state and form control) VOTable VO Cone Search VOClients RA,Dec,Radius Object Parser XML Instance GOOGLE IIS Web Server APT ASPX + JS IFRAME IFRAME SOAP STC Web Services SQL Server Footprint DB (with HTM) SQL Server DSS DB (with HTM)

  7. Virtual Observatory • Footprints are built on IVOA standard STC XML data model (Space Time Coordinate) • Regions, Convexes, Reference Frames + much much more • Data Access Layer services are built on standard VO protocols • Cone Search • Simple Image Access (SIA) • XML across the wire in VOTable or STC format • VO client applications can access HLA footprint programmatic services: • Datascope, Registry, Aladin, GOOGLE? • IVOA note on Footprint Overlay Specification

  8. Database => Performance Key • Microsoft SQL Server • Client development DOES NOT have to be on WINDOWS • Virtualization tools (Parallels, Remote Desk Top) • FreeTDS • SQL scripts • manage footprint computation of STC table objects/fields • Build and populate the different levels of representation • HTM (Hierarchical Triangulated Mesh) integrated for spatial search index • Coordinate based searching • Accessed via stored procedures and user defined functions • Bounding circles for each region convex have htmids

  9. DB Schema STC • DB Tables map to XML elements in the schema • HLA Science table associates regions to science metadata tags (target, exposure, dataset, filter, PI …)

  10. JHU Spherical Library • Spherical geometry library • Exact equations for highly accurate region definitions, leverages HTM • STC elements are class types (region, convex, halfspace…) • C# Assembly (SQL Server dll ) • Operations for combining regions • Unions (outlines) • Intersections (overlaps) • Mathematical Solutions • Area • Complex regions can be made disjoint into convexes

  11. Hierarchical Representations • Exposures (Level 1) • Stacks(Level 1 – visualization optimization) • Combined sequential exposures (Level 2) • Groups (Level 3 & 4) • Mosaics, weight maps, use-defined, custom constrained • Fractals • Performance Issues for crowded overlaps • HST unique distribution • sparse ALL-SKY

  12. Exposure Stacks • Many cases where exposures lie on top of each other (form a stack) • Can reduce overhead by graphically representing exposures in a stack by a single member exposure • Define stacks using coarse-grained HTM matching for aperture vertices.

  13. Visualization library • C# library with building canvas, frame, scaling and drawing methods using GDI • DSS background image access using spherical projection and tiling algorithms • ASPX is ~ html with C# class associated. • ASP controls for basic web gui features • Javascript for interactive mouse and cursor state • Event handling between the graphics and table paging control for selection

  14. Challenges Ahead • Enhanced capabilities for visualization • Completion of IVOA standard footprint services • Community exchange of STScI Footprint schema • Validation of footprint representations between existing tools (Starview/APT, HLA, external…) • Development of higher level product respresentations (MOSAICS, user-defined…) • Storing Region binary blob representations

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