Gavo after one year
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GAVO – after one year. H.-M. Adorf & the GAVO team. GAVO’s Pillars. Publication and federation of datasets including theoretical ones Spatial matching & classification & visualization (NGSE) Grid computing. The GAVO Team. PI: Wolfgang Voges, MPE, Garching

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GAVO – after one year

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Gavo after one year

GAVO – after one year

H.-M. Adorf & the GAVO team


Gavo s pillars

GAVO’s Pillars

  • Publication and federation of datasets

    • including theoretical ones

  • Spatial matching & classification & visualization (NGSE)

  • Grid computing


The gavo team

The GAVO Team

  • PI: Wolfgang Voges, MPE, Garching

  • CoI: Matthias Steinmetz, AIP, Potsdam

  • Hans-Martin Adorf, MPE

  • Harry Enke, AIP

  • Gerard Lemson, MPE


Collaborations

Collaborations

  • MPE, Garching (Peter Schuecker)

  • AIP Potsdam

  • Canadian Virtual Obs. (CVO), Victoria

  • Universitaetssternw. Muenchen (USM)

  • MPA, Garching (Planck, …)


Gavo work areas

GAVO Work Areas

  • Publication of ROSAT datasets

    • REST-based SCS service (HTTP GET in; XML, CSV, HTML out)

    • SOAP-based SCS service

  • MCMCS Download Manager

  • Fuzzy spatial matcher

  • Grid-based detection of galaxy clusters

  • ROSAT matcher/classifier service


Rosat all sky survey rass

ROSAT All-Sky Survey (RASS)

  • BSC, FSC & Photons

  • VO-compatibility:

    • Input: Simple cone search

    • Output: VOTable, …

  • New features

    • Exposure times

    • Galactic & Cartesian coordinates

    • Healpix indices


Gavo after one year

SCS


Result

Result


Votable

VOTable


Mcmcs download manager

MCMCS Download Manager

  • Tool …

    • … accesses registry at JHU

  • User …

    • … selects up to 70 distributed catalogues

    • … specifies one or more sky-locations

  • Tool …

    • … queries remote catalogues

    • … retrieves datasets (VOTables) for further processing


Mcmcs download manager1

MCMCS Download Manager


Mcmcs download manager2

MCMCS Download Manager


Workflow

Workflow


Fuzzy spatial matcher

Fuzzy spatial matcher

  • Essential for data mining

  • Prototype features

    • Performs “fuzzy” match between pairs of source lists from different catalogues

    • Computes probability of real match based on astrometric uncertainties

  • Moving matcher into production use

    • Currently exported to Canadian Virtual Observatory

    • Feeding matches to ClassX classifier

  • Long-term goal: assemble an SED


  • Fuzzy spatial matcher ctd

    Fuzzy spatial matcher (ctd)


    Grid computing

    Grid computing

    • What is Grid-computing?

      • Globus Toolkit, SGE, EJBs

      • WebServices

    • Detection of galaxy clusters

      • using RASS photons, SDSS

    • RASS source classification

      • using RASS B/FSC, SUMSS, NVSS, USNO


    Workflow1

    Workflow


    Galaxy cluster detection

    Galaxy-cluster detection

    • Search for galaxy clusters in heterogeneous databases

      • RASS photons

      • SDSS

    • Software

      • FORTRAN 90 code (data analysis)

      • Perl scripts (data/grid management)

      • Globus Toolkit


    Galaxy cluster detection1

    Galaxy-cluster detection

    • Components

      • Setup script

        • Sets up the directory structure

        • Distributes the software across the grid

      • Execution script

        • Triggers the parallel execution on the compute nodes

      • Data collection script

        • Retrieves the results from the compute nodes


    Gavo mini grid

    GAVO Mini-GRID


    Status

    Status

    • Perl scripts

    • Upgrading the RASS Photon DB

    • Soon integrate the SDSS mirror copy


    Rass source classifier

    RASS-source classifier

    • ClassX: international collaboration

      • T.A. McGlynn, A.A. Suchkov, E.L. Winter, R.J. Hanisch, R.L. White, F. Ochsenbein, S. Derriere, W. Voges, M.F. Corcoran

  • Requires data from several sky-surveys

    • X-ray: ROSAT BSC+FSC

    • Optical: USNO, (SDSS)

    • Infrared: (2MASS)

    • Radio: FIRST, NVSS, SUMSS

  • Distributed multi-wavelength VO-application


  • Data flow

    Data Flow


    Posequery

    PoseQuery


    Displayqueryresult

    DisplayQueryResult


    Displaymatchresult

    DisplayMatchResult


    The matching problem

    The matching problem


    Displayxmatchresult

    DisplayXMatchResult


    Displayclassxresult

    DisplayClassXResult


    Rass source classifier1

    RASS-source classifier

    • State & session management

      • Using Java Servlet session mechanism

      • Internal abstract state machine

    • Strong points

      • End-to-end VO-application

      • Works with lists of objects / sky-coordinates

      • Accesses several distributed databases

      • Uses deterministic matcher (at Vizier and SDSS)

      • Uses probabilistic matcher (at GAVO)

      • Uses data analysis service (at NASA)


    Rass source classifier2

    RASS-source classifier

    • Future work

      • Use IVOA-standards or protocols

        • VOTable

        • WSDL, SOAP-based Web Services

        • Add graphics

      • Multi-threaded

      • Modularize, generalize and make S/W configurable


    Rass source classifier3

    RASS-source classifier

    • Open questions

      • Is an HTML form-based GUI sufficiently powerful to control a complex grid application?

      • What are the user expectations wrt the workflow?

      • Is there a standard workflow that one could use / agree upon?


    Conclusion

    Conclusion

    • GAVO is a small, but ambitious project

    • Two Grid applications

      • Detection of galaxy clusters

        • Globus Toolkit

      • Classification of ROSAT sources

        • Based on WebServices


    References

    References

    • GAVO Mid-Term Report, 90 pages, http://www.g-vo.org (soon)

    • Detection of X-ray Clusters of Galaxies by Matching RASS Photons and SDSS Galaxies within GAVO, P. Schuecker, H. Boehringer, W. Voges, A&A (submitted)

    • Automated classification of ROSAT sources using heterogeneous multiwavelength catalogs, T.A. McGlynn et al., ApJ (submitted)


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