gavo – after one year h.-m. adorf & the gavo team
TRANSCRIPT
GAVO – after one year
H.-M. Adorf & the GAVO team
ADA III - 29-04-2004
GAVO’s Pillars
Publication and federation of datasets including theoretical ones
Spatial matching & classification & visualization (NGSE)Grid computing
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The GAVO Team
PI: Wolfgang Voges, MPE, GarchingCoI: Matthias Steinmetz, AIP, PotsdamHans-Martin Adorf, MPEHarry Enke, AIPGerard Lemson, MPE
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Collaborations
MPE, Garching (Peter Schuecker)AIP PotsdamCanadian Virtual Obs. (CVO), VictoriaUniversitaetssternw. Muenchen (USM)MPA, Garching (Planck, …)
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GAVO Work Areas
Publication of ROSAT datasets REST-based SCS service (HTTP GET in;
XML, CSV, HTML out) SOAP-based SCS service
MCMCS Download ManagerFuzzy spatial matcherGrid-based detection of galaxy clustersROSAT matcher/classifier service
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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
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SCS
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Result
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VOTable
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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
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MCMCS Download Manager
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MCMCS Download Manager
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Workflow
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Fuzzy spatial matcher
Essential for data miningPrototype 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
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Fuzzy spatial matcher (ctd)
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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
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Workflow
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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
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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
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GAVO Mini-GRID
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Status
Perl scriptsUpgrading the RASS Photon DBSoon integrate the SDSS mirror copy
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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
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Data Flow
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PoseQuery
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DisplayQueryResult
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DisplayMatchResult
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The matching problem
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DisplayXMatchResult
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DisplayClassXResult
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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)
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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
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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?
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Conclusion
GAVO is a small, but ambitious projectTwo Grid applications Detection of galaxy clusters
Globus Toolkit Classification of ROSAT sources
Based on WebServices
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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)