The Virtual Observatory in Australia Connecting to International Initiatives. Peter Lamb. CSIRO Mathematical & Information Sciences
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1 The Virtual Observatory in Australia Connecting to International Initiatives Peter Lamb CSIRO Mathematical & Information Sciences
2 The Grid & escience Convergence of high-performance computing, huge data stores and high-bandwidth computing to: share resources (data/computation/instruments) enhance collaboration allow for new ways of conducting research
3 International Virtual Observatories Alliance Global electronic access to astronomical data archives of space and ground-based observatories & sky surveys Coordination data analysis using common standards, highbandwidth networking & state-ofthe-art analysis tools
4 International Virtual Observatories Alliance UK AstroGrid Australia Aus-VO EU AVO China ChinaVO Canada CVO France VOFrance Germany GAVO Italy DRACO Japan JVO USA NVO Russia RVO India VO-I Korea KVO
5 Aus-VO Projects HI Parkes All- Sky Survey 2QZ spectroscopic quasar survey MACHO archive ATCA archive Machine learning SUMSS 843MHz southern sky survey RAVE radial velocity survey Remote Visualisation
6 IT Challenges Provide a uniform model of observational, derived and modelled data for an entire scientific discipline. Provide a model of computation for tools used to reduce the data. Allow for automatic, assisted and convenient manual assembly of data sources and tools.
7 Radio Interferometry Imaging Raw data to source extraction Amplify, filter, correlate Calibrate, Inverse Fourier Transform Many details omitted! Deconvolve Source extraction
8 Raw data - visibilities Amplify, filter, Visibilities correlate are samples (per frequency channel, polarisation) of the Fourier Transform of the image Visibilities are the data stored in the ATCA archive Can derive images, spectral data cubes, time series, large mosaiced images, etc
9 Dirty Image Calibrate, Inverse Fourier Transform Formed from the Inverse Fourier Transform on the visibilities Has high level of artefacts because of incomplete sampling of the Fourier plane
10 Clean image Deconvolve Deconvolve model of interferometer beam (derived from visibility sample locations) against dirty image, replacing the dirty beam with a clean Gaussian beam Highly underdetermined!
11 Source Extraction Source extraction Fit Gaussian models to bright areas of the image Requires classification of the sources true source, artefact, noise...
12 Merge with other data Search optical VO data
13 IT Demands Large distributed database (ATCA data alone is ~1.8TB) Need common data model Need to describe compose execute data queries and processing
14 Service description Radio Source detection Optical X-Ray Data query Radio imaging
15 Service composition User task description User constraints Service composition Radio Data query Radio imaging Source detection Data query Data query Source detection
16 Where we are Select an area of interest in the sky Assemble or acquire the data sets (does the data I need exist already)? Process/reduce Combine Scientific results
17 Where we want to be State the data and processing requirements Receive the data processed as needed Check the hypothesis Double-check the data and the processing Scientific result; sooner & with less effort
18 What s in the way We have archives, not data access nodes Many kinds of data: radio, optical, X- ray; images, spectra, polarisation maps Much data processing/reduction needed to make inspection, search & fusion possible Data treatment is a craft
19 Questions?
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