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20 Nov, 2002 Virtual Molonglo Observatory 1
“The VO in Australia” Melbourne Nov. 28/29 2002
What is the AVO? How did it develop - Grid computing
– particle physics Current status of International VO
projects (http://www.ivoa.net) Role for Australian Astronomy? Opportunities & challenges
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What is the Virtual Observatory?
NOT one project or the Web Distributed CPU – AVO, NVO,
ASTROGRID Distributed data – images, catalogues,
spectra, simulations & models Distributed software – assorted
acronyms Resource broker, road map, nodes
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What’s it all about?
Grid computing deals with coordinated resource sharing
and problem solving in dynamic, multi-institutional virtual organisations. The
resources are compute power, software, data and collaboration tools.
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Some statistics on doubling times
Computing power (Moore’s law): 18 mths
Bandwidth (Nielsen’s law): 20 mths Data archive size: 12 mths Number of websites: 9 mths
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Challenges & responses
Slow CPU growth distributed computing
Limited BW information hierarchies Limited storage distributed data Data diversity interoperability
SOLUTION: GRID COMPUTING
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Technical Update
Big commitment in Europe & USA Wide applications – business &
science VO-compliance & VO-table Issues of access, security, universal
querator, resource broker
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Role of Australian Astronomy
Workshop focus on data and tools Examples of current possibilities Challenges and opportunities
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20 Nov, 2002 Virtual Molonglo Observatory 8AVO Project Management
Functional Requirements: A First Draft
• Immediate processing of data from sensors (all s)
• Formats for raw data in sensor databases
• Transparent access to all databases
• Correlation of data sets across databases
• Facilitation and acceleration of the scientific method using all databases
Gavin Thoms 27 November 2002
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1. AAO & the IVOA - Strategy
Build/continue alliances with key groups
Assist in development of VO standards
Build VO-compliance into data & products
Facilitate development of analysis tools
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The Way forward: ARC grant for 2003 (1.5FTE@AAO)
Incorporate 2dF survey into VO-table (milestone: demo at IAU GA)
Integrate 2dF spectra & catalogue server (milestone: end 2003)
VO-compliance for 6dF from start (milestone: April 2003)
Route map for AAO VO-compliance (milestone: end 2003)
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2. Contribution from the Molonglo Observatory
Image availability - data calibration & quality
Source catalogues – integrity and interpretation
What is raw data? Case study at 408 MHz
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Response Classification with a Decision Tree
Blue ellipses - SourcesRed ellipses - Artefacts
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Current data pipeline
Automated observations Manual transport of data (CDs) to
Sydney Customised analysis software programs Image archive & source catalogue Processed data back to Molonglo & Web Resource intensive
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3. Machine Learning techniques
Goal – multiwavelength correlations Problem – database mismatches Traditional methods – closest
position & other information
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X
Y
(A)
(B)
RADIO: HIPASS 21cm survey OPTICAL: SuperCOSMOS
10 arc min error diameterThe correlation problem: which is the radio source?
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Use Machine Learning
Data vectors from catalogues Radio: RA, Dec, velocity, velocity width, flux Optical: (RA, Dec, B,R,I mags, shape)N
Training sets Optical counterparts with measured velocities
Machine learning Support Vector Machine
Use all parameters for the classification: new physics?
Quadratic programming problem, so unique solutions
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4. Future: direct image analysis
Handwritten postcode recognition US Postal Service database: each digit 16×16 pixels
7,300 training patterns, 2,000 test patterns Classifier % Error
Decision tree 16.2 5-layer neural net 5.1 Support vector machine 4.1 Human 2.5
Direct analysis of optical pixel data? Established for morphological galaxy classification Too many pixels for radio identification problems?
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5. Example element of e-Astronomy Australia
Build a pipeline processor (running aips++) to process radio synthesis data from ATCA archive on the fly User can choose parameters of image
Field centre Field size Optimise algorithm for science question being
asked Can use latest version of calibration
algorithm Expert users can tweak parameters
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Goals of e-Astronomy Australia
Survey and archive data from Australian telescopes available to all IVO users Prospects to put full ATCA archive online
Set up datagrid and compute grid to give Australian astronomers access to IVO resources
Help develop techniques, protocols, etc for the IVO
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6. Tools – new and used
FITS – successful data format – keep? Astronomy co-ordinate systems –
several in use – IAU working group VOtable – flexibility, greater
complexity, incorporate current protocols
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7. New multicolour Survey
Imaging survey with Great Melbourne Telescope
A TRAGEDY!
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Discussion: paradigm for a small country
1. Identify strengths or special roles in the international context
2. Identify any major international partners gains from the involvement
3. Identify gains for the small country from involvement in the project
4. Identify a realistic niche for a significant contribution
5. If any of 1- 4 are missing, withdraw!
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Challenges & Opportunities
Continue training of future astronomers Need resources to maintain and upgrade
databases & fund future instruments Cross-discipline collaborations Maintain role in observational science
FIND A NICHE!
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Where to now?
LIEF grant for 1 year – new grants? Raise visibility in Europe, USA programs Cross discipline links – herbarium,
medical centre, particle physics Identify areas of contribution to
international VO – spectroscopy? http://www.aus-vo.org (David Barnes)
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Conclusions
GOAL: To develop tools, data and organisational structures to facilitate international collaborations and individual research on multidimensional archives operating as a VO.