“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 20 Nov, 2002 Virtual Molonglo Observatory 1
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 20 Nov, 2002 Virtual Molonglo Observatory 2
What’s it all about? Grid computing deals with coordinated resource sharing and problem solving in dynamic, multiinstitutional virtual organisations. The resources are compute power, software, data and collaboration tools. 20 Nov, 2002 Virtual Molonglo Observatory 3
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 20 Nov, 2002 Virtual Molonglo Observatory 4
Challenges & responses § § Slow CPU growth distributed computing Limited BW information hierarchies Limited storage distributed data Data diversity interoperability § SOLUTION: GRID COMPUTING 20 Nov, 2002 Virtual Molonglo Observatory 5
Technical Update § § Big commitment in Europe & USA Wide applications – business & science VO-compliance & VO-table Issues of access, security, universal querator, resource broker 20 Nov, 2002 Virtual Molonglo Observatory 6
Role of Australian Astronomy § Workshop focus on data and tools § Examples of current possibilities § Challenges and opportunities 20 Nov, 2002 Virtual Molonglo Observatory 7
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 20 Nov, 2002 AVO Project Management Virtual Molonglo Observatory Gavin Thoms 8 27 November 2002
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 20 Nov, 2002 Virtual Molonglo Observatory 9
20 Nov, 2002 Virtual Molonglo Observatory 10
The Way forward: ARC grant for 2003 (1. 5 FTE@AAO) § Incorporate 2 d. F survey into VO-table (milestone: demo at IAU GA) § Integrate 2 d. F spectra & catalogue server (milestone: end 2003) § VO-compliance for 6 d. F from start (milestone: April 2003) § Route map for AAO VO-compliance (milestone: end 2003) 20 Nov, 2002 Virtual Molonglo Observatory 11
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 20 Nov, 2002 Virtual Molonglo Observatory 12
Response Classification with a Decision Tree Blue ellipses - Sources Red ellipses - Artefacts 20 Nov, 2002 Virtual Molonglo Observatory 13
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 20 Nov, 2002 Virtual Molonglo Observatory 14
3. Machine Learning techniques § Goal – multiwavelength correlations § Problem – database mismatches § Traditional methods – closest position & other information 20 Nov, 2002 Virtual Molonglo Observatory 15
RADIO: HIPASS 21 cm survey OPTICAL: Super. COSMOS (B) (A) Y X 10 arc min error diameter The correlation problem: which is the radio source? 20 Nov, 2002 Virtual Molonglo Observatory 16
Use Machine Learning § Data vectors from catalogues § Radio: RA, Dec, 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 20 Nov, 2002 Virtual Molonglo Observatory 17
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? 20 Nov, 2002 Virtual Molonglo Observatory 18
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 20 Nov, 2002 Virtual Molonglo Observatory 19
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 20 Nov, 2002 Virtual Molonglo Observatory 20
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 20 Nov, 2002 Virtual Molonglo Observatory 21
7. New multicolour Survey § Imaging survey with Great Melbourne Telescope § A TRAGEDY! 20 Nov, 2002 Virtual Molonglo Observatory 22
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! 20 Nov, 2002 Virtual Molonglo Observatory 23
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! 20 Nov, 2002 Virtual Molonglo Observatory 24
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) 20 Nov, 2002 Virtual Molonglo Observatory 25
Conclusions GOAL: To develop tools, data and organisational structures to facilitate international collaborations and individual research on multidimensional archives operating as a VO. 20 Nov, 2002 Virtual Molonglo Observatory 26
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