1. a long tradition

2. e-science, Data Centres, and the Virtual Observatory why is e-science important ? what is the structure of the VO ? what then must we do ? Beijing workshop on small VO projects Andy Lawrence Nov 2003

4. what is e-science ? application of extreme IT to science –TFlops, PBytes, Gbps –distributed computing –algorithms internet enabled science collaborative computing inter-enterprise computing

5. Generic science drivers data growth on-line research multi-archive science rare object science large database science empowerment

6. from GridPP web page

7. shared managed distributed resources –documents + data + software + storage + cycles + expertise network : ability to pass messages web : transparent document system computational grid : transparent CPU datagrid: transparent data access and services information grid, knowledge grid... ? Virtual Organisations ? the Grid concept

8. same story everywhere astronomy particle physics biology education commerce etc etc...

9. multi- views of a Supernova Remnant Shocks seen in the X- ray Heavy elements seen in the optical Dust seen in the IR Relativistic electrons seen in the radio

10. What happens to the Earth's magnetosphere during a coronal mass ejection ? Event imaged by space-based solar observatory Effect detected later by satellites and ground radar

11. needles in a haystack Hambly et al 2001 - faint moving object is a cool white dwarf - may be solution to the dark matter problem - but hard to find : one in a million - even harder across multiple archives

14. UK infrastructure co-ordinated programme national and regional centres shared facilities astronomy benefits from being on the map

16. Chinese infrastructure China Grid announced October featured areas in Grid Today article : –e-learning –video courses –bio-informatics CVO has GT3 focus –involvement in China Grid

18. VO structure : key points not a monolith data centres have the key role

19. not a monolith framework + standards inter-operable data inter-operable software modules content of VO : data + services + tools no central VO-command

20. VO geometry not a warehouse not a hierarchy not a peer-to-peer system small set of service centres and large population of end users

21. Data Centres build and curate databases deploy VO infrastructure supply data services –data access –data operations search / transform / combine / analyse data analysis standardised and online

22. yesterday browser front end CGI request html web page DB engine SQL data

23. today application web service SOAP/XML request SOAP/XML data DB engine SQL native data anything standard formats

24. tomorrow application web service job results anything web service web service web service web service web service Registry Workflow GLUE Community MySpace standard semantics publish WSDL

25. day after tomorrow application grid service job results anything grid service grid service grid service grid service grid service Registry Workflow GLUE Community MySpace pooled resource standard semantics ontology agents

27. what then must we do ?

28. work needed application grid service job results anything grid service grid service grid service grid service grid service Registry Workflow GLUE AstroPass MySpace pooled resource standard semantics TOOLS STANDARDS INFRASTRUCTURE TECHNOLOGY RESEARCH DATA SERVICES (access and analysis) INF. UPTAKE DATA PIPELINES ontology PHYSICAL GRID agents

29. work for "small" projects ? pipelines, databases    physical grid  infrastructure uptake    data services    infrastructure build  (niches) standards development  technology research   tools  

31. Ju Zhong