a long traditiona long tradition

e-science, Data Centres, and the Virtual Observatory

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

Beijing workshop on small VO projects Andy Lawrence Nov 2003

what is e-science ? what is e-science ?

• application of extreme IT to science– TFlops, PBytes, Gbps

– distributed computing

– algorithms

• internet enabled science

• collaborative computing

• inter-enterprise computing

Generic science driversGeneric science drivers

• data growth• on-line research• multi-archive science• rare object science• large database science• empowerment

from GridPPweb page

• 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 conceptthe Grid concept

same story everywheresame story everywhere

• astronomy • particle physics• biology • education• commerce• etc etc ...

multi- views of a Supernova Remnant

Shocks seen in the X-ray

Heavy elementsseen in the optical

Dust seen in the IR

Relativistic electrons seen in the radio

What happens to the Earth's magnetosphere during a coronal mass ejection ?

Event imaged by space-based solar observatory

Effect detected later bysatellites and ground radar

needles in a haystackneedles 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

UK infrastructure UK infrastructure

• co-ordinated programme• national and regional centres• shared facilities

• astronomy benefits frombeing on the map

Chinese infrastructure 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

VO structure : key pointsVO structure : key points

• not a monolith

• data centres have the key role

not a monolithnot a monolith

• framework + standards

• inter-operable data

• inter-operable software modules

• content of VO : data + services + tools

• no central VO-command

VO geometryVO geometry

• not a warehouse

• not a hierarchy

• not a peer-to-peer system

• small set of service centresand large population of end users

Data CentresData Centres

• build and curate databases• deploy VO infrastructure• supply data services

– data access

– data operationssearch / transform / combine / analyse

• data analysis standardised and online

yesterdayyesterday

browserfrontend

CGIrequest

html

web page

DBengine

SQL

data

todaytoday

appl

icat

ion

webservice

SOAP/XML request

SOAP/XML data

DBengine

SQL

nativedata

anyt

hin

g

standard formats

tomorrowtomorrow

appl

icat

ion

webservice

job

results

anyt

hin

g

webservice

webservice

webservice

webservice

webservice

Registry Workflow

GLUE Community MySpace

standard semantics

publ

ish W

SDL

day after tomorrowday after tomorrow

appl

icat

ion

gridservice

job

results

anyt

hin

g

gridservice

gridservice

gridservice

gridservice

gridservice

Registry

Workflow GLUE Community MySpace

poo

led

res

ourc

e

standard semantics

ontology agents

what then must we do ?what then must we do ?

work neededwork needed

appl

icat

ion

gridservice

job

results

anyt

hin

g

gridservice

gridservice

gridservice

gridservice

gridservice

Registry

Workflow GLUE AstroPass MySpace

poo

led

res

ourc

e

standard semantics

TOOLS

STANDARDS

INFRASTRUCTURE

TECHNOLOGYRESEARCH

DATA SERVICES(access and analysis)

INF. UPTAKE

DA

TA

PIP

EL

INE

S

ontology

PH

YS

ICA

L G

RID

agents

work for "small" projects ?work for "small" projects ?

• pipelines , databases • physical grid • infrastructure uptake • data services • infrastructure build (niches)

• standards development • technology research • tools

Ju Zhong