Transcript e-Science Institute & National e-Science Centre

Progress with UK
e-Science
Cardiff University
School of Computer Science
Welsh e-Science Centre
Malcolm Atkinson
Director e-Science Institute
UK e-Science Envoy
www.nesc.ac.uk
23rd May 2007
Overview
History of e-Science in UK > 6 years
Three Significant Strengths Established
Science projects
(70% of funding,
Demanding drivers)
Communities & Breadth
e-Infrastructure
(hardware,
software
& training)
Achieving the CI Vision requires
synergy between 3 types of
Foundation wide activities
Transformative
Application - to
enhance discovery &
learning
Provisioning Creation, deployment
and operation of
advanced CI
R&D to enhance technical and
social dimensions of future CI
systems
Office of
Cyberinfrastructure
D. E.
Atkins
Defining e-Science
e-Science: Systematic Support for
Collaborative Research using advanced ICT
Multi-disciplinary, Multi-Site & Multi-National
All disciplines contribute & benefit
Enabling wider engagement
Building on and demanding advances in
Computing Science
Using advances in computing to support
research, design, diagnosis
Dates back 50 years
Prevalent in branches of biology >30 years
Prevalent in Engineering for >40 years
New emphasis on systematic support for
collaboration, sharing & interdisciplinarity
UK e-Science
e-Science and the Grid
‘e-Science is about global collaboration in key
areas of science, and the next generation of
infrastructure that will enable it.’
‘e-Science will change the dynamic of the
way science is undertaken.’
John Taylor
Director General of Research Councils
Office of Science and Technology
GGF5 Edinburgh
From presentation by Tony Hey
UK e-Science Diversity
Thriving Community
All disciplines & all
Research Councils
Industry & Academia
Many universities &
research institutes
UK e-Science All
Hands Meetings
Productive
collaboration
e-Infrastructure
A shared resource
That enables science,
research, engineering,
medicine, industry, …
It will improve UK /
European / …
productivity


Lisbon Accord 2000
E-Science Vision SR2000 –
John Taylor
Commitment by UK
government

Sections 2.23-2.25
Always there

c.f. telephones, transport,
power
OSI report

www.nesc.ac.uk/documents/
OSI/index.html
Slide from Carole Goble
Kyra Norman and Orchestra Cube; Photo: Rob Bristow, June 2006
Slide: Angela Piccini
http://www.allhands.org.uk/index.html
Workshops
Summer Schools
Themes
Information Services for
Smart Decision making
Exploiting Diverse Data
Sources
Usability - Barriers to
Uptake
Geospatial semantics
Distributed programming
abstractions
Arts & Humanities
requirements
Edinburgh
Activity
Theme 3: Adoption of
e-Research Technologies
Theme 4: Spatial Semantics
for Automating Geographic
Information Processes
Theme 5: Distributed
Programming Abstractions
Theme 6: e-Science in the
Arts and Humanities
Slide from Dr Anna Kenway
National Grid Service and partners
Glasgow
Edinburgh
York
Lancaster
Leeds
Manchester
Sheffield
STFC Daresbury
Oxford
Cardiff
STFC Harwell
London
Bristol
Slide: Neil Geddes
Coordinated by:
Directors’ Forum
& NeSC
e-Science Centres in the UK
Access Grid
Support Centre
National Centre for
Text Mining
Glasgow
Digital Curation Centre
Lancaster
Edinburgh
Newcastle
Belfast
White Rose
Grid
National Institute
for Environmental
e-Science
Manchester
National Centre
for e-Social
Science
York
Leicester
Leeds
Sheffield
STFC Daresbury
Cambridge
National Grid
Service
Birmingham
STFC Harwell
Oxford
UCL
Cardiff
Bristol
Open Middleware
Infrastructure Institute
Southampton
Reading
LeSC
OMII-UK nodes
EPCC & National e-Science Centre
School of Computer Science
University of Manchester
Edinburgh
School of Electronics and
Computer Science
University of Southampton
Manchester
Southampton
OMII-UK Software
Open Source
Special Product Lines
User Community
Community
deposits
Software
catalogue
Software
repository
SE QA
pipeline
Workflow
Portal
Service
registry
Foreign
Distributions
Data
Community
software
stacks
Commissioned
programme
OMII-BPEL
Software spotted on safari
or by Product or Area Liaisons
(PALs)
Infrastructure and Standards Community
The NERC Success
Professor Robert Gurney
Director, Environmental Systems Science
Centre, Reading
The NERC e-Science experience
11 papers in Nature
Enthusiastic uptake of ensemble methods
climateprediction.net Users Worldwide
>300,000 users total (90% MS Windows): >60,000 active
~17 million model-years simulated (as of September '06)
~180,000 completed simulations
Impact:
New Science
Understanding of science
Engaging schools
BBC follow on
The world's largest climate modelling supercomputer!
(NB: a black dot is one or more computers running climateprediction.net)
Slide: Robert Gurney
David De Roure
Slide: Dave De Roure & Jeremy Frey
Foundations for Collaborative Behaviour
Grunts and
body language
500,000 years
Printing
600 years
Speech
300,000 years
Broadcasting
100 years
Telecommunications
170 years
Home Computers
Internet and WWW
Mobile phones
Grid and Web 2.0
Writing Web 3.0 and Ubiquitous connected devices
30 years
5,000 years
Today
“Wellbeing” the global-scale killer
app., Sir Robin Saxby Oct. 2006
Timeline
Healthcare @ Home
REFERRAL
GP
Home-mobile-clinic
via PDA-laptop-PC-Paper
REFERRAL
Diabetician
Home-mobile-clinic
via PDA-laptop-PC-Paper
Various Clinical Specialists (Distributed)
e.g. Ophthalmologist, Podiatrist, Vascular
Surgeons, Renal Specialists, Wound clinic,
Foot care clinic, Neurologists, Cardiologists
REFERRAL
VARIABLES
ACCESS
MATRIX
CASE
Patient
Home-mobile-clinic
via TV-PDA-laptop-PC-Paper
Dietitian
Slide from Alex Hardisty
Biochemist
Diabetes Specialist / Other Specialist Nurses
Home-mobile-clinic
via TV-PDA-laptop-PC-Paper
Community Nurses / Health Visitors
“Wellbeing” the global-scale killer
app., Sir Robin Saxby Oct. 2006
DAME/BROADEN
http://www.cs.york.ac.uk/dame/
•
•
•
•
•
•
•
•
•
•
•
Aims to manage >1Tb per year of
Aero Engine vibration and
maintenance data.
Interlinks with search and reasoning
services.
Defined and evaluated a distributed
search system.
GSI enabled secure engine
performance simulation
CBR advisor for diagnostic engineer
A data architecture defined based
on Globus and SRB.
BROADEN DTI Project (£3.9M)
Spun out technology exploited
through Cybula Ltd., Oxford
Biosignals and DS&S.
Successful mid-term demonstrator
well received by Rolls Royce
White Rose Grid: experience of
building & using production Grids
In Grid Blue Print 2 edition 2
Aircraft healthcare diagnosis
• Jim Austin (Comp Sci, York)
• 4 Universities and institutes
• 3 Companies
Slide: Carole Goble, Jim Fleming & Jim Austin
New EPSRC project.
CARMEN
late 2006 - 2009
Understanding the brain
may be the greatest
informatics challenge of
the 21st century
http://bioinf.ncl.ac.uk/carmen/
 determining ion
channel contribution
to the timing of action
potentials
 resolving the ‘neural
code’ from the timing
of action potential
activity
 examining integration
within networks of
differing dimensions
Source: Colin Ingram
MESSAGE – overview
• Heterogeneous fixed and
mobile sensors on
infrastructure, vehicles
and people
• Sensors communicate
via wireless networks
• Positioning via GPS +
wireless & cellular
ranging
• Integration of processing
along the data path
• Multiple application
studies in different local
contexts
Slide from John Polak
MESSAGE – multi-disciplinarity
• MESSAGE involves integrating academic
expertise from several disciplines:
– 1Transport network modellers
– Air quality modellers
– Geomatricians
– Computer Scientists
– Electrical Engineers
– Sensor Developers (Physicists and Chemists)
• Together with industry experience and
tangible real-world applications
Slide from John Polak
MESSAGE – research challenges
• Field units
– Sensors
– Positioning
– Communications
• e-Science
– Scalability
– Distributed data mining
– Online estimation of pollutant hotspots
• Transport and environment modelling
– Traffic management and control
– Traveller information
Slide from John Polak
www.nanocmos.ac.uk
The Challenge
International Tech nology Roadmap for Semiconductors
Year
MPU Half Pitch (nm)
MPU Gate Length (nm)
2005
2010
2015
2020
90
32
45
18
25
10
14
6
2005 edition Toshiba 04
Device diversification
230 nm
90nm: HP, LOP, LSTP
45nm: UTB SOI
Bulk MOSFET
32nm: Double gate
Standard
25 nm
FinFET
UTB SOI
FD SOI
Bulk MOSFET
LSTP
LOP
HP(MPU)
6th September 2006
Single
Set
Stat.
Sets
Slide from Asen Asenov
Mont Blanc
Kings Cross
Piper
Alpha
FireGrid
WTC
Kobe
FireGrid Architecture
A
Primary monitoring
& gateways
between sensor
nets & grid
B C
Building data
Pre-computed
scenarios
D
E
A
B C
D
E
A
Routine & Initial
Workflows
sensor validation
& calibration,
building and
people status &
event detection
B C
5 Peopl
Workflow
selection
& steering
Data-flow
selection
& actuation
D
E
Sensors & Actuators
Temp, CO, smoke,
displacement/strain,
vibration/acoustic,
systems status
Escalated
Workflows
From PCs to
teraflops
Displays from
sensors and
simulations
Logging
C&C
View selected
status displays &
user control panels
Personal & Team
Preference data
WISDOM deployment :
wisdom.eu-egee.fr
•country
•sites
•country
•sites
•Bulgaria
•3
•Greece
•3
•Romania
•1
•Croatia
•1
•Israel
•1
•Russia
•2
•Cyprus
•1
•Italy
•13
•Spain
•7
•France
•9
•Netherlands
•2
•Taiwan
•1
•Germany
•1
•Poland
•1
•UK
•10
Total amount of CPU
provided by EGEE
federation
•country
Countries with nodes
contributing to the data
challenge WISDOM
•sites
CentralEurope, 4%
GermanySwitzerland,
1%
AsiaPacific, 2%
Russia, 1%
UKI, 29%
NorthernEurope, 7%
SouthEasternEurope,
10%
SouthWesternEurope,
12%
France, 18%
Italy, 16%
Discovery Net
China SARS
Virtual Lab
Genbank
Homology search against
viral genome DB
Homology search
against protein DB
Annotation using
Artemis and GenSense
Annotation using
Artemis and
GenSense
Predicted
genes
Gene prediction
Exon prediction
Key word
search
Protein localization
site prediction
Splice site prediction
GeneSense
Ontology
Multiple sequence
alignment
D-Net:
Integration,
interpretation,
and discovery
Relationship
between
SARS and
other virus
Phylogenetic analysis
Immunogenetics
Mutual regions
identification
Microarray analysis
Epidemiological analysis
Homology search
against motif DB
SARS patients
diagnosis
Protein interaction
prediction
Relationship
between SARS virus
and human receptors
prediction
Classification and
secondary structure
prediction
Bibliographic databases
Bibliographic databases
Used now in Institute for Animal Health, UK
Source: Yike Guo and Moustafa Ghanem
Source: Andy Brass
http://www.genomics.liv.ac.uk/tryps/trypsindex.html
Mouse models of
trypanotolerance.
% Survival
Survival of F6 and parental strains
100
90
80
70
60
50
40
30
20
10
0
F6
AJ
C57BL
1
21
41
61
81
101
121
Days Post Challenge
T brucei rhodesiense
T gambiense
T. congolense,
T. vivax
Presentation services: subject, media-specific, data, commercial portals
Data creation /
capture /
gathering:
laboratory
experiments,
Grids,
fieldwork,
surveys, media
Resource
discovery, linking,
embedding
Data analysis,
transformation,
mining, modelling
Searching ,
harvesting,
embedding
Aggregator
services: national,
commercial
Resource
discovery,
linking,
embedding
Learning object
creation, re-use
Harvesting
metadata
Research &
e-Science
workflows
Deposit / selfarchiving
Learning &
Teaching
workflows
Repositories :
institutional,
e-prints, subject,
data, learning objects
Validation
Deposit / selfarchiving
Publication
Resource
discovery, linking,
embedding
The scholarly knowledge cycle.
Liz Lyon, Ariadne, July 2003.
© Liz Lyon (UKOLN, University of Bath), 2003
This work is licensed under a Creative Commons License
Attribution-ShareAlike 2.0
Peer-reviewed publications:
journals, conference
proceedings
Institutional
presentation
services: portals,
Learning
Management
Systems, u/g, p/g
courses, modules
Validation
Quality
assurance
bodies
Data capture
Slide: Dave De Roure & Jeremy Frey
Slide: Dave De Roure & Jeremy Frey
Amazon Web Services
Web 2.0 APIs
http://www.programmableweb.com/apis
currently (Jan 10 2007) 356 Web 2.0 APIs with
GoogleMaps the most used in Mashups
This site acts as a “UDDI” for Web 2.0
Geoffrey Fox
Europe FP7
http://cordis.europa.eu/fp7/
e-Health
The Virtual Human
Challenges for e-Science
Understand what enables
collaboration
Interdisciplinary
Multi-site
Through time
With realism about motives & competition
Find the best ways of supporting it
Is this a one-size fits all opportunity?
It requires an inter-disciplinary approach
Technology push or pull?
Abstract and communicate
Challenges for e-Science 2
Creating wider understanding
In researchers
In funders
In the public
Find the best ways of creating
understanding
Articulate the stories?
Analyse the successes
Educate the emerging generation?
An interdisciplinary challenge
Abstract and communicate
Training & Education Spectrum
• Training
–
–
–
–
Targeted
Immediate goals
Specific skills
Building a workforce
• Education
–
–
–
–
Strengthens
Services & Applications
Changing Culture
Pervasive
Long term and sustained
Generic conceptual models
Developing a culture
Organisation
Develop
Enriches
Skilled Workers
Society
Innovation
Create
Invests
Training
Prepares
Invests
Education
Graduates
Prepares
• Both are needed
ICEAGE & Forum’s Primary Focus
INFSO-SSA-26637
Three Educational
Challenges
The Computing & Computational Courses
Recognition of the importance of scale and
complexity
Systems thinking
Support for composition and orchestration
Numerical and Simulation skills
Data intensive engineering
Distributed systems
Computational engineering
Abstraction skills
Insights into usability
Experience working in multi-disciplinary
applications
Three Educational
Challenges
The Disciplines that may apply eScience
Understanding potential & limits of
models
Exploiting tools that capture methods and
processes
Success stories and exemplars in cognate
disciplines
Experience working in multi-disciplinary
collaborations
Appreciation of costs and responsibilities
Three Educational
Challenges
A new engineering discipline Designing, Building & Operating
continuously available systems
Changing the engines on a 747 while flying
passengers at 39,000 feet!
Planning & designing systems
Planning & designing operational procedures
Understanding risks and their management
Understanding workload dynamics
Predicting resource and system requirements
Developing abstractions that enable this to be
done reliably in every deployed system
Take Home
UK e-Science investment has built
three interdependent strengths:
Communities & collaboration
Projects delivering & demanding
e-Infrastructure: organisation, support & technology
Three success factors for projects
Engagement & value for all participants
Creativity & insight addressing a well-posed challenge
Technology adoption and innovation
Progress in research domains is the driver
Integrate whatever technology you need
Invent new technology only if you have to