EPSRC
e-Science
Pilot Projects
Comb-e-Chem
Structure-Property
Mapping:
Combinatorial Chemistry and the Grid
The synthesis of new compounds by combinatorial methods provides major
opportunities for the generation of large volumes of new chemical knowledge.
An extensive range of primary data needs to be accumulated, integrated and
Dr Jeremy Frey
relationships modelled, so that maximum knowledge can be derived.
The goal of the Comb-e-Chem project is to develop an e-science testbed that
integrates existing structure and property data sources within a grid-based
Prof. Dave de Roure
Dr. Jonathan Essex
information-and knowledge-sharing environment. The service-based grid
computing infrastructure extends to devices in the laboratory and involves enriched
streams, (including multimedia and live metadata), full support for provenance and
innovative techniques for automation throughout the environment.
Prof. Mike Hursthouse
Dr. Mike Luck
Comb-e-Chem Objectives:
• to support new data collection, including process as well as product data, based
on integration with electronic lab and e-logbook facilities
Dr. Luc Moreau
Prof. Alan Welsh
Prof. Sue Lewis
• to integrate data generation on demand via grid-based quantum and simulation
modelling to augment the experimental data
Dr. Mike Surridge
Dr. Ian Meacham
• to develop interfaces that provide a unified view of these resources, with
transparent access to data retrieval, online modelling, and design of experiments
Prof. Guy Orpen
to populate new regions of scientific interest
• to provide shared, secure access to these resources in a collaborative e-science
environment.
www.e-science.soton.ac.uk/projects.html
A collaboration between:
University of Southampton
University of Bristol
Roche Discovery Welwyn
Pfizer
IBM UK Ltd
Cambridge Crystallographic Data Centre
Southampton Combinatorial Centre
of Excellence
EPSRC
e-Science
Pilot Projects
DAME:
Distributed Aircraft
Maintenance Environment
The aim of this project is to demonstrate the use of the high-performance
computing grid to support diagnosis using geographically distributed information
and analysis.
The practical, real world demonstration will help Rolls-Royce with aero engine
maintenance decisions, and other sectors such as medical and manufacturing to
improve their diagnostic processes.
Prof. Jim Austin
The Universities of York, Sheffield, Leeds and Oxford have joined forces with RollsRoyce, its information system partner Data Systems & Solutions and Cybula Limited
to meet this challenge.
Prof. John McDermid
Prof. Andy Wellings
The project will deliver:
• a proof of concept demonstrator for the Grid
• a generic distributed diagnostics test-bed
Prof. Lionel Tarassenko
Prof. Peter Fleming
• an aero gas turbine application demonstrator for the maintenance
of aircraft engines
• techniques for distributed data mining and diagnostics
Prof. Peter Dew
Dr. Alison Mckay
• an evaluation of the existing US grid networks Globus and SRB for this task
DAME will build on the grid infrastructure, known as the White Rose
Computational Grid, currently under construction by Leeds, Sheffield and York
universities at a cost of £2.8 million.
Dr. Haydn Thompson
Dr. Karim Djemame
The essential themes of this project are real-time intelligent feature extraction,
high-performance pattern-matching, intelligent data mining and decision support
techniques, where expertise and software tools are distributed across the grid. The
enormity of the databases and the need for distributed access to the data make
this a particularly challenging problem for the grid.
www.cs.york.ac.uk/dame
A collaboration between:
Rolls-Royce plc.
Data Systems & Solutions
Cybula Limited
EPSRC
e-Science
Pilot Projects
GEODISE:
Grid Enabled Optimisation and DesIgn
Search for Engineering
GEODISE will provide grid-based seamless access to an intelligent knowledge
repository, a state-of-the-art collection of optimisation and search tools, industrial
strength analysis codes, and distributed computing and data resources.
Engineering design search and optimisation is the process whereby engineering
modelling and analysis are exploited to yield improved designs. In the next 2-5
Prof. Simon Cox
years intelligent search tools will become a vital component of all engineering
design systems and will steer the user through the process of setting up, executing
and post-processing design search and optimisation activities. Such systems
typically require large-scale distributed simulations to be coupled with tools to
describe and modify designs using information from a knowledge base. These tools
Prof. Andy Keane
are usually physically distributed and under the control of multiple elements in the
supply chain.
Whilst evaluation of a single design may require the analysis of gigabytes of data,
to improve the process of design can require assimilation of terabytes of distributed
Prof. Carole Goble
data. Achieving the latter goal will lead to the development of intelligent search
tools.
GEODISE will focus on the use of computational fluid dynamics (CFD). This
application is relevant to its existing industrial partners:
Prof. Nigel Shadbolt
BAE Systems/ Rolls-Royce and Fluent and will leverage expertise from e.g.
Prof. Mike Giles
Advanced Knowledge Technologies IRC (Soton) and BAE/RR UTP for Design (Soton)
and RR UTC for CFD (Oxford)
www.geodise.org/
A collaboration between:
University of Southampton
University of Oxford
University of Manchester
Rolls-Royce plc
BAE Systems plc
Fluent Europe Ltd
Intel Corp (UK)
Microsoft Ltd
Epistemics Ltd
Compusys plc
Condor
EPSRC
e-Science
Pilot Projects
myGrid:
An e-Biologist’s Workbench
Lead by the University of Manchester, myGrid is a consortium of five universities
the EMBL_EBI at Hinxton and eight commercial partners. The team is divided into
end-users and technology/service providers.
myGrid aims to deliver a personalised collaborative problem-solving platform for an
e-Scientist working in a distributed environment, such that they can construct
long-lived in silico experiments, find and adapt others and publish their own view
on public repositories, and be better informed as to the provenance the currency of
Prof. Carole Goble
the tools and data directly relevant to them. The focus is on data-intensive
post-gernomic functional analysis.
myGrid will develop an extensible open platform for data and tools interoperability
built using a mix of four technologies: the Grid, Web Services, the Semantic Web
Dr. Paul Watson
and an agent software engineering paradigm. Key functional features include:
data integration, process workflow, personalisation, provenance, change
notification and view management, collaborative sharing or process flows
and resources.
Prof. Tom Rodden
Dr. Luc Moreau
Non-functional requirements include security and fault tolerance.
The ultimate goal is to improve both the quality of information in repositories and
the way repositories are used. The appropriateness of the infrastructure will be
shown in two ways:
Dr. Rob Gazaiskaus
• for the e-Scientists: by a workbench and two applications
- Model organism gene expression analysis
- GPCR fingerprints database annotation
• for developers: by the dissemination of a “myGrid-in-a-box” developers kit
Dr. Alan Robinson
- the specification of services
- service descriptors
- APIs and message protocols
- Implemented pilot services and the assimilation of example existing Life
A collaboration between:
University of Manchester
University of Newcastle
University of Nottingham
University of Southampton
Science integration platforms.
The project approach is incremental and evolutionary, based on a series of
prototypes and using open standards and open source. An exploratory
“pre-prototype” to validate use case acquition and identify core services has just
University of Sheffield
been completed. The final results will be disseminated on a rolling programme
European Bioinformatics Institute
starting in June 2003. All software will be available as Open Source.
AstraZeneca
GlaxoSmithKline
MERCK KgaA
Sun Microsystems
Network Inference
Epistemics Ltd
GeneticXchange
IBM UK Limited
www.mygrid.org.uk/
EPSRC
e-Science
Pilot Projects
The RealityGrid
A Tool for Investigating Condensed
Matter and Materials
RealityGrid will construct a Grid test-bed to enable the realistic modelling and
simulation of complex condensed matter systems at the meso and nanoscale levels,
as well as the discovery of new materials. High performance computing and
visualisation are critical to this test-bed: they provide a synthetic environment for
modelling to be compared and integrated with the reality provided by
experimental data.
Prof. Peter Coveney
RealityGrid will provide Grid hardware and middleware that will allow these to be
coupled in an environment optimised for scientific discovery.
The project involves active collaboration with industry:
Dr. John Brooke
Prof. John Darlington
Advanced Visual Systems, Silicon Graphics Inc and Fujitsu on the underpinning
computational issues, Schlumberger and the Edward Jenner Institute for Vaccine
Research on end-user scientific applications in the conjunction of modelling,
simulation, informatics and experimental research.
Prof. Roy Kalawasky
Prof. Adrian Sutton
www.realitygrid.org
Prof. John Gurd
Prof. Michael Cates
A collaboration between:
Queen Mary, University of London
University of Manchester
University of Edinburgh
Imperial College of Science, Technology and Medicine
Loughborough University
University of Oxford
Schlumberger Cambridge Research Ltd.
The Edward Jenner Institute for Vaccine Research
Silicon Graphics Inc
Advanced Visual Systems Ltd.
Fujitsu Ltd
Computation for Science
EPSRC
e-Science
Pilot Projects
Discovery Net:
An e-Science Testbed for High
Throughput Informatics
The DNet project aims to design, develop and implement an advanced
infrastructure to support real-time processing, interpretation, integration,
visualisation and mining of massive amounts of time critical data generated by high
throughput devices. The project will maximize the benefit of testing EPSRC-funded
infrastructure and will cover new technology devices and technology including
biochips in biology, high throughput screening technology in biochemistry and
Dr. Yike Guo
combinatorial chemistry, high throughput sensors in energy and environmental
science, remote sensing and geology. Application studies include analysis of Protein
Folding Chips and SNP Chips using LFII technology, protein-based fluorescent
micro array data, air sensing data, renewable energy data, and geohazard
prediction data.
Prof. John Darlington
The development program of DNet will focus on the design and implementation of
four important components: grid infrastructure, data engineering, information
structuring and knowledge discovery. Each component provides mechanisms to
deal with the issues of high throughput informatics. Apart from delivering a
Dr. Daniel Ruekert
Dr Tony Cass
practical distributed discovery platform, DNet will focus on the establishment of a
Dr. John Hassard
set of standards for representing and communicating high throughput information
Prof. Bob Spence
for integrated research. Such standards will be promoted by establishing
Dr. Jian Liu
international collaborations in DNet research and integrating DNet with data grid
Dr. Moustafa Ghanem
activities and related distributed data analysis research in the USA.
A collaboration between:
Imperial College of Science, Technology and Medicine
Inforsense Ltd
DeltaDOT Ltd
RVCo Inc