e-Science
and the
David De Roure
University of Southampton
Outline
1.
2.
e-Science and e-Research
Enabling Technologies


3.
4.
July 2004
Grid
Semantic Web
Semantic Grid
Building Bridges
IAAI Panel
2
Vision: e-Science
e-Science is about global collaboration in
key areas of science and the next
generation of [computing] infrastructure
that will enable it. e-Science will change
the dynamic of the way science is
undertaken
John Taylor, Director General of UK Research Councils
July 2004
IAAI Panel
3
Vision: e-Science
‘[The Grid] intends to make access to
computing power, scientific data
repositories and experimental facilities as
easy as the Web makes access to
information.’
Tony Blair, 2002
July 2004
IAAI Panel
4
UK funding context
Particle Physics and
Astronomy
Engineering and
Physical Sciences
Natural Environment
Economic and Social
Medical
Biotechnology and
Biological Sciences
CCLRC
(Arts and Humanities)
July 2004
Dept of Trade
and Industry
Companies
University
R&D
European
Commission
Research Councils
Joint Information
Systems Committee
IAAI Panel
5
UK e-Science Funding
First Phase:
2001 –2004
 Application Projects
 £74M
 All areas of science
and engineering
 Core Programme
 £15M Research
infrastructure
 £20M Collaborative
industrial projects
Second Phase:
2003 –2006
 Application Projects
 £96M
 All areas of science
and engineering
 Core Programme
 £16M Research
Infrastructure
 £10M DTI Technology
Fund
Across all areas
Application-led
Core program
July 2004
IAAI Panel
6
e-Science Core Program
Four major functions:

Assist development of essential, wellengineered, generic, Grid middleware

Provide necessary infrastructure
support for UK e-Science Research
Council projects

Collaborate with the international
e-Science and Grid communities

Work with UK industry to develop
industrial-strength Grid middleware
July 2004
IAAI Panel
7
myGrid pilot project





Bioinformatics
Imminent ‘deluge’ of
data
Highly heterogeneous
Highly complex and
inter-related
Convergence of data
and literature archives
July 2004
IAAI Panel
8
Combe Chem pilot project
Video
Simulation
Diffractometer
Properties
Analysis
Structures
Database
X-Ray
e-Lab
Properties
e-Lab
Grid Middleware
July 2004
IAAI Panel
9
UK e-Science Grid
Edinburgh
Glasgow
DL
Belfast
Newcastle
Manchester
Cambridge
Oxford
Cardiff
RAL
London
Hinxton
Southampton
July 2004
IAAI Panel
10
UK e-Science: Phase 2
Three major new activities:
1. National Grid Service and Grid Operation
Centre
2. Open Middleware Infrastructure Institute
for testing, software engineering and UK
repository
3. Digital Curation Centre to look at longterm data preservation issues
July 2004
IAAI Panel
11
Grid Operation Support Centre
 Deploy production ‘National Grid Service’ based
on four dedicated compute and data nodes plus
two UK Supercomputers
 Develop operational policies, security, …
 Gain experience with genuine users
 Develop Web Services based e-Science Grid
 Work with EU EGEE project, the NSF
Cyberinfrastructure Program and A-P Grid
activities
July 2004
IAAI Panel
12
Open Middleware Infrastructure Institute







July 2004
Repository for UK-developed Open Source
‘e-Science/Cyber-infrastructure’ Middleware
Documentation, specification, QA and standards
Fund work to bring ‘research project’ software
up to ‘production strength’
Fund Middleware projects for identified ‘gaps’
Work with US NSF, EU Projects and others
Supported by major IT companies
Southampton selected as the OMII site
IAAI Panel
13
Digital Curation Centre
In next 5 years e-Science projects will produce
more scientific data than has been collected in
the whole of human history
In 20 years can guarantee that the OS and
spreadsheet program and the hardware used to
store data will not exist





July 2004
Research curation technologies and best practice
Need to liaise closely with individual research
communities, data archives and libraries
Edinburgh with Glasgow, CLRC and UKOLN
selected as site of DCC
IAAI Panel
14
Typical Science Grid
Service such as Research
Database or simulation
Campus or
Enterprise
Administrative
Grid
Learning Management
Grid
Science Grids
Bioinformatics
Earth Science …….
Transformed by Grid Filter
to form suitable for education
Publisher
Grid
Education Grid
Digital
Library
Grid
Teacher Educator
Grids
Student/Parent …
Community Grid
Informal
Education
(Museum)
Grid
Education as a Grid of Grids (thanks to Geoffrey Fox)
July 2004
IAAI Panel
15
Vision: e-Research

Not just new Science








e-Social Science
e-Humanities
e-Arts
e-Research
e-Business
e-Anything
…



And new disciplines!
July 2004
IAAI Panel
Researchers working in all
disciplines are faced daily with a
wide variety of tasks necessary
to sustain and progress their
research activity
These involve the analytical
aspects of their work, access to
resources, collaboration with
fellow researchers, and project
management and admin
These tasks rapidly increase in
scale and complexity as
collaborations grow larger,
become more geographically
distributed and involve a wider
range of disciplines
JISC
16
Vision: HASTAC
Humanities, Arts, Science and Technology
Advanced Collaboratory
HASTAC is an international, interdisciplinary
consortium which seeks to create, develop, advance
and utilize a broad range of leading computing and
information systems while contributing to an
understanding of the interconnections between the
human sciences, natural sciences, arts, and
technology in a complex global society
July 2004
IAAI Panel
17
Vision: Joining up

These visions are all about joining resources
and people together in new ways in order
to create new things





Researchers can focus on the real research
The research process is accelerated
New research results are possible
New research areas are possible
NB s/research/business/
July 2004
IAAI Panel
19
Vision: The Grid
July 2004
IAAI Panel
Courtesy of Ian Foster
20
Vision: The Grid
Grid computing has emerged as an important new
field, distinguished from conventional distributed
computing by its focus on large-scale resource
sharing, innovative applications, and, in some cases,
high-performance orientation...we [define] the "Grid
problem”…as flexible, secure, coordinated resource
sharing among dynamic collections of individuals,
institutions, and resources - what we refer to as
virtual organizations
From "The Anatomy of the Grid: Enabling Scalable Virtual
Organizations" by Foster, Kesselman and Tuecke
July 2004
IAAI Panel
21
Challenges: Unanticipated Re-use

myGrid
Wish to reuse
 Data
 Services
 Software
 Knowledge
Combechem
July 2004
IAAI Panel
22
Outline
1.
2.
The e-Vision and its challenges
Enabling Technologies


3.
4.
July 2004
Grid
Semantic Web
Semantic Grid
Building Bridges
IAAI Panel
26
Two infrastructure enablers
Grid
Computing



Semantic
Web
On demand transparently
constructed multiorganisational federations
of distributed services
Distributed computing
middleware
Computational Integration
July 2004



IAAI Panel
An automatically
processable, machine
understandable web
Distributed knowledge and
information management
Information integration
27
July 2004
IAAI Panel
28
Five Myths busted!
1.
2.
Isn’t it just for Physics?

No – Grids for Life Science and Medicine will
dominate Grid applications

Think of the range and scale of data and the
community!
Isn’t it just High Performance computing?

No – it’s a generic mechanism for forming,
managing and disbanding dynamic federations of
services

Data integration, data access, data transport will
dominate

Application integration is the key
July 2004
IAAI Panel
29
Five Myths busted!
3.
4.
5.
Isn’t it just a bag of protocols glued together?

No – the Open Grid Service Architecture gives a
well specified middleware stack built on industry
standard web services
Isn’t it just Globus toolkit?

No – that is one reference implementation.
Isn’t it just a bunch of academic physicists?

No –all the commercial vendors are making serious
investment. IBM DB2 and Oracle 10g will be gridcompliant
July 2004
IAAI Panel
30
Grid Services
Specific services: drug discovery
pipeline, sky surveys
Grid Applications
Open Grid Service Architecture
Web Service Resource Framework
Web Service-Notification
Web Services
July 2004
Standard services: agreement,
data access and integration,
workflow, security, policy,
brokering…
Standard interfaces and
behaviours for distributed systems:
naming, service state, lifetime
management, notification
Standard mechanisms for
describing and invoking services:
WSDL, SOAP, WS-Security etc
IAAI Panel
31
July 2004
IAAI Panel
32
Origins of the Semantic Web
The Semantic Web is an extension of
the current Web in which information
is given a well-defined meaning, better
enabling computers and people to
work in cooperation.
It is the idea of having data on the
Web defined and linked in a way that it
can be used for more effective
discovery, automation, integration and
reuse across various applications.
The Web can reach its full potential if
it becomes a place where data can be
processed by automated tools as well
as people.
W3C Activity Statement
July 2004
IAAI Panel
33
Layers of Languages
Attribution
Explanation
We are here!
Rules & Inference
Ontologies
Metadata annotations
Standard Syntax
Identity
July 2004
IAAI Panel
34
Resource Description Framework





Common model for
metadata
A graph of triples
Query over and link
together
RDQL, repositories,
integration tools,
presentation tools
The Network Effect
July 2004
IAAI Panel
Graphic courtesy of Tim Berners-Lee
35
OWL Web Ontology Language
DARPA
Agent Markup DAML
Language
EU/NSF Joint Ad hoc
Committee
The most popular ontology
language in the world ever!
A W3C
Recommendation
July 2004
OIL
Ontology
Inference
Layer
RDF
DAML+OIL
OWL
IAAI Panel
All
influenced
by RDF
OWL Lite (thesaurus)
OWL DL (reason-able)
OWL Full (anything goes)
36
5 More Myths Busted!
Isn’t it just AI and distributed agents (again)?
1.
No – It is primarily metadata integration and querying

Don’t you need all that reasoning stuff?
2.
No – A little bit of semantics goes a long way! (Hendler)

It only applies to the Web?
3.
No – the technologies are being used for Enterprise
integration, exposing data in a common model, common
ontology languages, representing terminologies.

One big ontology of everything never works!
4.
No – multiple ontologies; multiple everything!

One big Semantic Web!
5.

July 2004
No – lots of Semantic Web-lets, and expect it to break!
IAAI Panel
37
Outline
1.
2.
The e-Vision and its challenges
Enabling Technologies


3.
4.
July 2004
Grid
Semantic Web
Semantic Grid
Building Bridges
IAAI Panel
38
The Semantic Grid Report 2001


At this time, there are a number of grid
applications being developed and there is a whole
raft of computer technologies that provide
fragments of the necessary functionality.
However there is currently a major gap between
these endeavours and the vision of e-Science in
which there is a high degree of easy-to-use and
seamless automation and in which there are
flexible collaborations and computations on a
global scale.
www.semanticgrid.org
July 2004
IAAI Panel
39
Scale of
Interoperability
Semantic Grid
Semantic
Web
Semantic
Grid
Classical
Web
Classical
Grid
Scale of data and computation
July 2004
IAAI Panel
Based on an idea by Norman Paton
40
Semantics in and on the Grid
The Semantic Grid is
an extension of the
current Grid in which
information and
services are given
well-defined meaning,
better enabling
computers and people
to work in cooperation
July 2004
IAAI Panel
41
Underpinnings of e-Science
Grid
Computing
The
Semantic
Grid
The
Semantic
Web
Web Services
Contrast with…
July 2004
IAAI Panel
42
Knowledge Grid
July 2004
IAAI Panel
43
Grid Computing trajectory
There are SG
technologies
available today
for immediate
deployment
cost
Virtual organisations
with dynamic access to
unlimited resources
For all
Sharing of apps and know-how
With controlled set of
unknown clients
Sharing standard scientific
process and data, sharing
of common infrastructure
Between trusted partners
CPU intensive workload
Grid as a utility, data Grids,
robust infrastructure
Intra-company, intra community
e.g. Life Science Grid
CPU scavenging
time
July 2004
IAAI Panel
45
Semantics in e-Science





Ontology-aided
workflow
construction
RDF-based service
and data registries
RDF-based metadata
for experimental
components
RDF-based
provenance graphs
OWL based controlled
vocabularies for
database content
OWL based
integration
July 2004
IAAI Panel
RDF-based semantic
mark up of results,
logs, notes, data
entries
46
Engineering Design
Engineer
GEODISE
PORTAL
Knowledge
repository
Ontology for
Engineering,
Computation, &
Optimisation and
Design Search
Reliability
Security
QoS
Visualization
Session
database
Traceability
OPTIMISATION
Globus, Condor, SRB
OPTIONS
System
Optimisation
archive
APPLICATION
SERVICE
PROVIDER
Intelligent
Application
Manager
July 2004
CAD System
CADDS
IDEAS
ProE
CATIA, ICAD
COMPUTATION
Licenses
and code
Analysis
CFD
FEM
CEM
Design
archive
Parallel machines
Clusters
Internet Resource Providers
Pay-per-use
IAAI Panel
Intelligent
Resource
Provider
47
Ontologies for e-Science



User-oriented, scalable
environment for domain
experts to acquire,
develop and use
ontologies
Based on OilEd and
Protégé 2000
Transatlantic cooperation
on the development of
ontologies for e-Science
Universities Manchester and Southampton, UK
Stanford University, USA
July 2004
IAAI Panel
48
Collaboration tools
BuddySpace
Access Grid
Node
NetMeeting
awareness of
colleagues’ ‘presence’
virtual meetings
recovering information
from meetings
Replay
mapping real time
discussions/group
sensemaking
Compendium
enacting decisions/
coordinating activities
synthesising artifacts
I-X Tools
July 2004
IAAI Panel
49
NASA Scenario
1. Astronauts debrief on EVA
Compendium maps from trained
compendium astronaut
Mars
Video and
Science Data
Remote Science Team (RST) on
earth e.g. geologists
Plan for next
Day’s EVA
2. Virtual meeting of RST
using CoAKTinG tools
July 2004
IAAI Panel
50
Finding collaborators
Using scaleable triple store and AKT ontology
July 2004
IAAI Panel
51
GGF9 Semantic Grid Workshop








The Role of Concepts in myGrid Carole Goble
Planning and Metadata on the Computational Grid Jim
Blythe
Semantic support for Grid-Enabled Design Search in
Engineering Simon Cox
Knowledge Discovery and Ontology-based services on the
Grid Mario Cannataro
Attaching semantic annotations to service descriptions Luc
Moreau
Semantic Matching of Grid Resource Description
Frameworks John Brooke
Interoperability challenges in Grid for Industrial
Applications Mike Surridge
Semantic Grid and Pervasive Computing David De Roure
July 2004
IAAI Panel
52
GGF11 Semantic Grid Workshop



Engineering semantics: Costs and
Benefits Simon Cox
Designing Ontologies and
Distributed Resource Discovery
Services for an Earthquake
Simulation Grid Marlon Pierce
Exploring Williams-Beuren
Syndrome Using myGrid Carole

Schroeter


Goble



Distributed Data Management and
Integration Framework: The
Mobius Project Shannon Hastings
eBank UK - Linking Research Data,
Scholarly Communication and
Learning David De Roure
Using the Semantic Grid to Build
Bridges between Museums and
Indigenous Communities Ronald

Collaborative Tools in the Semantic
Grid David De Roure
The Integration of Peer-to-peer
and the Grid to Support Scientific
Collaboration
OWL-Based Resource Discovery for
Inter-Cluster Resource Borrowing
Hideki YOSHIDA

Semantic Annotation of
Computational Components Peter
Vanderbilt

Schroeter
July 2004
Using the Semantic Grid to Build
Bridges between Museums and
Indigenous Communities Ronald
IAAI Panel
Interoperability and
Transformability through Semantic
Annotation of a Job Description
Language Jeffrey Hau
53
E-Science Special Issue

IEEE Intelligent Issue Special Issue on
E-Science, Jan-Feb 2004


De Roure, Gil, Hendler
Challenges:




July 2004
Realizing the network effect
Moving beyond centralized stores
Automated assembly
Collaboration tools
IAAI Panel
54
Self-Organizing Semantic Grid
…Our self-organizing Semantic Grid is now
a constantly evolving organism, with
ongoing, autonomous processing rather
than on-demand processing. This evolving,
organic Grid can generate new processes
and new knowledge.
David De Roure, Trends and Controversies
IEEE Intelligent Systems, August 2003
July 2004
IAAI Panel
55
Outline
1.
2.
The e-Vision and its challenges
Enabling Technologies


3.
4.
July 2004
Grid
Semantic Web
Semantic Grid
Building Bridges
IAAI Panel
56
Building bridges
July 2004
IAAI Panel
57
Semantic
Pervasive
July 2004
IAAI Panel
Grid
58
Closing Remarks




The Semantic Grid is needed to realise the
Grid ambition and the e-Anything vision
Both Grid and Semantic Web are about
joining things up – building bridges
To create this infrastructure we also need to
build bridges – it needs the engagement of
multiple research communities
What can the Semantic Grid do for you, and
what can you do for the Semantic Grid?
July 2004
IAAI Panel
61
Contact



David De Roure
University of Southampton, UK
dder@ecs.soton.ac.uk
Carole Goble
University of Manchester, UK
carole@cs.man.ac.uk
See www.semanticgrid.org
July 2004
IAAI Panel
62
Acknowledgements
myGrid
July 2004
Combechem
IAAI Panel
63