David De Roure

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e-Science and the

• David De Roure
• University of Southampton

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Outline

• e-Science and e-Research
• Enabling Technologies
• Grid
• Semantic Web
• Semantic Grid
• Building Bridges

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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
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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

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UK funding context

• Research Councils
• Particle Physics and Astronomy
• Engineering and Physical Sciences
• Natural Environment
• Economic and Social
• Medical
• Biotechnology and Biological Sciences
• CCLRC
• (Arts and Humanities)

Dept of Tradeand Industry
Companies
University R D
EuropeanCommission

• Joint Information Systems Committee

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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

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e-Science Core Program

• Four major functions
• Assist development of essential, well-engineered,
  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

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myGrid pilot project

• Bioinformatics
• Imminent deluge of data
• Highly heterogeneous
• Highly complex and inter-related
• Convergence of data and literature archives

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Combe Chem pilot project
Video
Simulation
Properties
Analysis
StructuresDatabase
Diffractometer
X-Raye-Lab
Propertiese-Lab
Grid Middleware
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UK e-Science Grid
Edinburgh
Glasgow
DL
Newcastle
Belfast
Manchester
Cambridge
Oxford
Hinxton
RAL
Cardiff
London
Southampton
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UK e-Science Phase 2

• Three major new activities
• National Grid Service and Grid Operation Centre
• Open Middleware Infrastructure Institute for
  testing, software engineering and UK repository
• Digital Curation Centre to look at long-term data
  preservation issues

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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

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Open Middleware Infrastructure Institute

• 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

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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
• 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

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Typical Science GridService such as
Research Database or simulation
Science Grids Bioinformatics Earth Science .
Transformed by Grid Filterto form suitable for
education
Campus orEnterprise Administrative Grid
Education Grid
Publisher Grid
Learning Management Grid
Student/Parent Community Grid
Digital Library Grid
Informal Education (Museum) Grid
Teacher Educator Grids
Education as a Grid of Grids (thanks to Geoffrey
Fox)
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Vision e-Research

• 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

• Not just new Science
• e-Social Science
• e-Humanities
• e-Arts
• e-Research
• e-Business
• e-Anything
• And new disciplines!

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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

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Vision Collaboratory

• A collaboratory is

a center without walls, in which the nation's
researchers can perform their research without
regard to geographical location, interacting with
colleagues, accessing instrumentation, sharing
data and computational resources, and accessing
information in digital libraries
William Wulf, 1989 U.S. National Science
Foundation
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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/

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Vision The Grid
Courtesy of Ian Foster
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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 problemas 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

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Challenges Unanticipated Re-use

• Wish to reuse
• Data
• Services
• Software
• Knowledge

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Challenges Data Integration
Many sources of data, services, computation
Registries organize services of interest to a
community
Courtesy of Ian Foster
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Challenges Virtual Orgs

• Resource configurations are transient, dynamic
  and volatile as services (databases, sensors,
  compute servers) switched in and out
• They are ad-hoc as service consortia have no
  central location or control, and no existing
  trust relationships
• They may be large, with hundreds of services
  orchestrated at any time
• They may be long-lived, for example a protein
  folding simulation could take weeks

• Scale of data and compute resources is large
• Quality of Service and performance criteria are
  severe
• Platform must be scalable, able to evolve,
  fault-tolerant, robust, persistent and reliable
• It should work seamlessly, and transparently
  the user might not know or care where their
  calculation is done using how many machines, or
  where data is actually held

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Challenges Comp Sci

• Dynamic formation and management of virtual
  organisations
• Online negotiation of access to services who,
  what, why, when, how
• Configuration of applications and systems able to
  deliver multiple qualities of service
• Autonomic management of distributed
  infrastructures, services, and applications
• Management of distributed state as a fundamental
  issue

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Outline

• The e-Vision and its challenges
• Enabling Technologies
• Grid
• Semantic Web
• Semantic Grid
• Building Bridges

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Two infrastructure enablers
Grid Computing
Semantic Web

• On demand transparently constructed
  multi-organisational federations of distributed
  services
• Distributed computing middleware
• Computational Integration

• An automatically processable, machine
  understandable web
• Distributed knowledge and information management
• Information integration

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Five Myths busted!

• Isnt 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!
• Isnt it just High Performance computing?
• No its 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

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Five Myths busted!

• Isnt 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
• Isnt it just Globus toolkit?
• No that is one reference implementation.
• Isnt it just a bunch of academic physicists?
• No all the commercial vendors are making serious
  investment. IBM DB2 and Oracle 10g will be
  grid-compliant

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Grid Services
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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

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Layers of Languages
Attribution
Explanation
We are here!
Rules Inference
Ontologies
Metadata annotations
Standard Syntax
Identity
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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

Graphic courtesy of Tim Berners-Lee
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OWL Web Ontology Language
DARPA Agent Markup Language
Ontology Inference Layer
DAML
OIL
RDF

• EU/NSF Joint Ad hoc Committee
• The most popular ontology language in the world
  ever!

DAMLOIL
All influenced by RDF
OWL Lite (thesaurus) OWL DL (reason-able) OWL
Full (anything goes)
A W3C Recommendation
OWL
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5 More Myths Busted!

• Isnt it just AI and distributed agents (again)?
• No It is primarily metadata integration and
  querying
• Dont you need all that reasoning stuff?
• No A little bit of semantics goes a long way!
  (Hendler)
• It only applies to the Web?
• 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!
• No multiple ontologies multiple everything!
• One big Semantic Web!
• No lots of Semantic Web-lets, and expect it to
  break!

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Outline

• The e-Vision and its challenges
• Enabling Technologies
• Grid
• Semantic Web
• Semantic Grid
• Building Bridges

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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

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Semantic Grid
SemanticWeb
SemanticGrid
Scale of Interoperability
ClassicalWeb
ClassicalGrid
Scale of data and computation
Based on an idea by Norman Paton
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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 peopleto work in cooperation
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Underpinnings of e-Science

• Contrast with

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Knowledge Grid
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Advanced Grid Applications

Knowledge Grid
Text mining
Data mining
Col- laboratory
Portal
Knowledge Services
OGSA Semantic Grid services
Knowledge-based information services
Knowledge-based data/computation services
OGSA Base Grid services
Computation services
Information services
Data services
Grid Middleware Fabric
WSRF
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Grid Computing trajectory
Virtual organisations with dynamic access to
unlimited resources
There are SG technologies available today for
immediate deployment
cost
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
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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

RDF-based semantic mark up of results, logs,
notes, data entries
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Engineering Design
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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
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Collaboration tools
awareness ofcolleagues presence
BuddySpace
Access Grid Node
virtual meetings
mapping real time discussions/group sensemaking
NetMeeting
recovering information from meetings
enacting decisions/coordinating activities
synthesising artifacts
I-X Tools

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NASA Scenario
1. Astronauts debrief on EVA
Compendium maps from trained compendium astronaut
Remote Science Team (RST) on earth e.g. geologists
Video and Science Data
Mars
Plan for next Days EVA
2. Virtual meeting of RST using CoAKTinG tools
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Finding collaborators

• Using scaleable triple store and AKT ontology

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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

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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 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
  Schroeter

• Using the Semantic Grid to Build Bridges between
  Museums and Indigenous Communities Ronald
  Schroeter
• 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
• Interoperability and Transformability through
  Semantic Annotation of a Job Description Language
  Jeffrey Hau

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E-Science Special Issue

• IEEE Intelligent Issue Special Issue on
  E-Science, Jan-Feb 2004
• De Roure, Gil, Hendler
• Challenges
• Realizing the network effect
• Moving beyond centralized stores
• Automated assembly
• Collaboration tools

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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
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Outline

• The e-Vision and its challenges
• Enabling Technologies
• Grid
• Semantic Web
• Semantic Grid
• Building Bridges

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Building bridges
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Semantic
Pervasive
Grid
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Semantic Grid security and trust policies,
management and frameworks
Resource selection scheduling
Ontologies for service classification
Knowledge Representation for Semantic Grid
Services
Semantic interoperability and integration
Semantics in Agent Communication Languages
Workflow and schedule repair
Knowledge-based provenance and audit trails
Semantics for service delegation and knowledge
aggregation
Service Negotiation
Quality of service and service level agreement
management
(Semantic) event notification
Models for quality and accessibility of data
sources, incl. versioning, recoverability, etc.
Lifetime management
Architectures for supporting Semantic Grid
Services
New models for fault tolerance and dependability
(Semantic) Service state
Virtualisation and provisioning of knowledge
service
Audit trails over transient state
Naming
Scaleable service composition for heterogeneous
environments
Service enactment/invocation frameworks
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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?

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Contact

• David De Roure
• University of Southampton, UK
• dder_at_ecs.soton.ac.uk
• Carole Goble
• University of Manchester, UK
• carole_at_cs.man.ac.uk
• See www.semanticgrid.org

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Acknowledgements