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David

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The Semantic Grid is an extension of the current Grid in which ... CPU scavenging. CPU intensive workload Grid as a utility, data Grids, robust infrastructure ... – PowerPoint PPT presentation

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Title: David


1
The
  • David
  • De Roure

2
The what?
  • 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
  • The full richness of the Grid ambition depends
    upon realising the Semantic Grid, but for many
    its a mysterious hybrid of the Semantic Web and
    the Grid, both of which are subject to myths and
    misunderstandings
  • This talk will explain the changing landscape of
    the Grid, and describe the bridge-building needed
    to achieve the Semantic Grid

3
Outline
  • The e-Vision and its challenges
  • Enabling Technologies
  • Grid
  • Semantic Web
  • Semantic Grid
  • Building Bridges

4
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
5
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
(And to prove it invested 385 million over 5
years)
6
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!

7
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

8
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/

9
Vision The Grid
Courtesy of Ian Foster
10
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

11
Challenges Unanticipated Re-use
  • Wish to reuse
  • Data
  • Services
  • Software
  • Knowledge

12
Challenges Data Integration
Many sources of data, services, computation
Registries organize services of interest to a
community
Courtesy of Ian Foster
13
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

14
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

15
Outline
  • The e-Vision and its challenges
  • Enabling Technologies
  • Grid
  • Semantic Web
  • Semantic Grid
  • Building Bridges

16
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

17
(No Transcript)
18
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

19
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

20
Grid Services
21
(No Transcript)
22
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

23
Layers of Languages
Attribution
Explanation
We are here!
Rules Inference
Ontologies
Metadata annotations
Standard Syntax
Identity
24
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
25
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
26
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!

27
Outline
  • The e-Vision and its challenges
  • Enabling Technologies
  • Grid
  • Semantic Web
  • Semantic Grid
  • Building Bridges

28
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

29
Semantic Grid
SemanticWeb
SemanticGrid
Scale of Interoperability
ClassicalWeb
ClassicalGrid
Scale of data and computation
Based on an idea by Norman Paton
30
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
31
Underpinnings of e-Science
  • Contrast with

32
Knowledge Grid
33
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
34
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
35
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
36
Engineering Design
37
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
38
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

39
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
40
Finding collaborators
  • Using scaleable triple store and AKT ontology

41
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

42
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

43
E-Science Special Issue
  • IEEE Intelligent Issue Special Issue on
    E-Science, Jan-Feb 2004
  • De Roure-Hendler challenges
  • Realizing the network effect
  • Moving beyond centralized stores
  • Automated assembly
  • Collaboration tools

44
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
45
Outline
  • The e-Vision and its challenges
  • Enabling Technologies
  • Grid
  • Semantic Web
  • Semantic Grid
  • Building Bridges

46
Building bridges
47
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
48
(No Transcript)
49
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?

50
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

51
Acknowledgements
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