2. Gibbins - semantic web agents by dandanhuanghuang


									Semantic Web Agents:
Hope or Hype

Nicholas Gibbins
School of Electronics and Computer Science
University of Southampton
The Cynic’s View

The Semantic Web and agent technologies
are just old-fashioned artificial intelligence.

Artificial intelligence hasn’t delivered on its
previous promises, so why should it now?
         What is 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
The Web can reach its full potential if it
becomes a place where data can be
processed by automated tools as well as
                                              W3C Activity Statement
     Example: Scientific American article

The Semantic Web              dc:date

                                                        Tim Berners-Lee
                dc:title                     vcard:fn

                                                        James Hendler
   akt:publishedIn          dc:creator       vcard:fn

                                                          Ora Lassila
                            dc:creator       vcard:fn


      Scientific American                Relation and object types are
                                         defined in a machine-understandable
                                         form – an ontology
 The Semantic Web layer cake

        User Interface and Applications
                      Trust                                             Attribution
                  Proof                                                 Explanation

SPARQL              OWL           Rules                                 Ontologies +
(queries)                 RDF Schema                                    Inference

                  RDF                                                   Metadata
             XML + Namespaces                                           Standard syntax
            URI                           Unicode                       Identity
             The Semantic Web Hype Cycle

                Semantic Web
                c. 2004

             Technology Peak of Inflated Trough of       Slope of      Plateau of    Maturity
               Trigger    Expectation Disillusionment Enlightenment   Productivity

Which Semantic Web?

Semantic Web as the Annotated Web

∙ Enrich existing web pages with annotations
∙ Classify web pages
∙ Use natural language techniques to extract
  information from web pages

∙ Annotations enable enhanced browsing and
∙ (but NLP is hard)
Which Semantic Web?

Semantic Web as the Web of Data

∙ Expose existing databases in a common format
∙ Express database schemas in a machine-
  understandable form

∙ Common format allows the integration of data in
  unexpected ways
∙ Machine-understandable schemas allow reasoning
  about data
∙ (make the most of the structure you already have)
        Rocket Science (not)

Is this rocket science? Well, not really. The Semantic Web,
like the World Wide Web, is just taking well established
ideas, and making them work interoperably over the
Internet. This is done with standards, which is what the
World Wide Web Consortium is all about. We are not
inventing relational models for data, or query systems or rule-
based systems. We are just webizing them. We are just
allowing them to work together in a decentralized system -
without a human having to custom handcraft every
                   Tim Berners-Lee, Business Case for the Semantic Web,
e-Science and the Semantic Web

∙ e-Science characterised as:
   ∙   Large-scale science
   ∙   Distributed global collaborations
   ∙   Very large data collections
   ∙   Very large scale computing resources

∙ Data integration will be a major issue
   ∙ Capture, publish, reuse data
   ∙ Agreed vocabularies for data exchange
                           ∙ Improving the information
                             environment for chemists –
                             both within and beyond the lab
                           ∙ Supporting chemists in the
                             preparation, execution, analysis
                             and dissemination of their work

Data Capture: The Lab Notebook
Ingredient List
                                                                     Dissolve 4-      Add K2CO3                 Heat at reflux
Fluorinated biphenyl                   0.9 g
                                                                     flourinated      powder                    for 1.5 hours
Br11OCB                                1.59 g                        biphenyl in
Potassium Carbonate                    2.07 g                        butanone
Butanone                               40 ml

                                                           Add                       Add                       Reflux

                                                                0.9031    grammes


                                                    Sample of 4-
Butanone dried via silica column and
  measured into 100ml RB flask.                      flourinated
 Used 1ml extra solvent to wash out                    biphenyl

                                                                      1       1                2        2                  1           3
                                                            Add                       Add                      Reflux
                                                                                                   Sample of
                                                Measure                                             Powder

                                                                                                             Started reflux at 13.30. (Had to
                                                                                                            change heater stirrer) Only reflux
                                                      40        ml                                             for 45min, next step 14:15.

                                                                                      2.0719        g
            Publish and Reuse

Exchange Vocabularies

∙ BioPax Ontology (biological pathways)
   ∙ Metabolic and signalling pathways, molecular
∙ Gene Ontology (genes and gene products)
   ∙ Molecular function, cellular component, biological
∙ NCI Cancer Ontology
   ∙ Diseases, drugs, anatomy, genes

(and many others from other disciplines)
What are Agents?

∙ Many definitions of agent
  ∙   Mobile agents
  ∙   Collaborative agents
  ∙   Social agents
  ∙   Interface agents
∙ Three broad perspectives:
  ∙ Agents as design metaphor
  ∙ Agents as technology source
  ∙ Agents as simulation
Agent Based Computing

∙ Societies of components, owned by different
∙ Components provide services to each other
∙ Computing as a social activity
   ∙   Workflows and Planning
   ∙   Coordination, Collaboration and Negotiation
   ∙   Markets and auctions
   ∙   Models of trust and reputation

∙ Managing the distributed processing of data
             The Agent Hype Cycle


                        c. 1995

                                            c. 2005

             Technology Peak of Inflated Trough of       Slope of      Plateau of    Maturity
               Trigger    Expectation Disillusionment Enlightenment   Productivity
What’s different this time?

∙ First agent wave assumed that a special
  agent infrastructure was needed
   ∙ Hindered integration with existing systems
   ∙ Several high-profile failures in the marketplace
∙ Second agent wave is building on existing
  technologies such as Web Services
   ∙ Incremental approach that integrates existing
   ∙ Can be aligned with related work on Grid
Grid Computing

∙ e-Science applications typically have very high
  computational requirements
∙ Grid Computing provides an infrastructure for
   ∙ Flexible, secure, coordinated resource sharing
   ∙ Dynamic collections of individuals, institutions and
   ∙ Virtual organisations
   ∙ Workflow management

∙ Social computing, in effect




      X-Ray                                                                   Properties
      e-Lab                                                                   e-Lab

                                             Grid Middleware

       The Next Generation Grid

“The ongoing convergence between Grids, Web Services
and the Semantic Web is a fundamental step towards the
realisation of a common service-oriented architecture
empowering people to create, provide, access and use a
variety of intelligent services, anywhere, anytime, in a
secure, cost-effective and trustworthy way.”

                                            Next Generation Grids 2
                                       Requirements and Options for
                     European Grids Research 2005-2010 and Beyond
                                   EU Expert Group Report July 2004
The Semantic Grid

∙ Grid Computing + Semantic Web
∙ Information and services are given a well-
  defined meaning
   ∙ Uses SW technologies – OWL, RDF, etc
   ∙ Ontologies for describing services
∙ Better enables computers and people
  to work in cooperation
   ∙ Requires coordination and planning capabilities
     found in agent technologies
Hope or Hype?

∙ Web Services and Grid Computing are
  already a reality
∙ The Semantic Web is being used in large-
  scale e-Science applications
∙ Agent technology is approaching maturity,
  and offers management of rich patterns of
  interaction in service-oriented systems
Thank you!

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