1. Semantic Web Agents: Hope or Hype Nicholas Gibbins School of Electronics and Computer Science University of Southampton

2. 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?

3. 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 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

4. Example: Scientific American article Tim Berners-Lee James Hendler Ora Lassila The Semantic Web Scientific American vcard:fn dc:title dc:creator akt:publishedIndc:creator 2001-05 dc:date Relation and object types are defined in a machine-understandable form – an ontology

5. The Semantic Web layer cake XML + Namespaces URIUnicode SignatureEncryption Rules Proof Trust RDF RDF Schema OWL Identity Standard syntax Metadata Ontologies + Inference Explanation Attribution SPARQL (queries) User Interface and Applications

6. Semantic Web c. 2004 The Semantic Web Hype Cycle Technology Trigger Peak of Inflated Expectation Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Visibility Maturity Gartner

7. 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 searching ∙ (but NLP is hard)

8. 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)

9. 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 connection. Tim Berners-Lee, Business Case for the Semantic Web, http://www.w3.org/DesignIssues/Business

10. 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

11. ∙ Improving the information environment for chemists – both within and beyond the lab ∙ Supporting chemists in the preparation, execution, analysis and dissemination of their work http://www.smarttea.org/

12. Data Capture: The Lab Notebook

15. Publish and Reuse http://ecrystals.chem.soton.ac.uk

16. Exchange Vocabularies ∙ BioPax Ontology (biological pathways) ∙ Metabolic and signalling pathways, molecular interactions ∙ Gene Ontology (genes and gene products) ∙ Molecular function, cellular component, biological process ∙ NCI Cancer Ontology ∙ Diseases, drugs, anatomy, genes (and many others from other disciplines)

17. 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

18. Agent Based Computing ∙ Societies of components, owned by different organisations ∙ 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

19. The Agent Hype Cycle Technology Trigger Peak of Inflated Expectation Trough of Disillusionment Slope of Enlightenment Plateau of Productivity Visibility Maturity Agents c. 1995 Agents c. 2005

20. 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 systems ∙ Can be aligned with related work on Grid Computing

21. 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 resources ∙ Virtual organisations ∙ Workflow management ∙ Social computing, in effect

22. http://www.combechem.org/ X-Ray e -Lab Analysis Properties e -Lab Simulation Video Diffractometer Grid Middleware Structures Database Properties

23. http://www.mygrid.org.uk

24. 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

25. 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

26. 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

27. Thank you!