1 / 27

Semantic Web Agents: Hope or Hype

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.

tamyra
Download Presentation

Semantic Web Agents: Hope or Hype

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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 beused 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 2001-05 The Semantic Web dc:date Tim Berners-Lee dc:title vcard:fn dc:creator James Hendler vcard:fn akt:publishedIn dc:creator Ora Lassila dc:creator vcard:fn dc:title Relation and object types aredefined in a machine-understandableform – an ontology Scientific American

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

  6. The Semantic Web Hype Cycle Semantic Webc. 2004 Visibility Plateau ofProductivity TechnologyTrigger Peak of InflatedExpectation Trough ofDisillusionment Slope ofEnlightenment 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

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

  14. 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)

  15. 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

  16. 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

  17. The Agent Hype Cycle Agentsc. 1995 Visibility Agentsc. 2005 Plateau ofProductivity TechnologyTrigger Peak of InflatedExpectation Trough ofDisillusionment Slope ofEnlightenment Maturity

  18. 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

  19. 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

  20. Video Simulation Properties Analysis StructuresDatabase Diffractometer X-Raye-Lab Propertiese-Lab Grid Middleware http://www.combechem.org/

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

  22. 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

  23. 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 peopleto work in cooperation • Requires coordination and planning capabilities found in agent technologies

  24. 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

  25. Thank you!

More Related