Semantic Web Agents Hope or Hype Nicholas Gibbins

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 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. W 3 C Activity Statement

Example: Scientific American article 2001 -05 The Semantic Web dc: title dc: date dc: creator vcard: fn dc: creator akt: published. In vcard: fn Tim Berners-Lee James Hendler Ora Lassila dc: title 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 Rules RDF Schema RDF Explanation Ontologies + Inference Metadata XML + Namespaces URI Encryption OWL SPARQL (queries) Signature Proof Standard syntax Unicode Identity

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

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)

Which Semantic Web? Semantic Web as the Web of Data ∙ Expose existing databases in a common format ∙ Express database schemas in a machineunderstandable 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 connection. Tim Berners-Lee, Business Case for the Semantic Web, http: //www. w 3. org/Design. Issues/Business

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 http: //www. smarttea. org/

Data Capture: The Lab Notebook

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

Exchange Vocabularies ∙ Bio. Pax 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)

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 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

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

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

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

$Video Simulation Diffractometer Properties Analysis Structures Database X-Ray e-Lab Properties e-Lab Grid Middleware http:$

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

http: //www. mygrid. org. uk

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 welldefined 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 largescale e-Science applications ∙ Agent technology is approaching maturity, and offers management of rich patterns of interaction in service-oriented systems

Thank you!