1. Semantic Web Technologies Readings discussion Research presentations Projects & Papers discussions

2. Semantic Web ideas aid Discovery Machine (system) use of metadata automatically The network is the delivery system & addressing scheme - Network properties are metadata too Markup languages can express meaning - Formatting too - Context matters Meaning clusters into taxonomies - So does use & intent Taxonomies can fit into ontologies - Logical rules define the data & its relationships

3. Semantic Discovery Challenges Is Discovery BIGGER than Search? Searching & Understanding - Interfaces like a reference interview? How can we leverage others’ structure? - Other’s searching? - Others’ data? Does the interface change? - Make sense of huge amounts of data - Making sense of data may be more difficult Integrating systems logically helps users understand current information & provides new information in context

4. Is it all really about search? - Discovery of knowledge via taxonomies - Web service based data searches - Search by association By example Facets - Pattern searches OLAP reporting Status & monitoring - Interfaces & agents Ease of use Automatic use (or help) - Rule-based queries Structured Query Language for structured data? - Inference Personalized search

5. Berners-Lee on the Semantic Web “bring structure to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users” (Berners-Lee, 2001) Meaningful? Content? Agents? Tasks?

6. Searching

7. Semantic Searching Self-describing metadata - Reliability Machine readable, people understandable HTML? - Accuracy Personal Relevance - Annotations What can information specialists add? What other fields?

8. TAP: Semantic Web Data Query Interfaces & Publishing - Access information from an organized information set Semantic Negotiation - Registries & Trust Augmenting with Data - Denotation Ambiguity detection Multiple passes - Extraction RDF - Visualization What to show “Just knowing that the user is searching form information about a person… can help avoid several mistakes.”

9. Improving search What would you do? - Tagging systems for retrieval help - Different kinds of information (images) - Better interfaces for search query formulation - Better interfaces for search results display - Take unstructured information & build taxonomies or ontologies for organization - Enable easier comparison of information Expose the metadata & make it understandable - Improve existing search using Web services

10. Agents Programs That Use Semantic Web Content - These programs build upon each other - Exchanging information between them More Automated as Systems and Content Support Increases Digital Signatures - The Semantics of Trust - Exchanging proofs Service Discovery Ontology Exchanges - Fitting my ontology into yours & sorting out the rules Coordination of machines first, then information?

11. Agents & Trust People & machines can understand the data Does trust only matter in commerce? Extracting structure from multiple searches - Can a Semantic Spider help? How can you leverage other’s trust when searching? How can that be automated with an agent? An Ontology for Policies of Trust - Permissions - Obligations - Actions - Credentials - Certificates

12. Semantic Clustering with Facets Clustering helps with classifying Facets can represent navigable clusters to help clarify search - Disambiguation - Learning about the topic Hierarchical Faceted Categories - Meaningful labels that represent structure & content - Navigational control Location Next steps Paths through the information