1. 1 CSIT600f: Introduction to Semantic Web Conclusion and Outlook Dickson K.W. Chiu PhD, SMIEEE Text: Antoniou & van Harmelen: A Semantic Web PrimerA Semantic Web Primer (Chapter 8)

2. Dickson Chiu 2005CSIT600f s-2 How it All Fits Together Scenario: Bargaining among personal software agents Each party represented by a software agent They commit to shared understanding of terms: an ontology (e.g. in RDFS or OWL) Case facts, offers and decisions are represented as RDF statements

3. Dickson Chiu 2005CSIT600f s-3 How it All Fits Together (2) Information is exchanged in some XML-based language (or RDF-based language) Agent negotiation strategies are described in a logical language Agents decide about next course of action through inference, based on negotiation strategy, case facts and previous offers and counteroffers

4. Dickson Chiu 2005CSIT600f s-4 Web Ontology Language: Is Less More? In the beginning the focus was more on expressive power Simpler languages have advantages: More efficient reasoning support Easier to learn and apply Easier for tool vendors to support OWL Lite is a step in this direction

5. Dickson Chiu 2005CSIT600f s-5 Rules and Ontologies Rules are orthogonal to description logics One could try to combine them Computational problems Rule-based languages as alternatives to OWL? Rule-based systems on top of ontology languages

6. Dickson Chiu 2005CSIT600f s-6 Will the Semantic Web Succeed? Key Questions Where will the ontologies come from? Where will the semantic markup come from? Where will the tools come from? How should one deal with a multitude of ontologies? Where can we expect the first success stories?

7. Dickson Chiu 2005CSIT600f s-7 Where Will the Ontologies Come From? Some large ontologies are becoming de facto standards WordNet NCIBI’s cancer ontology Many small ontologies are hand-created (e.g., RosettaNet) or Created automatically through machine learning, natural language analysis and from legacy cources (e.g., data schemas)

8. Dickson Chiu 2005CSIT600f s-8 Where Will the Semantic Markup Come From? Clearly not by hand Tools for new information resources Natural language techniques, borrowing from legacy sources for old resources

9. Dickson Chiu 2005CSIT600f s-9 Where Will the Tools Come From? Large variety of tools already exists Editors, storage, querying and inferencing, visualization, versioning Mostly developed in academic domain … but taken up in the commercial sector Highly innovative startups

10. Dickson Chiu 2005CSIT600f s-10 How Should one Deal With a Multitude of Ontologies? A big research question, still open A potential bottleneck Various approaches currently tested Negotiation Machine learning Linguistic analysis

11. Dickson Chiu 2005CSIT600f s-11 Promising Areas for Initial Successes Knowledge Management … because of central authority E-Science Use ontologies, are informed and enthusiastic users of new technology E-Commerce probably later Problems with privacy, security and trust