《高级Web技术》参考资料：语义Web课件 A Semantic Web Primer_Chapter8 Conclusion and Outlook

Chapter 8 Conclusion and outlook Grigoris Antoniou Frank van Harmelen 1 Chapter 8 A Semantic Web Primer

1 Chapter 8 A Semantic Web Primer Chapter 8 Conclusion and Outlook Grigoris Antoniou Frank van Harmelen

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) e Case facts offers and decisions are represented as RDF statements Chapter 8 A Semantic Web primer

2 Chapter 8 A Semantic Web Primer 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

How it All Fits Together(2) o Information is exchanged in some XML based language(or RDF-based language) o Agent negotiation strategies are described in a logical language o Agents decide about next course of action through inference, based on negotiation strategy, case facts and previous offers and counteroffers 3 Chapter 8 A Semantic Web primer

3 Chapter 8 A Semantic Web Primer 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

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 suppor rt OWL Lite is a step in this direction Chapter 8 A Semantic Web primer

4 Chapter 8 A Semantic Web Primer 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

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 5 Chapter 8 A Semantic Web primer

5 Chapter 8 A Semantic Web Primer 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

Will the Semantic Web succeed? Key Questions o Where will the ontologies come from? o Where will the semantic markup come from? e Where will the tools come from? e How should one deal with a multitude of ? ontologies o Where can we expect the first success stories? 6 Chapter 8 A Semantic Web primer

6 Chapter 8 A Semantic Web Primer 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?

Where Will the Ontologies Come From? e 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) 7 Chapter 8 A Semantic Web primer

7 Chapter 8 A Semantic Web Primer 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)

Where Will the Semantic Markup Come From? ● Clearly not by hand o Tools for new information resources o Natural language techniques, borrowing from legacy sources for old resources 8 Chapter 8 A Semantic Web primer

8 Chapter 8 A Semantic Web Primer 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

Where will the Tools come from? o Large variety of tools already exists Editors, storage, querying and inferencing VISualIzation, versioning o Mostly developed in academic domain but taken up in the commercial sector Highly innovative startups 9 Chapter 8 A Semantic Web primer

9 Chapter 8 A Semantic Web Primer 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

How Should one deal with a multitude of Ontologies? a big research question, still open A potential bottleneck o Various approaches currently tested Negotiation Machine learning Linguistic analysis 10 Chapter 8 A Semantic Web primer

10 Chapter 8 A Semantic Web Primer 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