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The Semantic Web and Ontology

Explore the power of the Semantic Web and Ontology, enabling intelligent services and knowledge sharing while ensuring machine-processable data and metadata. Learn the crucial role of ontology in modeling real-world information and fostering semantic understanding. Dive into the concepts, applications, and limitations of Semantic Web technologies.

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The Semantic Web and Ontology

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  1. The Semantic Web and Ontology

  2. The Semantic Web • WWW: • syntactic transmission of information • only processible by human • no semantic conservation of the information • can not be processed by machine (e.g.. Machine does not know whether a branch means a part of a tree or a part of an organization)

  3. The Semantic Web • Information transmitted conserves semantics • information can be processed by machines • enable intelligent services: search agents, information brokers, and information filters

  4. What is information • Factual data • Meta Data about data • plans and activities • beliefs and doubts • Reasoning

  5. What is an Ontology? • The conceptualization of a domain • Represented as a set of terms and their relationships • An example: • a car is a type of automobile • it has engine, transmission, steering wheel, etc as parts • its energy source can be gasoline or electricity • and so on

  6. Term: a reference to real-world and abstract objects • Relationship: a named and typed set of links between objects • Reference: a label that names objects • Real-world object: an entity instance with a physical manifestation • Abstract object: a concept which refers to other objects

  7. An Example Ontology class-def animal class-def plant subclass-of NOT animal class-def defined carnivore subclass-of animal slot-constraint eats value-type animal class-def lion subclass-of animal subclass-of defined carnivore slot-constraint eats value-type herbivore

  8. Applications of Ontologies • Define Terms used in System Construction to Enable Correctness in Understanding designers, implementers, users, maintainers designers = implementers = users = maintainers • Define Higher-level Abstractions Needed to Communicate in Large Contexts managers, decision-makers, systems in other domains • Share the Cost of Knowledge Acquisition & Maintenance reuse encoded knowledge, remain up-to-date as domains change

  9. Why ontology is crucial for the Semantic Web • An existing technique to model the real world and information • Describe semantics • Understandable by different users • Ontology representation languages needs to be encoded into a machine-processable way

  10. Heavy-weight Ontology is needed for the Semantic Web • Light-weight Ontology • concepts, atomic types • is-a hierarchy among concepts • associations between concepts • Heavy-weight Ontology • cardinality constraints • taxonomy of relations • reified statements • Axioms / semantic entailments of various tastes • expressiveness (DL, propositional, horn, or first order logic, higher order) • inferences

  11. <course date=“...”><title>...</title><teacher>...</teacher> <name>...</name> <http>...</http><students>...</students></course> course title teacher students name http XML document = labeled tree node = label + attr/values + contents DTD: simple grammars to describe legal trees So: why not use XML to represent ontologies?

  12. Limitations of XML for Semantic Markup • Multiple possibilities to code an ontology • No commitment to domain-specific terms • Lacks modeling primitives • Requires pre-agreement between all users on a specific DTD

  13. RDF: Resource Description Framework • Intended for representation “meta-data”,basis for Web-based ontology-language • W3C recommendation • Supported by W3C • basis of $ 80M DAML program • Already embraced by some vendors(e.g.Netscape)

  14. pers05 ISBN... pers05 ISBN... MIT ISBN... Author-of • Object --Attribute-> Value tuples • Objects are web-resources • Value is again an Object: • data-model = graph Publ-by Author-of Publ-by Author-of

  15. RDF Schema • So, RDF : • (very small) commitment to modeling primitives • but: no commitment to domain vocabulary • RDF Schema • Define vocabulary for RDF • Organize this vocabulary in a typed hierarchy • Class, SubClassOf, type • Property, subPropertyOf, • domain, range

  16. RDF is Better than XML but Still Limited • Provides more semantic interoperability the object-attribute structure is natural semantic units easier mapping between two RDF descriptions XML independent • Lacks modeling primitives • Lacks semantic support (Description Logic) • provides syntax

  17. Ontology Inference Layer (OIL) • Sponsored by European Union IST programme for Information Society Technologies • Frame-based system + Description logic + RDF = OIL

  18. Ontology Inference Layer (OIL)

  19. RDF(S) OIL • class-def • subclass-of • slot-def • subslot-of • domain • range • class-expressions • AND, OR, NOT • slot-constraints • has-value, value-type • cardinality • slot-properties • trans, symm

  20. OIL as RDFS extension <rdfs:Class rdf:ID=”herbivore”> <rdf:type rdf:resource=”http://www.ontoknowledge.org/#DefinedClass”/> <rdfs:subClassOf rdf:resource=”#animal”/> <rdfs:subClassOf> <oil:NOT> <oil:hasOperand rdf:resource=”#carnivore”/> </oil:NOT> </rdfs:subClassOf> </rdfs:Class>

  21. OIL: currently available tools • Definition of language • semantics • XML encoding • RDF encoding • Tools: • translators (XSL based) • OntoEdit • case-studies • GIS ontology mapping • (KA)2 ontology • CIA world fact book

  22. DARPA Agent Markup Language (DAML) • Sponsored by the Defense Advance Research Project Agency • Develop technologies to provide interoperability between agents in semantic manner • First stage is DAML, similar to OIL

  23. Conclusion • OIL and DAML mark the first effort of using ontology for the Semantic Web • Both needs to be further enhanced • Tools to use these languages are in urgent need • Ontology interoperativity is the next step

  24. Future Directions • Tools to build and use ontology using the standard Web ontology language • Engineering tools to semantically integrate, migrate, reconciliate and share ontologies • Deploy the technology to be used for intelligent services

  25. References • Decker et al.(2000) The Semantic Web: the roles of XML and RDF. IEEE Internet Computing 4:63-74. • Bray et al. Extensible Markup Language (XML) 1.0, World Wide Web Consortium, 1998, current May 2000; www.w3.org/TR/REC-xml. • Brickley and Guha (2000) Resource Description Framework (RDF) Schima Specification. W3C Candidate Recommendation. http://www.w3.org/TR/2000/CR-rdf-schema-20000327/ • OIL, http://www.ontoknowledge.org/oil • DAML, http://www.daml.org

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