The Semantic Web and Ontology

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)

The Semantic Web

• Information transmitted conserves semantics

• information can be processed by machines• enable intelligent services: search agents,

information brokers, and information filters

What is information

• Factual data• Meta Data about data• plans and activities• beliefs and doubts• Reasoning

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

• 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

An Example Ontology

class-def animalclass-def plant

subclass-of NOT animalclass-def defined carnivore

subclass-of animalslot-constraint eatsvalue-type animal

class-def lionsubclass-of animalsubclass-of defined carnivoreslot-constraint eatsvalue-type herbivore

Applications of Ontologies

• Define Terms used in System Construction to Enable Correctness in Understandingdesigners, implementers, users, maintainersdesigners = implementers = users = maintainers

• Define Higher-level Abstractions Needed to Communicate in Large Contextsmanagers, decision-makers, systems in other domains

• Share the Cost of Knowledge Acquisition & Maintenancereuse encoded knowledge, remain up-to-date as domains change

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

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

XML document = labeled tree

course

teachertitle students

name http

<course date=“...”><title>...</title><teacher>...</teacher>

<name>...</name><http>...</http>

<students>...</students></course>

node = label + attr/values + contents

DTD: simple grammars to describe legal treesSo: why not use XML to represent ontologies?

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

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)

• Object --Attribute-> Value tuples

• Objects are web-resources• Value is again an Object:

– data-model = graph

pers05 ISBN...Author-of

Author-ofpers05 ISBN... MIT

ISBN...

Publ-by

Author-of Publ-by

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

RDF is Better than XML but Still Limited

• Provides more semantic interoperabilitythe object-attribute structure is natural semantic

unitseasier mapping between two RDF descriptionsXML independent

• Lacks modeling primitives • Lacks semantic support (Description Logic)• provides syntax

Ontology Inference Layer (OIL)

• Sponsored by European Union IST programme for Information Society Technologies

• Frame-based system + Description logic +

RDF

= OIL

Ontology Inference Layer (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

RDF(S) OIL

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>

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

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

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

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

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