Design of DAML+OIL_ An Ontology Language for the Semantic Web

							Design of DAML+OIL: An Ontology Language for the Semantic Web.
Written By: Ian Horrocks Peter F.Patel Frank van Harmelen

Presented by:- Jenish Parekh.

Introduction
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DAML-DARPA Agent Markup Language. OIL- Ontology Interface Layer. DAML+OIL
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an Ontology Language for semantic web. It takes an OO approach in terms of classes and properties. Consists of axioms

Foundations in DL

DAML+OIL class constructors

Foundations in DL (Conti..)

DAML+OIL axioms

Foundations in DL (Conti..)
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Axioms
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Make it possible to assert equivalence with respect to classes and properties, disjoint ness of classes, individuals and properties of properties. Crucial feature- subClassOf and sameClassas axioms Increases expressive power w.r.t. standard frame-based languages.

XML Data types in DAML+OIL
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Supports full range of data types in XML schema
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Data types are considered to be already sufficiently structured The simplicity and compactness of the ontology are not compromised. The semantic integrity of the language is not compromised. The implementability of the language is not compromised

XML Data types in DAML+OIL (Conti..)
 From Theoretical point of view
Ontology language can specify constraints on data values.
Allows the type system to be extended Formal properties of hybrid reasoners are determined by those of the two components.

XML Data types in DAML+OIL (Conti..)
From Practical Point of view.
DAML+OIL implementation can choose to support some or all of the XML schema data types. Can implement their own type checker/validater

Extending RDF schema
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Tightly integrated with RDFS Advantages because of dependency on RDFS
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Reuse of RDFS infrastructure Portability of ontology

Extending RDF schema (Conti..)
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Problems Difficult to design complete structure Can’t state that restriction should hold exactly one property and one class. Solution

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DAML+OIL vs. OIL
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From the point of view of language constructs. OIL also uses RDFS for serialization. Any ontology conforming to the RDFS meta-description may not be a valid OIL ontology. Treatment of individuals in OIL also different from that in DAML+OIL.

Challenges
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Individuals
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DAML+OIL individuals with inverse property pushes complexity from ExpTime to NExpTime. Currently no practical decision procedure is known for this logic. No implemented system can provide sound and complete reasoning for whole DAML+OIL langguage.

Challenges
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Scalability
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Without “one of” constructor class consitency reasoning is still a hard problem. There is good evidence of empirical tractability and scalability for implemented DL systems, but its mostly w.r.t. logics that do not have inverse property Inverse property makes practical implementation more problamatic.

Challenges
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New Reasoning Tasks.
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Querying , explanation, matching, computing least subsumers may be important problems to be considered. Querying in semantic web application

Conclusion
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We have discussed a number of fundamental design decision underlying the design of DAML+OIL, in particular its foundation in Description Logic, its use of data types from XML schema, and its deviations from its predecessor OIL. We have also described how various aspects of the language are motivated by the desire for tractable reasoning facilities. Although a number of challenges remain ,DAML+OIL has considerable merits. In particular, the basic idea of having formally specified web language that can represent ontology information will go a long way towards allowing computer programs to interoperate without pre-existing web agreements

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Thank you