building owl ontology driven applications
DESCRIPTION
Building OWL Ontology Driven Applications. OCHWIZ : A prototype medical application. Jay Kola, 10/09/2007. Why use OWL?. Good expressive power. Intuitive for domain experts. W3C recommendation for knowledge representation. Built-in logic services that allow inferences to be made. - PowerPoint PPT PresentationTRANSCRIPT
Building OWL Ontology Driven Applications
Jay Kola,10/09/2007
OCHWIZ : A prototype medical application
Why use OWL?
• Good expressive power.• Intuitive for domain experts.• W3C recommendation for
knowledge representation.• Built-in logic services that allow
inferences to be made.
Example : Pigmentation
• Pigmentation has cause Arsenic.• Black Pigmentation has cause Coal tar
constituents (Asphalt, Pitch).• Arsenic is exposed by Glass product
manufacturing and Electronic product manufacturing.
• Coal tar constituents are exposed by Construction industry.
User Questions ?
• What are the causes of Black Pigmentation?
• What are the industries associated with Black Pigmentation?
Arsenic Coal tar constituents Pitch Asphalt
Construction Industry
Glass product manufacturing
Electronic product manufacturing
Table Representation
Clinical Finding Cause
Pigmentation Arsenic
Black Pigmentation Coal Tar Constituents
Black Pigmentation Asphalt
Black Pigmentation Pitch
Cause Industry
Arsenic Glass product manufacturing
Arsenic Electronic product manufacturing
Coal Tar Constituents Construction Industry
Asphalt Construction Industry
Pitch Construction Industry
Clinical Finding Cause
Pigmentation Arsenic
Black Pigmentation
Coal Tar Constituents
Black Pigmentation
Asphalt
Black Pigmentation
Pitch
Black Pigmentation
Arsenic
Blue Pigmentation Silver Salts
Blue Pigmentation Arsenic
OWL RepresentationPigmentation - types Coal tar constituents
Blue Pigmentation - definition
Pigmentation - definition
Construction types
Associations of Pigmentation
Associations of Black Pigmentation
Reciprocal Inferences
is_cause_of some Black Pigmentation
has_cause some Coal_tar_constituent
Give me causes of Black pigmentation
Give me diseases caused by Coal tar or Arsenic
Reciprocal Relationships
• Kills the DL reasoner ….
How to implement Reciprocals Inferences ?• Mirror Ontologies
– One ontology has all relationships in one direction only
– Create two such ontologies. Query each separately. Combine results.
• Use OWL Individuals
Other Reasoner Issues
• Use of disjunctions– D has_cause (A1 or A2 or A3…)
• Scaling problems– FaCT++ is really fast.– Classification time depends on
ontology complexity.
Conclusion
• Reasoner issues can be overcome easily.• OWL offers an intuitive way to model
knowledge.• DL Reasoner service can be integrated
into an application easily.• Makes intelligent application development
easy.• A whole lot of OWL ontologies are
available for download on the web…. GET GOING !