KMi-SMI collaboration

Wenjin Lu and Enrico MottaKnowledge Media Institute

Monica CrubézyStanford Medical Informatics

Goals

• Customizing Protégé editor for use with OCML (Protégé-OCML)– Evaluating Protégé suitability

• Translating classification library into Protégé-OCML– Validating classification library– Evaluating UPML

• Revising Specification for Internet Reasoning Service

1. The Protégé-UPML editor for OCML

• Modeling of OCML meta ontology in Protégé– i.e., classes, relations, functions, axioms, etc...

• Inclusion of OCML meta ontology in Protégé-UPML editor– i.e., defining the appropriate KA forms for the basic OCML

constructs

• Extension of UPML concepts for OCML, with reference to OCML meta ontology– e.g., formula -> OCML-formula

OCML meta ontology in ProtégéBy the way, this is the output of a new plugin for Protégé,

that creates a graph out of a KB,with different visualization options

subclass-of linkinstance-of link

Each OCML construct is an instance of :OCML-CLASS

Template slots define own OCML

fields for all classes

OCML in Protégé-UPML editor

• Inclusion of OCML meta ontology in UPML domain modelling meta-ontology

• Extension of UPML concepts for OCML (“UPML-OCML concepts”)

– Formula < OCML-Formula • formula -> ocml-kappa-expression, ocml-relation-mapping

– Program < OCML-Program• program -> ocml-lambda-expression, :OCML-PROCEDURE

– Signature Element < OCML-Element • ocml-type -> :OCML-CLASS, :OCML-RELATION, :OCML-FUNCTION

– Signature < OCML-Signature • signature-elements -> (OCML-Element)

UPML core ontology isextended for OCML

2. The Classification library in UPML

Task-DomainBridge

PSM-DomainBridge

PSM-TaskBridge

Task

Task Refiner

DomainModel

Domain Refiner

PSM

PSM Refiner

Ontologies

Ontology Refiner

Classification Library

Heuristicclassifier

(Optimal)Classification

Optimal classification@ Heuristic classifier

Apples

Heuristic classifier@ Apples

Optimal classification@ Apples

Abtractor,Refiner

Color “green”,Sugar-level

Observable, Solution

Abstractor = Sugar-abstractorSolution = Apple class

The Classification library in Protégé-UPML

• Classification ontologies modeled in Protégé-OCML– Classification task, heuristic classification method, apples

domain, apples @ heuristic classification application– Modeled as separate ontologies in Protégé-OCML (ie, a

hierarchy of classes that are instances of OCML primitives)– Included along with UPML-OCML (UPML extended for OCML)

• UPML-OCML concepts instantiated with elements of the included classification ontologies

• UPML concepts instantiated with classification tasks, PSMs, knowledge roles, etc.

Classification ontologies in Protégé-OCML

OCML-BASE

CLASSIFICATION-TASK

HEURISTIC-CLASSIFICATION-METHOD

APPLE-DOMAIN

APPLE-HEURISTIC-CLASSIFICATION-APPLICATION

included-inincluded-in

included-inincluded-in

included-in

Each concept is an instance of

:OCML-CLASS

Own slots contain OCMLdefinition of the class

Classification Library instance

Classification Task instance

Task: Classification (ontology signature)

Task: Classification (competence)

Heuristic optimal solution classifier PSM

Heuristic optimal solution classifier PSM (Signature and Competence)

Heuristic optimal solution classifier PSM (Operational description)

Classification-task @ apples-domain bridge

4 mapping axioms define the bridge

Classification-task @ apples-domain bridge (mapping axiom for observable)

Conclusions of the experiment

• Customization of Protégé-UPML for OCML– 2-step process: OCML in Protégé + extension of UPML for

OCML– Reasonably easy to do!

• Classification library in UPML– Fits nicely, except:

• Knowledge roles (case-indep. data) at the task & complex PSM level

• Task, PSMs, etc. are classes in OCML, not instances as in UPML

• Needs the implementation of a connection to OCML interpreter

3. Internet Reasoning Service