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On Relationships among Models, Meta Models and Ontologies
Motoshi SaekiTokyo Institute of Technology
Haruhiko KaiyaShinshu University
DSM'06@OOPSLA2006, Oct. 22, 2006, Portland
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Motivation & Approach Meta Model: Abstract Syntax for DSL Semantics of Models and Meta Models?
Semantic Consistency & Completeness Using Ontology: Thesaurus + Inference Rules
Semantic Concept: Common Words where everybody can have the same and unique interpretation in a domain
Structure (Concepts and Relationships) : Thesaurus mechanisms to infer/calculate the semantic
properties on the ontology
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Domain Ontology: Example
Close<<Function>>
Open<<Function>>
require
Move<<Function>>
require
Door<<Object>>
applyapply
Stop<<Function>>
require
require
Lift<<Object>>
apply apply
Emergency Button<<Object>>
Specifying semantics of a specific area, e.g. Lift Control System, Insurance Business, etc.
Using Class Diagram Word = Class Relationship = Association
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Basic Idea
C D
A
E
B
cause
Model
Domain Ontology (thesaurus part only)
aaa
bbb
semantic mapping
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Basic Idea
C D
A
E
B
cause
Model
Domain Ontology (thesaurus part only)
aaa
bbb
semantic mapping
"A causes C" on the DomainOntology
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Basic Idea
C D
A
E
B
cause
Model
Domain Ontology (thesaurus part only)
aaa
cccbbb
semantic mapping
"aaa causes ccc" for semantic consistency
Adding ccc
Finding SemanticInconsistency andIncompleteness
Inferenceon the structureof the ontology
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Model v.s. Domain Ontology
Lift DoorScheduler
1: request2: up
3: arrived4: open
Model
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Model v.s. Domain Ontology
Door<<Object>>
Lift<<Object>>
Doors<<Class>>
Lifts<<Class>>
Close<<Event>>
Move<<Event>>
Stop<<Event>>
Open<<Event>>
next
next
next
next nextnext
Lift DoorScheduler
1: request2: up
3: arrived4: open
Model Domain Ontology
next : Temporal order of execution
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Model v.s. Domain Ontology
Door<<Object>>
Lift<<Object>>
Doors<<Class>>
Lifts<<Class>>
Close<<Event>>
Move<<Event>>
Stop<<Event>>
Open<<Event>>
next
next
next
next nextnext
Lift DoorScheduler
1: request2: up
3: arrived4: open
Model Domain Ontologysemantic mapping
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Model v.s. Domain Ontology
Door<<Object>>
Lift<<Object>>
Doors<<Class>>
Lifts<<Class>>
Close<<Event>>
Move<<Event>>
Stop<<Event>>
Open<<Event>>
next
next
next
next nextnext
Lift DoorScheduler
1: request2: up
3: arrived4: open
Model Domain Ontologysemantic mapping
?
Inference of causality Model: up causes arrived causes open Ontology: Move next Stop next Open
Stop missing!
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Meta Model v.s. Meta Model Ontology
Object
Message
sendreceive
Data
carry
Meta Model ofSequence Diagram
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Meta Model v.s. Meta Model Ontology
manipulate
Object
Message
sendreceive
AssociationClass source
destination
Function Dataconsume
produce
State
describe
Object
abstraction
describedescribe
Event
associate
change-from
change-to
participate
next
Data
carry
Meta Model ofSequence Diagram
Meta Model Ontology
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Meta Model v.s. Meta Model Ontology
manipulate
Object
Message
sendreceive
AssociationClass source
destination
Function Dataconsume
produce
State
describe
Object
abstraction
describedescribe
Event
associate
change-from
change-to
participate
next
Data
carry
Meta Model ofSequence Diagram
Meta Model Ontologysemantic mapping
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Meta Model v.s. Meta Model Ontology
manipulate
Object
Message
sendreceive
AssociationClass source
destination
Function Dataconsume
produce
State
describe
Object
abstraction
describedescribe
Event
associate
change-from
change-to
participate
next
Data
carry
Meta Model ofSequence Diagram
Meta Model Ontologysemantic mapping
?
Meta Model: Message carry Data, Message ? MessageOntology: Event associate Data, Event next Event
Next missing
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Meta Model v.s. Meta Model Ontology
manipulate
Object
Message
sendreceive
cause
AssociationClass source
destination
Function Dataconsume
produce
State
describe
Object
abstraction
describedescribe
Event
associate
change-from
change-to
participate
next
Data
carry
Meta Model ofSequence Diagram
Meta Model Ontology
Adding "cause"
Semantic Quality = 6/7
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Syntactic Domain Semantic Domain
semantic mapping
semantic mapping
instantiation instantiation
Meta Model
Model DomainOntology
Meta Model Ontology Inference Rule#2
Inference Rule#1
M1 Layer(in MOF)
M2 Layer(in MOF)
Relationships
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Summary & Future Work Providing Semantics for Models and Meta Models using Ontologi
es How faithfully a model and a meta model reflect their ontologi
es? Deviations from Ontologies represent semantic inconsistency
and incompleteness Future Application
Semantic Quality Measurement for Models and Meta Models (DSL)
Elaborating a Meta Model Ontology Reasoning Properties on Models and Meta Models Automated Tool for Reasoning, Calculating, ...