Applications of Description Logics IJCAR 2001: Description Logics - - PowerPoint PPT Presentation

▶
applications of description logics
SMART_READER_LITE
LIVE PREVIEW

Applications of Description Logics IJCAR 2001: Description Logics - - PowerPoint PPT Presentation

Nov 11, 2022 6 likes •767 views

Applications of Description Logics IJCAR 2001: Description Logics tutorial p.1/9 Application Areas I IJCAR 2001: Description Logics tutorial p.2/9 Application Areas I Terminological KR and Ontologies IJCAR 2001: Description Logics

slide-1
SLIDE 1

Applications of Description Logics

IJCAR 2001: Description Logics tutorial – p.1/9

slide-2
SLIDE 2

Application Areas I

IJCAR 2001: Description Logics tutorial – p.2/9

slide-3
SLIDE 3

Application Areas I

☞ Terminological KR and Ontologies

IJCAR 2001: Description Logics tutorial – p.2/9

slide-4
SLIDE 4

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)

IJCAR 2001: Description Logics tutorial – p.2/9

slide-5
SLIDE 5

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

IJCAR 2001: Description Logics tutorial – p.2/9

slide-6
SLIDE 6

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

IJCAR 2001: Description Logics tutorial – p.2/9

slide-7
SLIDE 7

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

IJCAR 2001: Description Logics tutorial – p.2/9

slide-8
SLIDE 8

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

IJCAR 2001: Description Logics tutorial – p.2/9

slide-9
SLIDE 9

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

IJCAR 2001: Description Logics tutorial – p.2/9

slide-10
SLIDE 10

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

  • Requirement for web based ontology language

IJCAR 2001: Description Logics tutorial – p.2/9

slide-11
SLIDE 11

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

  • Requirement for web based ontology language

➙ Well defined semantics

IJCAR 2001: Description Logics tutorial – p.2/9

slide-12
SLIDE 12

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

  • Requirement for web based ontology language

➙ Well defined semantics ➙ Builds on existing Web standards (XML, RDF, RDFS)

IJCAR 2001: Description Logics tutorial – p.2/9

slide-13
SLIDE 13

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

  • Requirement for web based ontology language

➙ Well defined semantics ➙ Builds on existing Web standards (XML, RDF, RDFS)

  • Resulting language (DAML+OIL) is based on a DL (SHIQ)

IJCAR 2001: Description Logics tutorial – p.2/9

slide-14
SLIDE 14

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

  • Requirement for web based ontology language

➙ Well defined semantics ➙ Builds on existing Web standards (XML, RDF, RDFS)

  • Resulting language (DAML+OIL) is based on a DL (SHIQ)
  • DL reasoning can be used to, e.g.,

IJCAR 2001: Description Logics tutorial – p.2/9

slide-15
SLIDE 15

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

  • Requirement for web based ontology language

➙ Well defined semantics ➙ Builds on existing Web standards (XML, RDF, RDFS)

  • Resulting language (DAML+OIL) is based on a DL (SHIQ)
  • DL reasoning can be used to, e.g.,

➙ Support ontology design and maintenance

IJCAR 2001: Description Logics tutorial – p.2/9

slide-16
SLIDE 16

Application Areas I

☞ Terminological KR and Ontologies

  • DLs initially designed for terminological KR (and reasoning)
  • Natural to use DLs to build and maintain ontologies

☞ Semantic Web

  • Semantic markup will be added to web resources

➙ Aim is “machine understandability”

  • Markup will use Ontologies to provide common terms of

reference with clear semantics

  • Requirement for web based ontology language

➙ Well defined semantics ➙ Builds on existing Web standards (XML, RDF, RDFS)

  • Resulting language (DAML+OIL) is based on a DL (SHIQ)
  • DL reasoning can be used to, e.g.,

➙ Support ontology design and maintenance ➙ Classify resources w.r.t. ontologies

IJCAR 2001: Description Logics tutorial – p.2/9

slide-17
SLIDE 17

Application Areas II

IJCAR 2001: Description Logics tutorial – p.3/9

slide-18
SLIDE 18

Application Areas II

☞ Configuration

IJCAR 2001: Description Logics tutorial – p.3/9

slide-19
SLIDE 19

Application Areas II

☞ Configuration

  • Classic system used to configure telecoms equipment

IJCAR 2001: Description Logics tutorial – p.3/9

slide-20
SLIDE 20

Application Areas II

☞ Configuration

  • Classic system used to configure telecoms equipment
  • Characteristics of components described in DL KB

IJCAR 2001: Description Logics tutorial – p.3/9

slide-21
SLIDE 21

Application Areas II

☞ Configuration

  • Classic system used to configure telecoms equipment
  • Characteristics of components described in DL KB
  • Reasoner checks validity (and price) of configurations

IJCAR 2001: Description Logics tutorial – p.3/9

slide-22
SLIDE 22

Application Areas II

☞ Configuration

  • Classic system used to configure telecoms equipment
  • Characteristics of components described in DL KB
  • Reasoner checks validity (and price) of configurations

☞ Software information systems

IJCAR 2001: Description Logics tutorial – p.3/9

slide-23
SLIDE 23

Application Areas II

☞ Configuration

  • Classic system used to configure telecoms equipment
  • Characteristics of components described in DL KB
  • Reasoner checks validity (and price) of configurations

☞ Software information systems

  • LaSSIE system used DL KB for flexible software documentation

and query answering

IJCAR 2001: Description Logics tutorial – p.3/9

slide-24
SLIDE 24

Application Areas II

☞ Configuration

  • Classic system used to configure telecoms equipment
  • Characteristics of components described in DL KB
  • Reasoner checks validity (and price) of configurations

☞ Software information systems

  • LaSSIE system used DL KB for flexible software documentation

and query answering ☞ Database applications

IJCAR 2001: Description Logics tutorial – p.3/9

slide-25
SLIDE 25

Application Areas II

☞ Configuration

  • Classic system used to configure telecoms equipment
  • Characteristics of components described in DL KB
  • Reasoner checks validity (and price) of configurations

☞ Software information systems

  • LaSSIE system used DL KB for flexible software documentation

and query answering ☞ Database applications ☞ . . .

IJCAR 2001: Description Logics tutorial – p.3/9

slide-26
SLIDE 26

Database Schema and Query Reasoning

IJCAR 2001: Description Logics tutorial – p.4/9

slide-27
SLIDE 27

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER)

IJCAR 2001: Description Logics tutorial – p.4/9

slide-28
SLIDE 28

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER)

IJCAR 2001: Description Logics tutorial – p.4/9

slide-29
SLIDE 29

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

IJCAR 2001: Description Logics tutorial – p.4/9

slide-30
SLIDE 30

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

  • Can reason about query containment w.r.t. schema

IJCAR 2001: Description Logics tutorial – p.4/9

slide-31
SLIDE 31

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

  • Can reason about query containment w.r.t. schema

☞ DL reasoning can be used to support

IJCAR 2001: Description Logics tutorial – p.4/9

slide-32
SLIDE 32

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

  • Can reason about query containment w.r.t. schema

☞ DL reasoning can be used to support

  • Schema design, evolution and query optimisation

IJCAR 2001: Description Logics tutorial – p.4/9

slide-33
SLIDE 33

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

  • Can reason about query containment w.r.t. schema

☞ DL reasoning can be used to support

  • Schema design, evolution and query optimisation
  • Source integration in heterogeneous databases/data

warehouses

IJCAR 2001: Description Logics tutorial – p.4/9

slide-34
SLIDE 34

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

  • Can reason about query containment w.r.t. schema

☞ DL reasoning can be used to support

  • Schema design, evolution and query optimisation
  • Source integration in heterogeneous databases/data

warehouses

  • Conceptual modelling of multidimensional aggregation

IJCAR 2001: Description Logics tutorial – p.4/9

slide-35
SLIDE 35

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

  • Can reason about query containment w.r.t. schema

☞ DL reasoning can be used to support

  • Schema design, evolution and query optimisation
  • Source integration in heterogeneous databases/data

warehouses

  • Conceptual modelling of multidimensional aggregation

☞ E.g., I.COM Intelligent Conceptual Modelling tool (Enrico Franconi)

IJCAR 2001: Description Logics tutorial – p.4/9

slide-36
SLIDE 36

Database Schema and Query Reasoning

☞ DLR (n-ary DL) can capture semantics of many conceptual modelling methodologies (e.g., EER) ☞ Satisfiability preserving mapping to SHIQ allows use of DL reasoners (e.g., FaCT, RACER) ☞ DL Abox can also capture semantics of conjunctive queries

  • Can reason about query containment w.r.t. schema

☞ DL reasoning can be used to support

  • Schema design, evolution and query optimisation
  • Source integration in heterogeneous databases/data

warehouses

  • Conceptual modelling of multidimensional aggregation

☞ E.g., I.COM Intelligent Conceptual Modelling tool (Enrico Franconi)

  • Uses FaCT system to provide reasoning support for EER

IJCAR 2001: Description Logics tutorial – p.4/9

slide-37
SLIDE 37

I.COM Demo

IJCAR 2001: Description Logics tutorial – p.5/9

slide-38
SLIDE 38

Terminological KR and Ontologies

IJCAR 2001: Description Logics tutorial – p.6/9

slide-39
SLIDE 39

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project

IJCAR 2001: Description Logics tutorial – p.6/9

slide-40
SLIDE 40

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies

IJCAR 2001: Description Logics tutorial – p.6/9

slide-41
SLIDE 41

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

IJCAR 2001: Description Logics tutorial – p.6/9

slide-42
SLIDE 42

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected

IJCAR 2001: Description Logics tutorial – p.6/9

slide-43
SLIDE 43

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

IJCAR 2001: Description Logics tutorial – p.6/9

slide-44
SLIDE 44

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

IJCAR 2001: Description Logics tutorial – p.6/9

slide-45
SLIDE 45

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)

IJCAR 2001: Description Logics tutorial – p.6/9

slide-46
SLIDE 46

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)
  • Use DL classifier to build taxonomy

IJCAR 2001: Description Logics tutorial – p.6/9

slide-47
SLIDE 47

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)
  • Use DL classifier to build taxonomy

☞ Needed expressive DL and efficient reasoning

IJCAR 2001: Description Logics tutorial – p.6/9

slide-48
SLIDE 48

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)
  • Use DL classifier to build taxonomy

☞ Needed expressive DL and efficient reasoning

  • Descriptions use transitive/inverse roles, GCIs etc.

IJCAR 2001: Description Logics tutorial – p.6/9

slide-49
SLIDE 49

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)
  • Use DL classifier to build taxonomy

☞ Needed expressive DL and efficient reasoning

  • Descriptions use transitive/inverse roles, GCIs etc.
  • Very large KBs (tens of thousands of concepts)

IJCAR 2001: Description Logics tutorial – p.6/9

slide-50
SLIDE 50

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)
  • Use DL classifier to build taxonomy

☞ Needed expressive DL and efficient reasoning

  • Descriptions use transitive/inverse roles, GCIs etc.
  • Very large KBs (tens of thousands of concepts)

➙ Even prototype KB is very large (≈3,000 concepts)

IJCAR 2001: Description Logics tutorial – p.6/9

slide-51
SLIDE 51

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)
  • Use DL classifier to build taxonomy

☞ Needed expressive DL and efficient reasoning

  • Descriptions use transitive/inverse roles, GCIs etc.
  • Very large KBs (tens of thousands of concepts)

➙ Even prototype KB is very large (≈3,000 concepts) ➙ Existing (incomplete) classifier took ≈24 hours to classify KB

IJCAR 2001: Description Logics tutorial – p.6/9

slide-52
SLIDE 52

Terminological KR and Ontologies

Initial motivation for work on FaCT system was Galen project ☞ General requirement for medical terminologies ☞ Static lists/taxonomies difficult to build and maintain

  • Need to be very large and highly interconnected
  • Inevitably contain many errors and omissions

☞ Galen project aims to replace static hierarchy with DL

  • Describe concepts (e.g., spiral fracture of left femur)
  • Use DL classifier to build taxonomy

☞ Needed expressive DL and efficient reasoning

  • Descriptions use transitive/inverse roles, GCIs etc.
  • Very large KBs (tens of thousands of concepts)

➙ Even prototype KB is very large (≈3,000 concepts) ➙ Existing (incomplete) classifier took ≈24 hours to classify KB ➙ FaCT system (sound and complete) takes ≈60 seconds

IJCAR 2001: Description Logics tutorial – p.6/9

slide-53
SLIDE 53

Reasoning Support for Ontology Design

IJCAR 2001: Description Logics tutorial – p.7/9

slide-54
SLIDE 54

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance

IJCAR 2001: Description Logics tutorial – p.7/9

slide-55
SLIDE 55

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

IJCAR 2001: Description Logics tutorial – p.7/9

slide-56
SLIDE 56

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)

IJCAR 2001: Description Logics tutorial – p.7/9

slide-57
SLIDE 57

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language

IJCAR 2001: Description Logics tutorial – p.7/9

slide-58
SLIDE 58

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions

IJCAR 2001: Description Logics tutorial – p.7/9

slide-59
SLIDE 59

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting

IJCAR 2001: Description Logics tutorial – p.7/9

slide-60
SLIDE 60

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting ➙ Properties for slot relations (transitive, functional etc.)

IJCAR 2001: Description Logics tutorial – p.7/9

slide-61
SLIDE 61

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting ➙ Properties for slot relations (transitive, functional etc.) ➙ General axioms

IJCAR 2001: Description Logics tutorial – p.7/9

slide-62
SLIDE 62

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting ➙ Properties for slot relations (transitive, functional etc.) ➙ General axioms ☞ Reasoning support for OilEd provided by FaCT system

IJCAR 2001: Description Logics tutorial – p.7/9

slide-63
SLIDE 63

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting ➙ Properties for slot relations (transitive, functional etc.) ➙ General axioms ☞ Reasoning support for OilEd provided by FaCT system

  • Frame representation translated into SHIQ

IJCAR 2001: Description Logics tutorial – p.7/9

slide-64
SLIDE 64

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting ➙ Properties for slot relations (transitive, functional etc.) ➙ General axioms ☞ Reasoning support for OilEd provided by FaCT system

  • Frame representation translated into SHIQ
  • Communicates with FaCT via CORBA interface

IJCAR 2001: Description Logics tutorial – p.7/9

slide-65
SLIDE 65

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting ➙ Properties for slot relations (transitive, functional etc.) ➙ General axioms ☞ Reasoning support for OilEd provided by FaCT system

  • Frame representation translated into SHIQ
  • Communicates with FaCT via CORBA interface
  • Indicates inconsistencies and implicit subsumptions

IJCAR 2001: Description Logics tutorial – p.7/9

slide-66
SLIDE 66

Reasoning Support for Ontology Design

☞ DL reasoner can be used to support design and maintenance ☞ Example is OilEd ontology editor (for DAML+OIL)

  • Frame based interface (like Protegé, OntoEdit, etc.)
  • Extended to clarify semantics and capture whole DAML+OIL

language ➙ Slots explicitly existential or value restrictions ➙ Boolean connectives and nesting ➙ Properties for slot relations (transitive, functional etc.) ➙ General axioms ☞ Reasoning support for OilEd provided by FaCT system

  • Frame representation translated into SHIQ
  • Communicates with FaCT via CORBA interface
  • Indicates inconsistencies and implicit subsumptions
  • Can make implicit subsumptions explicit in KB

IJCAR 2001: Description Logics tutorial – p.7/9

slide-67
SLIDE 67

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology

IJCAR 2001: Description Logics tutorial – p.8/9

slide-68
SLIDE 68

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc.

IJCAR 2001: Description Logics tutorial – p.8/9

slide-69
SLIDE 69

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc. Smoking ⊑ ∃causes.Cancer plus Cancer ⊑ ∃causes.Death ⇒ Cancer ⊑ FatalThing

IJCAR 2001: Description Logics tutorial – p.8/9

slide-70
SLIDE 70

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc. Smoking ⊑ ∃causes.Cancer plus Cancer ⊑ ∃causes.Death ⇒ Cancer ⊑ FatalThing ☞ GCIs represent additional non-definitional knowledge

IJCAR 2001: Description Logics tutorial – p.8/9

slide-71
SLIDE 71

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc. Smoking ⊑ ∃causes.Cancer plus Cancer ⊑ ∃causes.Death ⇒ Cancer ⊑ FatalThing ☞ GCIs represent additional non-definitional knowledge Stomach-Ulcer . = Ulcer ⊓ ∃hasLocation.Stomach plus Stomach-Ulcer ⊑ ∃hasLocation.Lining-Of-Stomach ⇒ Ulcer ⊓ ∃hasLocation.Stomach ⊑ OrganLiningLesion

IJCAR 2001: Description Logics tutorial – p.8/9

slide-72
SLIDE 72

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc. Smoking ⊑ ∃causes.Cancer plus Cancer ⊑ ∃causes.Death ⇒ Cancer ⊑ FatalThing ☞ GCIs represent additional non-definitional knowledge Stomach-Ulcer . = Ulcer ⊓ ∃hasLocation.Stomach plus Stomach-Ulcer ⊑ ∃hasLocation.Lining-Of-Stomach ⇒ Ulcer ⊓ ∃hasLocation.Stomach ⊑ OrganLiningLesion ☞ Inverse roles capture e.g. causes/causedBy relationship

IJCAR 2001: Description Logics tutorial – p.8/9

slide-73
SLIDE 73

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc. Smoking ⊑ ∃causes.Cancer plus Cancer ⊑ ∃causes.Death ⇒ Cancer ⊑ FatalThing ☞ GCIs represent additional non-definitional knowledge Stomach-Ulcer . = Ulcer ⊓ ∃hasLocation.Stomach plus Stomach-Ulcer ⊑ ∃hasLocation.Lining-Of-Stomach ⇒ Ulcer ⊓ ∃hasLocation.Stomach ⊑ OrganLiningLesion ☞ Inverse roles capture e.g. causes/causedBy relationship Death ⊓ ∃causedBy.Smoking ⊑ PrematureDeath ⇒ Smoking ⊑ CauseOfPrematureDeath

IJCAR 2001: Description Logics tutorial – p.8/9

slide-74
SLIDE 74

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc. Smoking ⊑ ∃causes.Cancer plus Cancer ⊑ ∃causes.Death ⇒ Cancer ⊑ FatalThing ☞ GCIs represent additional non-definitional knowledge Stomach-Ulcer . = Ulcer ⊓ ∃hasLocation.Stomach plus Stomach-Ulcer ⊑ ∃hasLocation.Lining-Of-Stomach ⇒ Ulcer ⊓ ∃hasLocation.Stomach ⊑ OrganLiningLesion ☞ Inverse roles capture e.g. causes/causedBy relationship Death ⊓ ∃causedBy.Smoking ⊑ PrematureDeath ⇒ Smoking ⊑ CauseOfPrematureDeath ☞ Cardinality restrictions add consistency constraints

IJCAR 2001: Description Logics tutorial – p.8/9

slide-75
SLIDE 75

DAML+OIL Medical Terminology Examples

E.g., DAML+OIL medical terminology ontology ☞ Transitive roles capture transitive partonomy, causality, etc. Smoking ⊑ ∃causes.Cancer plus Cancer ⊑ ∃causes.Death ⇒ Cancer ⊑ FatalThing ☞ GCIs represent additional non-definitional knowledge Stomach-Ulcer . = Ulcer ⊓ ∃hasLocation.Stomach plus Stomach-Ulcer ⊑ ∃hasLocation.Lining-Of-Stomach ⇒ Ulcer ⊓ ∃hasLocation.Stomach ⊑ OrganLiningLesion ☞ Inverse roles capture e.g. causes/causedBy relationship Death ⊓ ∃causedBy.Smoking ⊑ PrematureDeath ⇒ Smoking ⊑ CauseOfPrematureDeath ☞ Cardinality restrictions add consistency constraints BloodPressure ⊑ ∃hasValue.(High ⊔ Low) ⊓ 1hasValue plus High ⊑ ¬Low ⇒ HighLowBloodPressure ⊑ ⊥

IJCAR 2001: Description Logics tutorial – p.8/9

slide-76
SLIDE 76

OilEd Demo

IJCAR 2001: Description Logics tutorial – p.9/9