Book: Model Driven Architecture and Ontology Development

Table of Contents

Part I Basics

1. Knowledge Representation. 3

1.1 Basic Concepts. 4

1.2 Cognitive Science. 7

1.3 Types of Human Knowledge. 11

1.4 Knowledge Representation Techniques. 14

1.4.1 Object–Attribute–Value Triplets. 15

1.4.2 Uncertain Facts. 15

1.4.3 Fuzzy Facts. 16

1.4.4 Rules. 17

1.4.5 Semantic networks. 18

1.4.6 Frames. 19

1.5 Knowledge Representation Languages. 19

1.5.1 Logic-Based Representation Languages. 20

1.5.2 Frame-Based Representation Languages. 27

1.5.3 Rule-Based Representation Languages. 29

1.5.4 Visual Languages for Knowledge Representation. 32

1.5.5 Natural Languages and Knowledge Representation. 35

1.6 Knowledge Engineering. 36

1.7 Open Knowledge Base Connectivity (OKBC) 39

1.8 The Knowledge Level 41

2. Ontologies. 45

2.1 Basic Concepts. 46

2.1.1 Definitions. 46

2.1.2 What Do Ontologies Look Like?. 48

2.1.3 Why Ontologies?. 50

2.1.4 Key Application Areas. 55

2.1.5 Examples. 57

2.2 Ontological Engineering. 58

2.2.1 Ontology Development Tools. 58

2.2.2 Ontology Development Methodologies. 65

2.3 Applications. 69

2.3.1 Magpie. 69

2.3.2 Briefing Associate. 70

2.3.3 Quickstep and Foxtrot 71

2.4 Advanced Topics. 72

2.4.1 Metadata, Metamodeling, and Ontologies. 72

2.4.2 Standard Upper Ontology. 74

2.4.3 Ontological Level 76

3. The Semantic Web. 79

3.1 Rationale. 80

3.2 Semantic Web Languages. 81

3.2.1 XML and XML Schema. 81

3.2.2 RDF and RDF Schema. 84

3.2.3 DAML+OIL. 87

3.2.4 OWL. 90

3.2.5 SPARQL. 92

3.3 The Role of Ontologies. 95

3.4 Semantic Markup. 96

3.5 Semantic Web Services. 100

3.6 Open Issues. 104

3.7 Quotations. 107

4. The Model Driven Architecture (MDA) 109

4.1 Models and Metamodels. 109

4.2 Platform-Independent Models. 110

4.3 Four-Layer Architecture. 112

4.4 The Meta-Object Facility. 114

4.5 Specific MDA Metamodels. 117

4.5.1 Unified Modeling Language. 117

4.5.2 Common Warehouse Metamodel (CWM) 118

4.5.3 Ontology Definition Metamodel 119

4.6 UML Profiles. 120

4.6.1 Examples of UML Profiles. 121

4.7 An XML for Sharing MDA Artifacts. 123

4.8 The Need for Modeling Spaces. 126

5. Modeling Spaces. 127

5.1 Modeling the Real World. 128

5.2 The Real World, Models, and Metamodels. 129

5.3 The Essentials of Modeling Spaces. 131

5.4 Modeling Spaces Illuminated. 134

5.5 A Touch of RDF(S) and MOF Modeling Spaces. 137

5.6 A Touch of the Semantic Web and MDA Technical Spaces. 139

5.7 Instead of Conclusions

141

Part II The Model Driven Architecture and Ontologies

6. Software Engineering Approaches to Ontology Development 145

6.1 A Brief History of Ontology Modeling. 145

6.1.1 Networked Knowledge Representation and Exchange Using UML and RDF. 145

6.1.2 Extending the Unified Modeling Language for Ontology Development 150

6.1.3 The Unified Ontology Language. 155

6.1.4 UML for the Semantic Web:

Transformation-Based Approach. 156

6.1.5 The AIFB OWL DL Metamodel 159

6.1.6 The GOOD OLD AI ODM Proposal 160

6.2 Ontology Development Tools Based on Software Engineering Techniques. 160

6.2.1 Protégé. 161

6.2.2 DUET (DAML UML Enhanced Tool) 164

6.2.3 An Ontology Tool for

IBM Rational Rose UML Models. 165

6.2.4 Visual Ontology Modeler (VOM) 167

6.3 Summary of Relations Between UML and Ontologies. 168

6.3.1 Summary of Approaches and Tools for Software Engineering-Based Ontology Development 169

6.3.2 Summary of Differences Between UML and Ontology Languages. 169

6.3.3 Future Development 172

7. The MDA-Based Ontology Infrastructure. 173

7.1 Motivation. 173

7.2 Overview.. 174

7.3 Bridging RDF(S) and MOF. 176

7.4 Design Rationale for the Ontology UML Profile. 178

8. The Ontology Definition Metamodel (ODM) 181

8.1 ODM Metamodels. 181

8.2 A Few Issues Regarding the Revised Joint Submission. 183

8.3 The Resource Description Framework Schema (RDFS) metamodel 184

8.4 The Web Ontology Language (OWL) Metamodel 190

9. The Ontology UML Profile. 201

9.1 Classes and Individuals in Ontologies. 201

9.2 Properties of Ontologies. 204

9.3 Statements. 206

9.4 Different Versions of the Ontology UML Profile. 207

10. Mappings of MDA-Based Languages and Ontologies. 211

10.1 Relations Between Modeling Spaces. 211

10.2 Transformations Between Modeling Spaces. 214

10.3 Example of an Implementation: an XSLT-Based Approach. 217

10.3.1 Implementation Details. 218

10.3.2 Transformation Example. 219

10.3.3 Practical Experience. 222

10.3.4 Discussion

. 225

Part III Applications

11. Using UML Tools for Ontology Modeling. 229

11.1 MagicDraw.. 230

11.1.1 Starting with MagicDraw.. 230

11.1.2 Things You Should Know when Working with UML Profiles. 232

11.1.3 Creating a New Ontology. 234

11.1.4 Working with Ontology Classes. 237

11.1.5 Working with Ontology Properties. 240

11.1.6 Working with Individuals. 244

11.1.7 Working with Statements. 246

11.2 Poseidon for UML. 247

11.2.1 Modeling Ontology Classes in Poseidon. 249

11.2.2 Modeling Ontology Individuals and Statements in Poseidon. 250

11.3 Sharing UML Models Between UML tools and Protégé Using the UML Back End. 251

12. An MDA Based Ontology Platform: AIR.. 255

12.1 Motivation. 255

12.2 The Basic Idea. 256

12.3 Metamodel – the Conceptual Building Block of AIR.. 258

12.4 The AIR Metadata Repository. 259

12.5 The AIR Workbench. 262

12.6 The Role of XML Technologies. 264

12.7 Possibilities. 265

13. Examples of Ontology. 267

13.1 Petri Net Ontology. 267

13.1.1 Organization of the Petri Net Ontology. 269

13.1.2 The Core Petri Net Ontology in the Ontology UML Profile. 272

13.1.3 Example of an Extension: Upgraded Petri Nets. 275

13.2 Educational Ontologies. 278

13.2.1 Conceptual Solution. 279

13.2.2 Mapping the Conceptual Model to Ontologies. 281

References. 291

Index 305

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Book: Model Driven Architecture and Ontology Development