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Model Driven Engineering and Ontology Development (eBook)

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2009 | 2nd ed. 2009
XXI, 378 Seiten
Springer Berlin (Verlag)
978-3-642-00282-3 (ISBN)

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Model Driven Engineering and Ontology Development - Dragan Gaševic, Dragan Djuric, Vladan Devedžic
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Defining a formal domain ontology is considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artefacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are unfamiliar with these. This book fills this gap by covering the subject of MDA application for ontology development on the Semantic Web. The writing is technical yet clear, and is illustrated with examples. The book is supported by a website.



Dragan Gasevic is an assistant professor in the School of Computing and Information Systems at Athabasca University in Canada and an Adjunct Professor at Simon Fraser University in Canada. He is a recipient of Alberta Ingenuity's 2008 New Faculty Award. His research interests include semantic technologies, software language engineering, and learning technologies.

Dragan Djuric is an assistant professor of computer science at the Department of Software Engineering, FON - School of Business Administration, University of Belgrade, Serbia. He is also a memeber of the GOOD OLD AI research group. His main research interests include software engineering, web engineering, intelligent systems, knowledge representation, ontologies and the Semantic Web.

Vladan Devedzic is a professor of computer science at the Department of Software Engineering, FON - School of Business Administration, University of Belgrade, Serbia. He is also the head of the GOOD OLD AI research group. His main research interests include software engineering, intelligent systems, knowledge representation, ontologies, Semantic Web, intelligent reasoning, and applications of artificial intelligence techniques to education and healthcare.

Dragan Gasevic is an assistant professor in the School of Computing and Information Systems at Athabasca University in Canada and an Adjunct Professor at Simon Fraser University in Canada. He is a recipient of Alberta Ingenuity's 2008 New Faculty Award. His research interests include semantic technologies, software language engineering, and learning technologies. Dragan Djuric is an assistant professor of computer science at the Department of Software Engineering, FON - School of Business Administration, University of Belgrade, Serbia. He is also a memeber of the GOOD OLD AI research group. His main research interests include software engineering, web engineering, intelligent systems, knowledge representation, ontologies and the Semantic Web. Vladan Devedzic is a professor of computer science at the Department of Software Engineering, FON - School of Business Administration, University of Belgrade, Serbia. He is also the head of the GOOD OLD AI research group. His main research interests include software engineering, intelligent systems, knowledge representation, ontologies, Semantic Web, intelligent reasoning, and applications of artificial intelligence techniques to education and healthcare.

Foreword to the 2nd Edition 6
Foreword to the 1st Edition 8
Preface 10
What Happened Since the First Edition? 11
Second Edition 12
Organization, Structure, and Changes 13
Acknowledgments 14
Contents 16
Part I Basics 21
1 Knowledge Representation 22
1.1 Basic Concepts 23
1.2 Cognitive Science 26
1.3 Types of Human Knowledge 30
1.4 Knowledge Representation Techniques 33
1.5 Knowledge Representation Languages 38
1.6 Knowledge Engineering 55
1.7 Open Knowledge Base Connectivity (OKBC) 57
1.8 The Knowledge Level 60
2 Ontologies 63
2.1 Basic Concepts 64
2.2 Ontological Engineering 77
2.3 Applications 90
2.4 Advanced Topics 94
3 The Semantic Web 99
3.1 Rationale 100
3.2 Semantic Web Languages 101
3.3 The Role of Ontologies 123
3.4 Semantic Markup 125
3.5 Development Frameworks 128
3.6 Reasoning 131
3.7 Semantic Web Services 134
3.8 Open Issues 139
3.9 Quotations 142
4 Model Driven Engineering 143
4.1 Models and Metamodels 143
4.2 Types of Software Models 150
4.3 The Model Driven Architecture 151
4.4 Metamodeling Languages 153
4.5 Standardized MDA Metamodels 158
4.6 UML Profiles 161
4.7 Model Transformations 165
4.8 Object Constraint Language 169
4.9 An XML for Sharing MDA Artifacts 170
4.10 The Need for Modeling Spaces 172
5 Modeling Spaces 174
5.1 Modeling the Real World 175
5.2 The Real World, Models, and Metamodels 176
5.3 The Essentials of Modeling Spaces 178
5.4 Modeling Spaces Illuminated 181
5.5 Modeling Spaces Applied 184
5.6 A Touch of RDF(S) and MOF Modeling Spaces 186
5.7 A Touch of the Semantic Web and MDA Technical Spaces 188
5.8 Instead of Conclusions 190
Part II Model Driven Engineering and Ontologies 191
6 Software Engineering Approaches to Ontology Development 192
6.1 A Brief History of Ontology Modeling 192
6.2 Ontology Development Tools Based on Software Engineering Techniques 208
6.3 Summary of Relations Between UML and Ontologies 216
7 The MDA-Based Ontology Infrastructure 221
7.1 Motivation 221
7.2 Overview 222
7.3 Bridging RDF(S) and MOF 225
7.4 Design Rationale for the Ontology UML Profile 227
8 The Ontology Definition Metamodel (ODM) 229
8.1 ODM Metamodels 229
8.2 A Few Objections to the ODM Specification 231
8.3 The Resource Description Framework Schema (RDFS) Metamodel 233
8.4 The Web Ontology Language (OWL) Metamodel 239
9 The Ontology UML Profile 248
9.1 Classes and Individuals in Ontologies 248
9.2 Properties of Ontologies 251
9.3 Statements 253
9.4 Different Versions of the Ontology UML Profile 254
10 Mappings of MDA-Based Languages and Ontologies 257
10.1 Relations Between Modeling Spaces 257
10.2 Transformations Between Modeling Spaces 260
10.3 Example of an Implementation: An XSLT-Based Approach 264
Part III Applications 274
11 Modeling Tools and Ontology Development 275
11.1 MagicDraw 276
11.2 Poseidon for UML 293
11.3 Sharing Models Between UML Tools and Protégé 297
11.4 Atlas Transformation Language 301
12 An MDA Based Ontology Platform: AIR 308
12.1 Motivation 308
12.2 The Basic Idea 309
12.3 Metamodel—the Conceptual Building Block of AIR 311
12.4 The AIR Metadata Repository 312
12.5 The AIR Workbench 315
12.6 The Role of XML Technologies 317
12.7 Possibilities 318
13 Examples of Ontology 319
13.1 Petri Net Ontology 319
13.2 Educational Ontologies 330
14 Beyond the Ontology Definition Metamodel: Applications 343
14.1 Integrated Ontology Development Toolkit 343
14.2 TwoUse: UML and OWL Modeling 346
14.3 Model Driven Engineering of Ontology Reasoners 349
14.4 Model Driven Engineering and Semantic Web Rules 353
References 359
Index 378

Erscheint lt. Verlag 12.6.2009
Vorwort Bran V. Selic, Jean Bézivin
Zusatzinfo XXI, 378 p. 183 illus.
Verlagsort Berlin
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Software Entwicklung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Informatik Web / Internet
Schlagworte Artificial Intelligence • DAML • Knowledge • Knowledge Representation • MDA • Modeling • ODM • Ontologie • Ontology Definition Metamodel • OWL • RDF • semantic web • Software engineering • UML • XML
ISBN-10 3-642-00282-X / 364200282X
ISBN-13 978-3-642-00282-3 / 9783642002823
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