Model Driven Engineering and Ontology Development

By: Bran V. Selic (Foreword by), Dragan GaÅ¡evic, Dragan Djuric

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Hardcover | 18 May 2009 | Edition Number 2

At a Glance

Hardcover
402 Pages

Edition Type
Revised

Dimensions(cm)
25.4 x 15.88 x 2.54

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Defining a formal domain ontology is generally 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 largely unfamiliar with these.

Gasevic and his co-authors try to fill this gap by detailing how to use model-driven engineering for ontology development on the Semantic Web. Part I of their book describes existing technologies, tools, and standards like XML, RDF, OWL, MDA, and UML. Part II presents the first detailed description of OMG's new ODM (Ontology Definition Metamodel) initiative, a specification which is expected to be in the form of an OMG language like UML. Finally, Part III is dedicated to applications and practical aspects of developing ontologies using MDA-based languages.

For this second edition, the descriptions of the related standards (like MOF, ODM, OCL, and OWL) have been revised and updated; new chapters introducing the basic principles of model-driven engineering, recent research results on metamodeling Semantic Web rule languages, an introduction to the Atlas Transformation Language (ATL) and its tool support, and, last but not least, many new examples have been added.

Industry Reviews

From the reviews:

"The central theme of this book is the definition and application of ontologies for developing software systems. ... The presentation style is clear and accessible ... . This book provides adequate guidelines for enjoying the semantic Web's benefits, and warns of the potential dangers of its misuse. It is well written, innovative, and definitely recommended as a book to return to from time to time, to gather some fresh ideas and continue working on their implementation." (M. Ivanovi, Computing Reviews, January, 2007)

"The book is equally suited to those who merely want to be informed of the relevant technological landscape, to practitioners dealing with concrete problems, and to researchers seeking pointers to potentially fruitful areas of research. The writing is technical yet clear and accessible, illustrated throughout with useful and easily digestible examples." (from the Foreword by Bran Selic, IBM Rational Software, Canada)

"I do notknow another book that offers such a high quality insight into UML and ontologies" (Steffen Staab, U Koblenz, Germany)

"The authors offer not only high level conceptual presentations, but also implementation-level coverage of the presented technologies, and even hands-on guidance to their practical application." (Jean Bezivin, U Nantes, France)

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Non-Fiction Computing & I.T.Computer Programming & Software Development Software Engineering Computer Science Artificial Intelligence

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Paperback

Published: 19th October 2010

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Basics
Knowledge Representation	p. 3
Basic Concepts	p. 4
Cognitive Science	p. 7
Types of Human Knowledge	p. 11
Knowledge Representation Techniques	p. 14
Object-Attribute-Value Triplets	p. 15
Uncertain Facts	p. 15
Fuzzy Facts	p. 16
Rules	p. 16
Semantic Networks	p. 17
Frames	p. 18
Knowledge Representation Languages	p. 19
Logic-Based Representation Languages	p. 20
Frame-Based Representation Languages	p. 27
Rule-Based Representation Languages	p. 29
Visual Languages for Knowledge Representation	p. 32
Natural Languages and Knowledge Representation	p. 35
Knowledge Engineering	p. 36
Open Knowledge Base Connectivity (OKBC)	p. 38
The Knowledge Level	p. 41
Ontologies	p. 45
Basic Concepts	p. 46
Definitions	p. 46
What Do Ontologies Look Like?	p. 48
Why Ontologies?	p. 50
Key Application Areas	p. 55
Examples	p. 57
Ontological Engineering	p. 59
Ontology Development Tools	p. 59
Ontology Development Methodologies	p. 66
Applications	p. 72
Magpie	p. 73
Briefing Associate	p. 74
Quickstep and Foxtrot	p. 75
Advanced Topics	p. 76
Metadata, Metamodeling, and Ontologies	p. 76
Standard Upper Ontology	p. 77
Ontological Level	p. 80
The Semantic Web	p. 81
Rationale	p. 82
Semantic Web Languages	p. 83
XML and XML Schema	p. 85
RDF and RDF Schema	p. 87
DAML+OIL	p. 90
OWL	p. 93
SPARQL	p. 95
GRDDL	p. 98
RDFa	p. 100
SKOS	p. 103
The Role of Ontologies	p. 105
Semantic Markup	p. 107
Development Frameworks	p. 110
Reasoning	p. 113
Semantic Web Services	p. 116
Open Issues	p. 121
Quotations	p. 124
Model Driven Engineering	p. 125
Models and Metamodels	p. 125
Models in General	p. 126
Model-Driven Engineering Theory	p. 126
Types of Software Models	p. 132
The Model Driven Architecture	p. 133
Metamodeling Languages	p. 135
The Meta-Object Facility	p. 136
Ecore Metamodeling Language	p. 138
Standardized MDA Metamodels	p. 140
Unified Modeling Language	p. 140
Common Warehouse Metamodel (CWM)	p. 141
Ontology Definition Metamodel	p. 143
UML Profiles	p. 143
Basics of UML Profiles	p. 143
Examples of UML Profiles	p. 145
Model Transformations	p. 147
Definitions	p. 147
Classification of Model Transformation Languages	p. 148
Model Transformation Languages	p. 149
Model Transformation Tools and Implementations	p. 150
Object Constraint Language	p. 151
An XML for Sharing MDA Artifacts	p. 152
The Need for Modeling Spaces	p. 154
Modeling Spaces	p. 157
Modeling the Real World	p. 158
The Real World, Models, and Metamodels	p. 159
The Essentials of Modeling Spaces	p. 161
Modeling Spaces Illuminated	p. 164
Modeling Spaces Applied	p. 167
A Touch of RDF(S) and MOF Modeling Spaces	p. 169
A Touch of the Semantic Web and MDA Technical Spaces	p. 171
Instead of Conclusions	p. 173
Model Driven Engineering and Ontologies
Software Engineering Approaches to Ontology Development	p. 177
A Brief History of Ontology Modeling	p. 177
Networked Knowledge Representation and Exchange Using UML and RDF	p. 177
Extending the Unified Modeling Language for Ontology Development	p. 182
The Unified Ontology Language	p. 187
UML for the Semantic Web: Transformation-Based Approach	p. 188
The AIFB OWL DL Metamodel	p. 191
NeOn Metamodels for the Semantic Web	p. 192
The GOOD OLD AI ODM Proposal	p. 193
Ontology Development Tools Based on Software Engineering Techniques	p. 193
Protégé	p. 194
DUET (DAML UML Enhanced Tool)	p. 197
An Ontology Tool for IBM Rational Rose UML Models	p. 198
Visual Ontology Modeler (VOM)	p. 200
Summary of Relations Between UML and Ontologies	p. 201
Summary of Approaches and Tools for Software Engineering-Based Ontology Development	p. 202
Summary of Differences Between UML and Ontology Languages	p. 202
Future Development	p. 205
The MDA-Based Ontology Infrastructure	p. 207
Motivation	p. 207
Overview	p. 208
Bridging RDF(S) and MOF	p. 211
Design Rationale for the Ontology UML Profile	p. 213
The Ontology Definition Metamodel (ODM)	p. 215
ODM Metamodels	p. 215
A Few Objections to the ODM Specification	p. 217
The Resource Description Framework Schema (RDFS) Metamodel	p. 219
The Web Ontology Language (OWL) Metamodel	p. 225
The Ontology UML Profile	p. 235
Classes and Individuals in Ontologies	p. 235
Properties of Ontologies	p. 238
Statements	p. 240
Different Versions of the Ontology UML Profile	p. 241
Mappings of MDA-Based Languages and Ontologies	p. 245
Relations Between Modeling Spaces	p. 245
Transformations Between Modeling Spaces	p. 248
Example of an Implementation: An XSLT-Based Approach	p. 252
Implementation Details	p. 253
Transformation Example	p. 254
Practical Experience	p. 257
Discussion	p. 260
Applications
Modeling Tools and Ontology Development	p. 265
MagicDraw	p. 266
Starting with MagicDraw	p. 266
Things You Should Know when Working with UML Profiles	p. 268
Creating a New Ontology	p. 270
Working with Ontology Classes	p. 273
Working with Ontology Properties	p. 276
Working with Individuals	p. 280
Working with Statements	p. 282
Poseidon for UML	p. 283
Modeling Ontology Classes in Poseidon	p. 285
Modeling Ontology Individuals and Statements in Poseidon	p. 286
Sharing Models Between UML Tools and Protege	p. 287
Atlas Transformation Language	p. 291
Basics	p. 291
ATL Integrated Development Environment	p. 292
Support for Technical Spaces	p. 293
ATL for Transforming Between ODM and UML	p. 294
An MDA Based Ontology Platform: AIR	p. 299
Motivation	p. 299
The Basic Idea	p. 300
Metamodel-the Conceptual Building Block of AIR	p. 302
The AIR Metadata Repository	p. 303
The AIR Workbench	p. 306
The Role of XML Technologies	p. 308
Possibilities	p. 309
Examples of Ontology	p. 311
Petri Net Ontology	p. 311
Organization of the Petri Net Ontology	p. 313
The Core Petri Net Ontology in the Ontology UML Profile	p. 316
An Extension Example: Upgraded Petri Nets	p. 319
Educational Ontologies	p. 322
Conceptual Solution	p. 323
Mapping the Conceptual Model to Ontologies	p. 325
Beyond the Ontology Definition Metamodel: Applications	p. 335
Integrated Ontology Development Toolkit	p. 335
TwoUse: UML and OWL Modeling	p. 338
Model Driven Engineering of Ontology Reasoners	p. 341
Model Driven Engineering and Semantic Web Rules	p. 345
References	p. 351
Index	p. 371
Table of Contents provided by Ingram. All Rights Reserved.

Model Driven Engineering and Ontology Development

At a Glance

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Industry Reviews

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