Contents

Foreword by Dave McComb

Foreword by Mark A. Musen

Preface

Acknowledgments

Part 1: Introducing OWL

1    Getting Started: What Do We Need to Say?

1.1    What is an Ontology? What is OWL?

1.2    In the Beginning there are Things

1.3    Kinds of Things vs. Individual Things

1.4    No Thing is an Island

1.4.1    Healthcare

1.4.2    Finance

1.4.3    Corporate Registrations

1.5    Things Can Have a Variety of Attributes

1.6    More General Things and More Specific Things

1.7    Drawing Conclusions

1.8    Data and Metadata

1.9    Summary Learning

2    How Do We Say it in OWL?

2.1    Introduction

2.2    Saying Things

2.2.1    An Ontology is a Set of Triples

2.2.2    Namespaces, Resource Identifiers, and OWL Syntax

2.2.3    Summary: Informal to Formal

2.2.4    Notational Conventions

2.3    A Simple Ontology in Healthcare

2.3.1    Healthcare Data

2.3.2    Healthcare Metadata

2.3.3    Individuals and Their Types

2.3.4    Richer Semantics and Automatic Categorization

2.3.5    Other Ways to Specify Meaning

2.3.6    Pause and Reflect

2.4    Summary of Key OWL Concepts and Assertions

2.4.1    Vocabularies and Namespaces

2.4.2    Individuals and Classes

2.4.3    Properties

2.4.4    Class Expressions and Restrictions

2.4.5    Drawing Conclusions

2.5    Summary Learning

3    Fundamentals: Meaning, Semantics, and Sets

3.1    Logic

3.1.1    Reasoning and Arguments

3.1.2    Formal Semantics and Sets

3.1.3    The Open World

3.1.4    Resource Identifiers

3.1.5    Literals and Datatypes

3.1.6    Metaclasses

3.1.7    Expressions

3.1.8    Meaning, Semantics, and Ambiguity

3.1.9    Concepts vs. Terms

3.1.10  The World of Triples

3.1.11  Reuse and Modularity

3.1.12  Triple Stores, Querying, and SPARQL

3.1.13  Summary Learning

3.2    Summary for Part 1

Part 2: Going into Depth: Properties and Classes

4    Properties

4.1    Properties, Relationships, and Sets

4.2    Properties are First-Class Objects

4.3    Property Hierarchies

4.4    Domain and Range

4.4.1    Use Domain and Range with Care

4.5    Inverse Properties and Property Chains

4.5.1    Inverse Properties

4.5.2    Property Chains

4.6    Property Characteristics

4.6.1    Functional Properties

4.6.2    Transitive Properties

4.6.3    Symmetric and Asymmetric Properties

4.7    Property Characteristics of Subproperties and Inverse Properties

4.7.1    Subproperties

4.7.2    Inverse Properties

4.8    Data Properties

4.8.1    Data vs. Object Properties

4.8.2    When to Use Data Properties

4.9    Disjointness and Equivalence

4.10  Annotation Properties

4.11  Summary Learning

5    Classes

5.1    Review: Classes and Sets

5.2    Class Relationships

5.2.1    Subclass

5.2.2    Class Equivalence

5.2.3    Disjoint Classes

5.3    Class Expressions

5.3.1    Anonymous Classes and Blank Nodes

5.3.2    Boolean Expressions

5.3.3    Enumeration

5.3.4    Property Restrictions

5.3.5    Summary: Class Expressions

5.4    Property Restrictions

5.4.1    Usage Scenarios

5.4.2    Anatomy of a Property Restriction

5.4.3    Existential: someValuesFrom

5.4.4    Universal: allValuesFrom

5.4.5    Minimum Cardinality

5.4.6    Maximum Cardinality

5.4.7    Exact Cardinality

5.4.8    Individual Value: hasValue

5.4.9    Data Property Restrictions

5.4.10  Summary: Property Restrictions

5.5    Summary Learning

5.6    Conclusion for Part 2

Part 3: Using OWL in Practice

6    More Examples

6.1    Patient Visit

6.2    Collateral

6.3    Internal vs. External Transactions

6.4    Inference

6.4.1    Patient Visit

6.4.2    Inference with Partial Information

6.4.3    Security Agreement and Collateral

6.4.4    Internal Organizations and Transactions

6.4.5    Classification Inference

6.5    Summary Learning

7    OWL Limitations

7.1    Metaclasses

7.2    The Object of a Triple

7.3    N-ary Relations

7.4    Rules

7.5    Dates and Times

7.6    Cardinality Restrictions with Transitive Properties or Property Chains

7.7    Inference at Scale

7.8    Summary Learning

8    Go Forth and Ontologize

8.1    Modeling Principles and Tools

8.1.1    Conceptual and Operational

8.1.2    Concepts, Terms, and Naming Conventions

8.1.3    Modeling Choice: Data or Object Property?

8.1.4    Modeling Choice: Class or Property?

8.1.5    Modeling Choice: Class or Individual?

8.1.6    Modularity for Reusability

8.1.7    Ontology Editors and Inference Engines

8.2    Modeling Patterns

8.2.1    Genus Differentia

8.2.2    Orphan Classes and High-level Disjoints

8.2.3    Upper Ontologies

8.2.4    N-ary Relations

8.2.5    Buckets, Buckets Everywhere

8.2.6    Roles

8.3    Common Pitfalls

8.3.1    Reading Too Much into IRIs and Labels

8.3.2    Unique Name Assumption

8.3.3    Namespace Proliferation

8.3.4    Domain and Range

8.3.5    Less is More

8.4    Less Frequently Used OWL Constructs

8.4.1    Pairwise disjoint and disjoint Union

8.4.2    Datatypes

8.4.3    Different Individuals

8.4.4    Same Individuals

8.4.5    Deprecation

8.5    The Open World Revisited

8.6    Summary Learning

8.7    Final Remarks

Appendices

A.1    Acronyms & Abbreviations

A.2    e6Tools Visual OWL Syntax

A.3    Recommended Resources for Further Learning

A.4    Answers to Exercises

A.4.1    Chapter 1

A.4.2    Chapter 2

A.4.4    Chapter 4

A.4.5    Chapter 5

A.4.6    Chapter 6

Author Biography

Index