Foundations of Semantic Web Technologies 1st Edition by Pascal Hitzler, Markus Krotzsch, Sebastian Rudolph ISBN 9781439890028 1439890021

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ISBN 10: 1439890021
ISBN 13: 9781439890028
Author: Pascal Hitzler, Markus Krotzsch, Sebastian Rudolph

Foundations of Semantic Web Technologies 1st Edition Table of contents:

Chapter 1 The Quest for Semantics

1.1 Building Models

FIGURE 1.1: The Tree of Porphyry, an early tree structure in knowledge modeling; diagram based on a translation in [Sow00]

1.2 Calculating with Knowledge

1.3 Exchanging Information

1.4 Semanic Web Technologies

1.5 Further Reading

Part I Resource Description Language RDF

Chapter 2 Simple Ontologies in RDF and RDF Schema

FIGURE 2.1: A simple RDF graph describing the relationship between this book and the publisher, CRC Press

2.1 Introduction to RDF

2.1.1 Graphs Instead of Trees

2.1.2 Names in RDF: URIs

2.1.3 Data Values in RDF: Literals

FIGURE 2.2: The basic construction scheme for URIs

FIGURE 2.3: An RDF graph with literals for describing data values

2.2 Syntax for RDF

2.2.1 From Graphs to Triples

2.2.2 Simple Triple Syntax: N3, N-Triples and Turtle

2.2.3 The XML Serialization of RDF

2.2.4 RDF in XML: URIs and Other Problems

2.2.5 Shorter URIs: XML Entities and Relative URIs

2.2.6 Where Do URIs Come From? What Do They Mean?

FIGURE 2.4: Summary of abbreviation mechanisms in RDF/XML

FIGURE 2.5: An RDF graph with typed literals

2.3 Advanced Features

2.3.1 Datatypes in RDF

2.3.2 Language Settings and Datatypes

Similar yet distinct

2.3.3 Many-Valued Relationships

FIGURE 2.6: Representing many-valued relationships in RDF

2.3.4 Blank Nodes

FIGURE 2.7: Representing auxiliary resources by blank nodes

2.4 Simple Ontologies in RDF Schema

2.4.1 Classes and Instances

2.4.2 Subclasses and Class Hierarchies

2.4.3 Properties

FIGURE 2.8: Example for class hierarchies in RDFS

2.4.4 Subproperties and Property Hierarchies

2.4.5 Property Restrictions

2.4.6 Additional Information in RDFS

2.5 Encoding of Special Datastructures

FIGURE 2.9: Additional information in RDFS documents

2.5.1 Lists in RDF

2.5.1.1 RDF Container

FIGURE 2.10: A list of type rdf: Seq in RDF

2.5.1.2 Containers in RDFS

2.5.1.3 RDF Collections

FIGURE 2.11: A collection in RDF

2.5.2 Propositions About Propositions: Reification

FIGURE 2.12: Example of multiple reification in graph representation

2.6 An Example

FIGURE 2.13: Graph representation of a simple RDFS ontology

2.7 Summary

2.7.1 Overview of RDF(S) Language Constructs

2.8 Exercises

2.9 Further Reading

Chapter 3 RDF Formal Semantics

3.1 Why Semantics?

3.2 Model-Theoretic Semantics for RDF(S)

FIGURE 3.1: Definition of the entailment relation via models

FIGURE 3.2: Correspondence of interpretations

3.2.1 Simple Interpretations

FIGURE 3.3: Schematic representation of a simple interpretation

FIGURE 3.4: Criterion for the validity of a triple with respect to an interpretation

3.2.2 RDF-Interpretations

FIGURE 3.5: Example of an interpretation

3.2.3 RDFS Interpretations

3.2.4 Interpretation of Datatypes

3.2.5 Worked Example

FIGURE 3.6: Example of a simple interpretation

FIGURE 3.7: Example of an RDF-interpretation

FIGURE 3.8: Example of IS

3.3 Syntactic Reasoning with Deduction Rules

3.3.1 Deduction Rules for Simple Entailment

THEOREM 3.1

3.3.2 Deduction Rules for RDF-Entailment

FIGURE 3.9: Example of simple entailment

FIGURE 3.10: Graph that is simply entailed by the graph from Fig. 2.3

FIGURE 3.11: Example deduction illustrating Theorem 3.1

THEOREM 3.2

3.3.3 Deduction Rules for RDFS-Entailment

THEOREM 3.3

3.3.4 Additional Rules for Datatypes

3.3.5 Example of an RDFS Deduction

FIGURE 3.12: Graph G2, possibly RDFS-entailed by G1

3.4 The Semantic Limits of RDF(S)

FIGURE 3.13: Example of an RDFS deduction

3.5. Summary

3.6 Exercises

3.7 Further Reading

Part II Web Ontology Language OWL

Chapter 4 Ontologies in OWL

FIGURE 4.1: Sentences which cannot be modeled in RDF(S) in a sufficiently precise way

4.1 OWL Syntax and Intuitive Semantics

FIGURE 4.2: The three sublanguages of OWL and their most important general properties. Further details can be found in Section 4.2

4.1.1 The Header of an OWL Ontology

4.1.2 Classes, Roles, and Individuals

FIGURE 4.3: XML datatypes for OWL

FIGURE 4.4: Logical inference by transitivity of rdfs:subClassOf

4.1.3 Simple Class Relations

4.1.4 Relations Between Individuals

FIGURE 4.5: Example of an inference with owl:disjointWith

FIGURE 4.6: Example of an inference with owl:equivalentClass

FIGURE 4.7: Example of an inference with individuals

FIGURE 4.8: Example inference with owl:sameAs

4.1.5 Closed Classes

4.1.6 Boolean Class Constructors

FIGURE 4.9: Example inference with closed classes

FIGURE 4.10: Classes via oneOf and datatypes

FIGURE 4.11: Example inference using nested Boolean class constructors

4.1.7 Role Restrictions

FIGURE 4.12: owl:cardinality expressed using owl:minCardinality and owl:maxCardinality

FIGURE 4.13: Example ontology for role restrictions

4.1.8 Role Relationships

FIGURE 4.14: Example using role relationships

4.1.9 Role Characteristics

FIGURE 4.15: Role characteristics

4.1.10 Types of Inferences

4.2 OWL Species

4.2.1 OWL Full

4.2.2 OWL DL

4.2.3 OWL Lite

4.3 The Forthcoming OWL 2 Standard

4.3.1 OWL 2 DL

4.3.1.1 Type Separation, Punning and Declarations

4.3.1.2 Disjoint Classes

4.3.1.3 Role Characteristics and Relationships

4.3.1.4 Inverse Roles

4.3.1.5 Role Chains

4.3.1.6 Qualified Cardinality Restrictions

4.3.1.7 The Self Construct

4.3.1.8 Negated Role Assignments

4.3.1.9 Datatypes

FIGURE 4.16: Datatype constraining facets: restricting the allowed range of an integer value

4.3.2 OWL 2 Profiles

4.3.2.1 OWL 2 EL

4.3.2.2 OWL 2 QL

4.3.2.3 OWL 2 RL

4.3.3 OWL 2 Full

4.4 Summary

4.4.1 Overview of OWL 1 Language Constructs

4.4.1.1 Header

4.4.1.2 Relations Between Individuals

4.4.1.3 Class Constructors and Relationships

4.4.1.4 Role Constructors, Relationships and Characteristics

4.1.5 Allowed Datatypes

4.4.2 Overview of Additional OWL 2 Language Constructs

4.4.2.1 Declaring Individuals

4.4.2.2 Class Relationships

4.4.2.3 Role Characteristics and Relationships

4.4.2.4 Role Restrictions

4.4.2.5 Role Assignments

4.4.2.6 Datatype Restrictions

4.4.2.7 Additional Datatypes

4.5 Exercises

4.6 Further Reading

Chapter 5 OWL Formal Semantics

5.1 Description Logics

5.1.1 The Description Logic

5.1.1.1 Building Blocks of

5.1.1.2 Modeling Part of OWL in

5.1.1.3 Formal Syntax of

5.1.2 OWL DL as Description Logic

5.1.2.1 Class Constructors and Relationships

5.1.2.2 Relationships Between Individuals

5.1.2.3 Role Constructors, Role Relationships, and Role Characteristics

5.1.2.4 Datatypes

5.1.2.5 and OWL DL

5.1.3 Naming Description Logics – and How They Relate to the OWL Sublanguages

5.1.3.1 Role Functionality

5.1.3.2 Qualified Cardinality Restrictions

5.1.3.3 Generalized Role Inclusions

FIGURE 5.1: Correspondence between OWL variants and description logics

5.1.3.4 Existential Role Restrictions

5.1.3.5 OWL Sublanguages and Description Logics

5.1.4 Formal Syntax of

5.1.4.1 RBoxes

5.1.4.2 Knowledge Bases

5.1.4.3

5.2 Model-Theoretic Semantics of OWL

5.2.1 Extensional Semantics of

5.2.1.1 Interpreting Individuals, Classes, and Roles

FIGURE 5.2: Schematic representation of a DL interpretation

5.2.1.2 Interpreting Axioms

FIGURE 5.3: Models for the example knowledge base from page 174

5.2.1.3 Logical Consequences

FIGURE 5.4: Logical consequences of a knowledge base. The first line states that C ⊑ D is a logical consequence of K if and only if holds for all models of K, which is the case if and only if holds for all models of K.

FIGURE 5.5: Example of logical consequence

FIGURE 5.6: Examples of notions of consistency and satisfiability

5.2.2 Semantics via Predicate Logic

5.2.2.1 Translating Class Inclusion Axioms

5.2.2.2 Translating Individual Assignments

5.2.2.3 Translating RBoxes

5.2.2.4 Properties of the Translation and an Example

FIGURE 5.7: Translating general inclusion axioms into first-order predicate logic with equality. Note that πx(≥0S.C) = ⊤(x). We use auxiliary functions πx, πx1, etc., where x, x1, etc. are variables. Also note that variables x1 …, xn+1 introduced on the right-hand sides should always be variables which are new, i.e. which have not yet been used in the knowledge base. Obviously, renamings are possible — and indeed advisable for better readability. The axiom D ⊑ ∃R.∃S.C, for example, could be translated to (∀x)((D(x)) → (∃y)(R(x, y) ∧ (∃z)(S(y, z) ∧ C(z)))).

FIGURE 5.8: Translating RBoxes into first-order predicate logic

5.3 Automated Reasoning with OWL

FIGURE 5.9: Example of translation from description logic syntax to first-order predicate logic syntax

5.3.1 Inference Problems

5.3.2 Negation Normal Form

FIGURE 5.10: Transformation of a knowledge base K into negation normal form

5.3.3 Tableaux Algorithm for

5.3.3.1 Initial Examples

5.3.3.2 The Naive Tableaux Algorithm for

FIGURE 5.11: Example of an initial tableau given the knowledge base K = {A(a), (∃R.B)(a), R(a, b), R(a, c), S(b, b), (A ⊔ B)(c), ¬A ⊔ (∀S.B)}

FIGURE 5.12: Expansion rules for the naive tableaux algorithm

5.3.3.3 The Tableaux Algorithm with Blocking for

FIGURE 5.13: Worked example of tableau

5.3.3.4 Worked Examples

5.3.3.4.1 Blocking

5.3.3.4.2 Open World

5.3.3.4.3 A Sophisticated Example

5.3.4 Tableaux Algorithm for

FIGURE 5.14: Final tableau for the example from Section 5.3.3.4.3

FIGURE 5.15: Example of notions of successor, predecessor, neighbor and ancestor

5.3.4.1 Blocking for

5.3.4.2 The Algorithm

5.3.4.3 Worked Examples

5.3.4.3.1 Cardinalities

FIGURE 5.16: Expansion rules (part 1) for the tableaux algorithm

FIGURE 5.17: Expansion rules (part 2) for the tableaux algorithm

5.3.4.3.2 Choose

5.3.4.3.3 Inverse Roles

5.3.4.3.4 Transitivity and Blocking

5.3.4.3.5 Why We Need Pairwise Blocking

FIGURE 5.18: Worst-case complexity classes of some description logics

5.3.5 Computational Complexities

5.4 Summary

5.5 Exercises

5.6 Further Reading

Part III Rules and Queries

Chapter 6 Ontologies and Rules

6.1 What Is a Rule?

6.2 Datalog as a First-Order Rule Language

6.2.1 Introduction to Datalog

FIGURE 6.1: Example datalog program

6.2.2 Semantics of Datalog

FIGURE 6.2: Example datalog interpretation of predicate symbols

6.3 Combining Rules with OWL DL

6.3.1 Combined Semantics: Datalog and Description Logics

FIGURE 6.3: Description logic axioms extending the datalog program from Fig. 6.1

6.3.2 Computing Conclusions

6.3.3 Description Logic Rules

FIGURE 6.4: Examples of simple rule dependency graphs

FIGURE 6.5: Transforming Description Logic Rules into axioms

FIGURE 6.6: DL-safety of rules depends on the given description logic axioms

6.3.4 DL-safe Rules

FIGURE 6.7: Combination of DL-safe rules, DL Rules, and description logic axioms

6.4 Rule Interchange Format RIF

6.4.1 RIF-Core

6.4.2 Object-Oriented Data Structures: Frames in RIF

6.4.3 RIF-Core Semantics

6.4.4 XML Syntax for RIF-Core

FIGURE 6.8: Transformation of RIF-Core rules to datalog

FIGURE 6.9: Transformation of RIF presentation syntax to XML syntax

6.4.5 Combining RIF with OWL DL

FIGURE 6.10: Example RIF-Core rules, formatted for OWL-RIF integration

6.4.6 Combining RIF with RDF(S)

6.4.6.1 Simple Semantics

6.4.6.2 RDF Semantics

6.4.6.3 RDFS Semantics

6.4.7 Further Features of RIF-Core and RIF-BLD

FIGURE 6.11: Additional first-order axioms for simulating RDFS semantics; initial labels refer to the corresponding deduction rule in Section 3.3.3

6.5 Summary

6.6 Exercises

6.7 Further Reading

Chapter 7 Query Languages

7.1 SPARQL: Query Language for RDF

7.1.1 Simple SPARQL Queries

7.1.2 Simple Graph Patterns: Triples and Variables

7.1.3 Blank Nodes in SPARQL

7.1.4 Complex Graph Patterns: Groups, Options, and Alternatives

7.1.5 Queries with Data Values

7.1.6 Filters

7.1.6.1 Comparison Operators

7.1.6.2 Special Operators

FIGURE 7.1: Unary operators for accessing specific parts of RDF literals

7.1.6.3 Boolean Operators

7.1.6.4 Arithmetic Operations

7.1.6.5 Errors

7.1.7 Result Formats

7.1.8 Modifiers

7.1.9 Semantics and Algebra of SPARQL

7.1.9.1 Translating Queries to SPARQL Algebra

7.1.9.2 Calculations in SPARQL Algebra

FIGURE 7.2: Example RDF document for illustrating query evaluation in SPARQL

7.1.9.3 Operators for Modifiers

FIGURE 7.3: Intermediate results in computing the result of a SPARQL query

7.1.10 Further Expressive Features of SPARQL

7.2 Conjunctive Queries for OWL DL

7.2.1 The Limits of OWL

7.2.2 Introduction to Conjunctive Queries

7.2.3 Non-Distinguished Variables

7.2.4 Conjunctive Queries and Rules

7.2.5 Conjunctive Queries and SPARQL

7.3 Summary

7.4 Exercises

7.5 Further Reading

Part IV Beyond Foundations

Chapter 8 Ontology Engineering

8.1 Requirement Analysis

8.2 Ontology Creation – Where Is Your Knowledge?

8.2.1 It’s in Your Heads: Human Sources

8.2.2 It’s in Your Books: Unstructured sources

FIGURE 8.1: Parse trees for the two example sentences

8.2.3 It’s on the Web: Semistructured Sources

8.2.4 It’s in the Databases: Structured Sources

8.3 Quality Assurance of Ontologies

8.3.1 Ontology Evaluation: What Makes an Ontology Good

8.3.2 How to (Not) Model Correctly

8.3.2.1 Don’t forget disjointness

8.3.2.2 Don’t forget role characteristics

8.3.2.3 Don’t choose too specific domains or ranges

8.3.2.4 Be careful with quantifiers

8.3.2.5 Don’t mistake parts for subclasses

8.3.2.6 Watch the direction of roles

8.3.2.7 Don’t confuse class subsumption and class equivalence

8.3.2.8 Don’t translate too verbally

8.3.3 Ontology Refinement: How to Make Ontologies Better

8.4 Modular Ontologies: Divide and Conquer

8.5 Software Tools

8.5.1 Ontology Editors

8.5.1.1 Protégé

8.5.1.2 TopBraid Composer

8.5.1.3 NeOn Toolkit

8.5.1.4 OntoStudio

8.5.1.5 SWOOP

8.5.2 RDF Stores

8.5.2.1 Virtuoso

8.5.2.2 Redland

8.5.2.3 Sesame

8.5.2.4 AllegroGraph

8.5.2.5 OWLIM

8.5.3 OWL DL Reasoning Engines

8.5.3.1 Pellet

8.5.3.2 RacerPro

8.5.3.3 FaCT++

8.5.3.4 KAON2

8.5.3.5 SHER

8.5.4 Reasoning Engines for OWL 2 Profiles

8.5.4.1 CEL

8.5.4.2 Owlgres

8.5.5 QuOnto

8.5.5.1 Oracle 11g

8.5.6 Datalog and Rules Engines

8.5.6.1 XSB

8.5.6.2 SWI-Prolog

8.5.6.3 Ontobroker

8.5.6.4 DLV

8.5.6.5 IRIS

8.5.7 Further Systems

8.5.7.1 OWL API

8.5.7.2 Jena

8.6 Summary

8.7 Further Reading

Chapter 9 Applications

9.1 Web Data Exchange and Syndication

9.1.1 Endowing Web Data with Metadata

9.1.2 Vocabularies

FIGURE 9.1: Example RSS file

FIGURE 9.2: Example FOAF file

9.2 Semantic Wikis

9.2.1 Semantic MediaWiki

9.2.2 Applications

9.3 Semantic Portals

9.4 Semantic Metadata in Data Formats

9.5 Semantic Web in Life Sciences

9.6 Ontologies for Standardizations

9.7 RIF Applications

9.8 Toward Future Applications

9.9 Summary

9.10 Further Reading

Part V Appendices

Appendix A Extensible Markup Language XML

A.1 XML in a Nutshell

FIGURE A.1: The tree structure of XML

A.2 Syntax of XML

A.3 XML Schema

A.3.1 Elements, Attributes, and Datatypes

A.3.2 User-Defined Types

Appendix B Set Theory

B.1 Basic Notions

B.2 Set Operations

B.3 Relations and Functions

Appendix C Logic

C.1 Syntax

C.2 Semantics

THEOREM C.1

FIGURE C.1: Logical equivalences from Theorem C.1.

THEOREM C.2

THEOREM C.3

THEOREM C.4

C.3 Proof Theory and Decidability

THEOREM C.5

THEOREM C.6

THEOREM C.7

Appendix D Solutions to the Exercises

D.1 Solutions for Chapter 2

D.2 Solutions for Chapter 3

D.3 Solutions for Chapter 4

D.4 Solutions for Chapter 5

FIGURE D.1: Solution to Exercise 5.4

D.5 Solutions for Chapter 6

FIGURE D.2: Solution to Exercise 6.6

D.6 Solutions for Chapter 7

FIGURE D.3: Exercise 7.3 fourth query: Table for Join(BGP( ?object ?satellite1.), BGP(?object ?satellite2.))

FIGURE D.4: Exercise 7.3 fourth query: Table for Filter((!sameTERM(?satellite1,?satellite2)), Join(BGP(?object ?satellite1.), BGP(?object ?satellite2.) ) )

References

Index

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