Yu A Developer's Guide to the Semantic Web

1. Auflage 2011
ISBN: 978-3-642-15970-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 608 Seiten

Covering the theory, technical components and applications of the Semantic Web, this book's unrivalled coverage includes the latest on W3C standards such as OWL 2, and discusses new projects such as DBpedia. It also shows how to put theory into practice.

Liyang Yu is Senior Software Developer with Delta Air Lines in Atlanta, GA, USA. He is a regular speaker on Semantic Web research and development issues at international conferences. His previously published introductory book on Semantic Web services has been used as the basic textbook for related courses by universities worldwide.

Autoren/Hrsg.

Yu, Liyang

Inhaltsverzeichnis

1;Preface;5
1.1;Objectives of the Book;5
1.2;Intended Readers;6
1.3;Structure of the Book;6
1.4;Where to Get the Code;9
1.5;Acknowledgment;9
2;Contents;11
3;1 A Web of Data: Toward the Idea of the Semantic Web;18
3.1;1.1 A Motivating Example: Data Integration on the Web;18
3.1.1;1.1.1 A Smart Data Integration Agent;19
3.1.2;1.1.2 Is Smart Data Integration Agent Possible?;24
3.1.3;1.1.3 The Idea of the Semantic Web;26
3.2;1.2 A More General Goal: A Web Understandable to Machines;26
3.2.1;1.2.1 How Do We Use the Web?;26
3.2.1.1;1.2.1.1 Searching;27
3.2.1.2;1.2.1.2 Information Integration;27
3.2.1.3;1.2.1.3 Web Data Mining;28
3.2.2;1.2.2 What Stops Us from Doing More?;29
3.2.3;1.2.3 Again, the Idea of the Semantic Web;31
3.3;1.3 The Semantic Web: A First Look;31
3.3.1;1.3.1 The Concept of the Semantic Web;31
3.3.2;1.3.2 The Semantic Web, Linked Data, and the Web of Data;32
3.3.3;1.3.3 Some Basic Things About the Semantic Web;34
3.4;Reference;35
4;2 The Building Block for the Semantic Web: RDF;36
4.1;2.1 RDF Overview;36
4.1.1;2.1.1 RDF in Official Language;36
4.1.2;2.1.2 RDF in Plain English;38
4.2;2.2 The Abstract Model of RDF;42
4.2.1;2.2.1 The Big Picture;42
4.2.2;2.2.2 Statement;42
4.2.3;2.2.3 Resource and Its URI Name;44
4.2.4;2.2.4 Predicate and Its URI Name;48
4.2.5;2.2.5 RDF Triples: Knowledge That Machine Can Use;50
4.2.6;2.2.6 RDF Literals and Blank Node;52
4.2.6.1;2.2.6.1 Basic Terminologies So Far;52
4.2.6.2;2.2.6.2 Literal Values;54
4.2.6.3;2.2.6.3 Blank Nodes;55
4.2.7;2.2.7 A Summary So Far;58
4.3;2.3 RDF Serialization: RDF/XML Syntax;59
4.3.1;2.3.1 The Big Picture: RDF Vocabulary;59
4.3.2;2.3.2 Basic Syntax and Examples;60
4.3.2.1;2.3.2.1 rdf:RDF, rdf:Description, rdf:about, and rdf:resource ;60
4.3.2.2;2.3.2.2 rdf:type and Typed Nodes;62
4.3.2.3;2.3.2.3 Using Resource as Property Value;64
4.3.2.4;2.3.2.4 Using Un-typed Literals as Property Values, rdf:value and rdf:parseType;66
4.3.2.5;2.3.2.5 Using Typed Literal Values and rdf:datatype ;69
4.3.2.6;2.3.2.6 rdf:nodeID and More About Anonymous Resources;72
4.3.2.7;2.3.2.7 rdf:ID, xml:base, and RDF/XML Abbreviation;73
4.3.3;2.3.3 Other RDF Capabilities and Examples;76
4.3.3.1;2.3.3.1 RDF Containers: rdf:Bag, rdf:Seq, rdf:Alt, and rdf:li ;76
4.3.3.2;2.3.3.2 RDF Collections: rdf:first, rdf:rest, rdf:nil, and rdf:List ;78
4.3.3.3;2.3.3.3 RDF Reification: rdf:statement, rdf:subject, rdf:predicate, and rdf:object;80
4.4;2.4 Other RDF Sterilization Formats;82
4.4.1;2.4.1 Notation-3, Turtle, and N-Triples;82
4.4.2;2.4.2 Turtle Language;83
4.4.2.1;2.4.2.1 Basic Language Feature;83
4.4.2.2;2.4.2.2 Abbreviations and Shortcuts: Namespace Prefix, Default Prefix, and @base ;84
4.4.2.3;2.4.2.3 Abbreviations and Shortcuts: Token a, Comma, and Semicolons;86
4.4.2.4;2.4.2.4 Turtle Blank Nodes;88
4.5;2.5 Fundamental Rules of RDF;89
4.5.1;2.5.1 Information Understandable by Machine;90
4.5.2;2.5.2 Distributed Information Aggregation;92
4.5.3;2.5.3 A Hypothetical Real-World Example;93
4.6;2.6 More About RDF;96
4.6.1;2.6.1 Dublin Core: Example of Pre-defined RDF Vocabulary;96
4.6.2;2.6.2 XML vs. RDF?;98
4.6.3;2.6.3 Use an RDF Validator;101
4.7;2.7 Summary;102
5;3 Other RDF-Related Technologies: Microformats, RDFa, and GRDDL;104
5.1;3.1 Introduction: Why Do We Need These?;104
5.2;3.2 Microformats;105
5.2.1;3.2.1 Microformats: The Big Picture;105
5.2.2;3.2.2 Microformats: Syntax and Examples;106
5.2.2.1;3.2.2.1 From vCard to hCard Microformat;106
5.2.2.2;3.2.2.2 Using hCard Microformat to Mark Up Page Content;108
5.2.3;3.2.3 Microformats and RDF;111
5.2.3.1;3.2.3.1 What Is So Good About Microformats?;111
5.2.3.2;3.2.3.2 Microformats and RDF;112
5.3;3.3 RDFa;112
5.3.1;3.3.1 RDFa: The Big Picture;112
5.3.2;3.3.2 RDFa Attributes and RDFa Elements;113
5.3.3;3.3.3 RDFa: Rules and Examples;114
5.3.3.1;3.3.3.1 RDFa Rules;114
5.3.3.2;3.3.3.2 RDFa Examples;116
5.3.4;3.3.4 RDFa and RDF;121
5.3.4.1;3.3.4.1 What Is So Good About RDFa?;121
5.3.4.2;3.3.4.2 RDFa and RDF;121
5.4;3.4 GRDDL;122
5.4.1;3.4.1 GRDDL: The Big Picture;122
5.4.2;3.4.2 Using GRDDL with Microformats;122
5.4.3;3.4.3 Using GRDDL with RDFa;124
5.5;3.5 Summary;124
6;4 RDFS and Ontology;125
6.1;4.1 RDFS Overview;125
6.1.1;4.1.1 RDFS in Plain English;125
6.1.2;4.1.2 RDFS in Official Language;126
6.2;4.2 RDFS + RDF: One More Step Toward Machine Readable;127
6.2.1;4.2.1 A Common Language to Share;127
6.2.2;4.2.2 Machine Inferencing Based on RDFS;129
6.3;4.3 RDFS Core Elements;130
6.3.1;4.3.1 The Big Picture: RDFS Vocabulary;130
6.3.2;4.3.2 Basic Syntax and Examples;130
6.3.2.1;4.3.2.1 Defining Classes;130
6.3.2.2;4.3.2.2 Defining Properties;136
6.3.2.3;4.3.2.3 More About Properties;142
6.3.2.4;4.3.2.4 RDFS Datatypes;145
6.3.2.5;4.3.2.5 RDFS Utility Vocabulary;147
6.3.3;4.3.3 Summary So Far;148
6.3.3.1;4.3.3.1 Our Camera Vocabulary;148
6.3.3.2;4.3.3.2 Where Is the Knowledge?;152
6.4;4.4 The Concept of Ontology;152
6.4.1;4.4.1 What Is Ontology?;153
6.4.2;4.4.2 The Benefits of Ontology;153
6.5;4.5 Building the Bridge to Ontology: SKOS;154
6.5.1;4.5.1 Knowledge Organization Systems (KOS);154
6.5.2;4.5.2 Thesauri vs. Ontologies;156
6.5.3;4.5.3 Filling the Gap: SKOS;157
6.5.3.1;4.5.3.1 What Is SKOS?;157
6.5.3.2;4.5.3.2 SKOS Core Constructs;158
6.5.3.3;4.5.3.3 Interlinking Concepts by Using SKOS;163
6.6;4.6 Another Look at Inferencing Based on RDF Schema;165
6.6.1;4.6.1 RDFS Ontology-Based Reasoning: Simple, Yet Powerful;165
6.6.2;4.6.2 Good, Better, and Best: More Is Needed;167
6.7;4.7 Summary;168
7;5 OWL: Web Ontology Language;170
7.1;5.1 OWL Overview;170
7.1.1;5.1.1 OWL in Plain English;170
7.1.2;5.1.2 OWL in Official Language: OWL 1 and OWL 2;171
7.1.3;5.1.3 From OWL 1 to OWL 2;173
7.2;5.2 OWL 1 and OWL 2: The Big Picture;173
7.2.1;5.2.1 Basic Notions: Axiom, Entity, Expression, and IRI Names;174
7.2.2;5.2.2 Basic Syntax Forms: Functional Style, RDF/XML Syntax, Manchester Syntax, and XML Syntax;175
7.3;5.3 OWL 1 Web Ontology Language;176
7.3.1;5.3.1 Defining Classes: The Basics;176
7.3.2;5.3.2 Defining Classes: Localizing Global Properties;178
7.3.2.1;5.3.2.1 Value Constraints: owl:allValuesFrom ;179
7.3.2.2;5.3.2.2 Enhanced Reasoning Power 1;181
7.3.2.3;5.3.2.3 Value Constraints: owl:someValuesFrom ;182
7.3.2.4;5.3.2.4 Enhanced Reasoning Power 2;183
7.3.2.5;5.3.2.5 Value Constraints: owl:hasValue ;183
7.3.2.6;5.3.2.6 Enhanced Reasoning Power 3;185
7.3.2.7;5.3.2.7 Cardinality Constraints: owl:cardinality, owl:min(max)Cardinality ;185
7.3.2.8;5.3.2.8 Enhanced Reasoning Power 4;187
7.3.3;5.3.3 Defining Classes: Using Set Operators;187
7.3.3.1;5.3.3.1 Set Operators;187
7.3.3.2;5.3.3.2 Enhanced Reasoning Power 5;189
7.3.4;5.3.4 Defining Classes: Using Enumeration, Equivalent, and Disjoint;190
7.3.4.1;5.3.4.1 Enumeration, Equivalent, and Disjoint;190
7.3.4.2;5.3.4.2 Enhanced Reasoning Power 6;192
7.3.5;5.3.5 Our Camera Ontology So Far;192
7.3.6;5.3.6 Define Properties: The Basics;194
7.3.7;5.3.7 Defining Properties: Property Characteristics;199
7.3.7.1;5.3.7.1 Symmetric Properties;199
7.3.7.2;5.3.7.2 Enhanced Reasoning Power 7;200
7.3.7.3;5.3.7.3 Transitive Properties;201
7.3.7.4;5.3.7.4 Enhanced Reasoning Power 8;201
7.3.7.5;5.3.7.5 Functional Properties;202
7.3.7.6;5.3.7.6 Enhanced Reasoning Power 9;204
7.3.7.7;5.3.7.7 Inverse Property;204
7.3.7.8;5.3.7.8 Enhanced Reasoning Power 10;205
7.3.7.9;5.3.7.9 Inverse Functional Property;205
7.3.7.10;5.3.7.10 Enhanced Reasoning Power 11;207
7.3.8;5.3.8 Camera Ontology Written Using OWL 1;207
7.4;5.4 OWL 2 Web Ontology Language;211
7.4.1;5.4.1 What Is New in OWL 2?;211
7.4.2;5.4.2 New Constructs for Common Patterns;212
7.4.2.1;5.4.2.1 Common Pattern: Disjointness;212
7.4.2.2;5.4.2.2 Common Pattern: Negative Assertions;214
7.4.3;5.4.3 Improved Expressiveness for Properties;215
7.4.3.1;5.4.3.1 Property Self-Restriction;215
7.4.3.2;5.4.3.2 Property Self-Restriction: Enhanced Reasoning Power 12;216
7.4.3.3;5.4.3.3 Property Cardinality Restrictions;216
7.4.3.4;5.4.3.4 Property Cardinality Restrictions: Enhanced Reasoning Power 13;218
7.4.3.5;5.4.3.5 More About Property Characteristics: Reflexive, Irreflexive, and Asymmetric Properties;218
7.4.3.6;5.4.3.6 More About Property Characteristics: Enhanced Reasoning Power 14;220
7.4.3.7;5.4.3.7 Disjoint Properties;220
7.4.3.8;5.4.3.8 Disjoint Properties: Enhanced Reasoning Power 15;221
7.4.3.9;5.4.3.9 Property Chains;222
7.4.3.10;5.4.3.10 Property Chains: Enhanced Reasoning Power 16;224
7.4.3.11;5.4.3.11 Keys;224
7.4.3.12;5.4.3.12 Keys: Enhanced Reasoning Power 17;225
7.4.4;5.4.4 Extended Support for Datatypes;225
7.4.4.1;5.4.4.1 Wider Range of Supported Datatypes and Extra Built-In Datatypes;226
7.4.4.2;5.4.4.2 Restrictions on Datatypes and User-Defined Datatypes;226
7.4.4.3;5.4.4.3 Data Range Combinations;228
7.4.5;5.4.5 Punning and Annotations;229
7.4.5.1;5.4.5.1 Understanding Punning;229
7.4.5.2;5.4.5.2 OWL Annotations, Axioms About Annotation Properties;230
7.4.6;5.4.6 Other OWL 2 Features;233
7.4.6.1;5.4.6.1 Entity Declarations;233
7.4.6.2;5.4.6.2 Top and Bottom Properties;234
7.4.6.3;5.4.6.3 Imports and Versioning;234
7.4.7;5.4.7 OWL Constructs in Instance Documents;237
7.4.8;5.4.8 OWL 2 Profiles;241
7.4.8.1;5.4.8.1 Why We Need All These?;241
7.4.8.2;5.4.8.2 Assigning Semantics to OWL Ontology: Description Logic vs. RDF-Based Semantics;241
7.4.8.3;5.4.8.3 Three Faces of OWL 1;242
7.4.8.4;5.4.8.4 Understanding OWL 2 Profiles;244
7.4.8.5;5.4.8.5 OWL 2 EL, QL, and RL;245
7.4.9;5.4.9 Our Camera Ontology in OWL 2;248
7.5;5.5 Summary;253
8;6 SPARQL: Querying the Semantic Web;255
8.1;6.1 SPARQL Overview;255
8.1.1;6.1.1 SPARQL in Official Language;255
8.1.2;6.1.2 SPARQL in Plain English;256
8.1.3;6.1.3 Other Related Concepts: RDF Data Store, RDF Database, and Triple Store;257
8.2;6.2 Set up Joseki SPARQL Endpoint;258
8.3;6.3 SPARQL Query Language;261
8.3.1;6.3.1 The Big Picture;263
8.3.1.1;6.3.1.1 Triple Pattern;263
8.3.1.2;6.3.1.2 Graph Pattern;264
8.3.2;6.3.2 SELECT Query;266
8.3.2.1;6.3.2.1 Structure of a SELECT Query;266
8.3.2.2;6.3.2.2 Writing Basic SELECT Query;267
8.3.2.3;6.3.2.3 Using OPTIONAL Keyword for Matches;271
8.3.2.4;6.3.2.4 Using Solution Modifier;273
8.3.2.5;6.3.2.5 Using FILTER Keyword to Add Value Constraints;275
8.3.2.6;6.3.2.6 Using Union Keyword for Alternative Match;278
8.3.2.7;6.3.2.7 Working with Multiple Graphs;281
8.3.3;6.3.3 CONSTRUCT Query;286
8.3.4;6.3.4 DESCRIBE Query;288
8.3.5;6.3.5 ASK Query ;289
8.4;6.4 What Is Missing from SPARQL?;291
8.5;6.5 SPARQL 1.1;291
8.5.1;6.5.1 Introduction: What Is New?;291
8.5.2;6.5.2 SPARQL 1.1 Query;292
8.5.2.1;6.5.2.1 Aggregate Functions;292
8.5.2.2;6.5.2.2 Subqueries;294
8.5.2.3;6.5.2.3 Negation;295
8.5.2.4;6.5.2.4 Expressions with SELECT ;297
8.5.2.5;6.5.2.5 Property Paths;298
8.5.3;6.5.3 SPARQL 1.1 Update;299
8.5.3.1;6.5.3.1 Graph Update: Adding RDF Statements;300
8.5.3.2;6.5.3.2 Graph Update: Deleting RDF Statements;301
8.5.3.3;6.5.3.3 Graph Update: LOAD and CLEAR ;303
8.5.3.4;6.5.3.4 Graph Management: Graph Creation;303
8.5.3.5;6.5.3.5 Graph Management: Graph Removal;303
8.6;6.6 Summary;304
9;7 FOAF: Friend of a Friend;305
9.1;7.1 What Is FOAF and What It Does;305
9.1.1;7.1.1 FOAF in Plain English;305
9.1.2;7.1.2 FOAF in Official Language;306
9.2;7.2 Core FOAF Vocabulary and Examples;307
9.2.1;7.2.1 The Big Picture: FOAF Vocabulary;307
9.2.2;7.2.2 Core Terms and Examples;308
9.3;7.3 Create Your FOAF Document and Get into the Friend Circle;315
9.3.1;7.3.1 How Does the Circle Work?;315
9.3.2;7.3.2 Create Your FOAF Document;317
9.3.3;7.3.3 Get into the Circle: Publish Your FOAF Document;319
9.3.4;7.3.4 From Web Pages for Human Eyes to Web Pages for Machines;321
9.4;7.4 Semantic Markup: a Connection Between the Two Worlds;322
9.4.1;7.4.1 What Is Semantic Markup;322
9.4.2;7.4.2 Semantic Markup: Procedure and Example;322
9.4.3;7.4.3 Semantic Markup: Feasibility and Different Approaches;326
9.5;7.5 Summary;328
10;8 Semantic Markup at Work: Rich Snippets and SearchMonkey;329
10.1;8.1 Introduction;329
10.1.1;8.1.1 Prerequisite: How Does a Search Engine Work?;329
10.1.1.1;8.1.1.1 Basic Search Engine Tasks;329
10.1.1.2;8.1.1.2 Basic Search Engine Workflow;330
10.1.2;8.1.2 Rich Snippets and SearchMonkey;332
10.2;8.2 Rich Snippets by Google;333
10.2.1;8.2.1 What Is Rich Snippets: An Example;333
10.2.2;8.2.2 How Does It Work: Semantic Markup Using Microformats/RDFa;333
10.2.2.1;8.2.2.1 Rich Snippets Powered by Semantic Markup;333
10.2.2.2;8.2.2.2 Microformats Supported by Rich Snippets;335
10.2.2.3;8.2.2.3 Ontologies Supported by Rich Snippets;336
10.2.3;8.2.3 Test It Out Yourself;336
10.3;8.3 SearchMonkey from Yahoo;336
10.3.1;8.3.1 What Is SearchMonkey: An Example;337
10.3.2;8.3.2 How Does It Work: Semantic Markup Using Microformats/RDFa;338
10.3.2.1;8.3.2.1 SearchMonkey Architecture;339
10.3.2.2;8.3.2.2 Microformats Supported by SearchMonkey;343
10.3.2.3;8.3.2.3 Ontologies Supported by SearchMonkey;343
10.3.3;8.3.3 Test It Out Yourself;343
10.4;8.4 Summary;344
10.5;Reference;344
11;9 Semantic Wiki;345
11.1;9.1 Introduction: From Wiki to Semantic Wiki;345
11.1.1;9.1.1 What Is a Wiki?;345
11.1.2;9.1.2 From Wiki to Semantic Wiki;347
11.2;9.2 Adding Semantics to Wiki Site;349
11.2.1;9.2.1 Namespace and Category System;350
11.2.2;9.2.2 Semantic Annotation in Semantic MediaWiki;353
11.2.2.1;9.2.2.1 Semantic Annotation: Links;353
11.2.2.2;9.2.2.2 Semantic Annotation: Text;357
11.3;9.3 Using the Added Semantics;361
11.3.1;9.3.1 Browsing;361
11.3.1.1;9.3.1.1 FactBox;361
11.3.1.2;9.3.1.2 Semantic Browsing Interface;362
11.3.2;9.3.2 Wiki Site Semantic Search;364
11.3.2.1;9.3.2.1 Direct Wiki Query: Basics;364
11.3.2.2;9.3.2.2 Direct Wiki Query: Advanced Search;367
11.3.2.3;9.3.2.3 Displaying Information;369
11.3.3;9.3.3 Inferencing;370
11.4;9.4 Where Is the Semantics?;373
11.4.1;9.4.1 SWiVT: an Upper Ontology for Semantic Wiki;374
11.4.2;9.4.2 Understanding OWL/RDF Exports;376
11.4.3;9.4.3 Importing Ontology: a Bridge to Outside World;386
11.5;9.5 The Power of the Semantic Web;389
11.6;9.6 Use Semantic MediaWiki to Build Your Own Semantic Wiki;390
11.7;9.7 Summary;390
12;10 DBpedia;392
12.1;10.1 Introduction to DBpedia;392
12.1.1;10.1.1 From Manual Markup to Automatic Generation of Annotation;392
12.1.2;10.1.2 From Wikipedia to DBpedia;393
12.1.3;10.1.3 The Look and Feel of DBpedia: Page Redirect;395
12.2;10.2 Semantics in DBpedia DBpedia look and feel ;398
12.2.1;10.2. Infobox Template;398
12.2.2;10.2.2 Creating DBpedia Ontology;401
12.2.2.1;10.2.2.1 The Need for Ontology;401
12.2.2.2;10.2.2.2 Mapping Infobox Templates to Classes;403
12.2.2.3;10.2.2.3 Mapping Infobox Template Attributes to Properties;405
12.2.3;10.2.3 Infobox Extraction Methods;407
12.2.3.1;10.2.3.1 Generic Infobox Extraction Method;408
12.2.3.2;10.2.3.2 Mapping-Based Infobox Extraction Method;408
12.3;10.3 Accessing DBpedia Dataset;409
12.3.1;10.3.1 Using SPARQL to Query DBpedia;410
12.3.1.1;10.3.1.1 SPARQL Endpoints for DBpedia;410
12.3.1.2;10.3.1.2 Examples of Using SPARQL to Access DBpedia;411
12.3.2;10.3.2 Direct Download of DBpedia Datasets;414
12.3.2.1;10.3.2.1 The Wikipedia Datasets;414
12.3.2.2;10.3.2.2 DBpedia Core Datasets;414
12.3.2.3;10.3.2.3 Extended Datasets;418
12.3.3;10.3.3 Access DBpedia as Linked Data;419
12.4;10.4 Summary;421
12.5;Reference;421
13;11 Linked Open Data;422
13.1;11.1 The Concept of Linked Data and Its Basic Rules;422
13.1.1;11.1.1 The Concept of Linked Data;422
13.1.2;11.1.2 How Big Is the Web of Linked Data and the LOD Project;424
13.1.3;11.1.3 The Basic Rules of Linked Data;425
13.2;11.2 Publishing RDF Data on the Web;426
13.2.1;11.2.1 Identifying Things with URIs;426
13.2.1.1;11.2.1.1 Web Document, Information Resource, and URI;426
13.2.1.2;11.2.1.2 Non-information Resources and Their URIs;428
13.2.1.3;11.2.1.3 URIs for Non-information Resources: 303 URIs and Content Negotiation;429
13.2.1.4;11.2.1.4 URIs for Non-information Resources: Hash URIs;432
13.2.1.5;11.2.1.5 URIs for Non-information Resources: 303 URIs vs. Hash URIs;434
13.2.1.6;11.2.1.6 URI Aliases;434
13.2.2;11.2.2 Choosing Vocabularies for RDF Data;436
13.2.3;11.2.3 Creating Links to Other RDF Data;440
13.2.3.1;11.2.3.1 Basic Language Constructs to Create Links;440
13.2.3.2;11.2.3.2 Creating Links Manually;444
13.2.3.3;11.2.3.3 Creating Links Automatically;446
13.2.4;11.2.4 Serving Information as Linked Data;447
13.2.4.1;11.2.4.1 Minimum Requirements for Being Linked Open Data;447
13.2.4.2;11.2.4.2 Example: Publishing Linked Data on the Web;449
13.2.4.3;11.2.4.3 Make Sure You Have Done It Right;451
13.3;11.3 The Consumption of Linked Data;452
13.3.1;11.3.1 Discover Specific Target on the Linked Data Web;454
13.3.1.1;11.3.1.1 Semantic Web Search Engine for Human Eyes;454
13.3.1.2;11.3.1.2 Semantic Web Search Engine for Applications;456
13.3.2;11.3.2 Accessing the Web of Linked Data;458
13.3.2.1;11.3.2.1 Using a Linked Data Browser;458
13.3.2.2;11.3.2.2 Using SPARQL Endpoints;463
13.3.2.3;11.3.2.3 Accessing the Linked Data Web Programmatically;468
13.4;11.4 Linked Data Application;468
13.4.1;11.4.1 Linked Data Application Example: Revyu;469
13.4.1.1;11.4.1.1 Revyu: An Overview;469
13.4.1.2;11.4.1.2 Revyu: Why It Is Different;474
13.4.2;11.4.2 Web 2.0 Mashups vs. Linked Data Mashups;476
13.5;11.5 Summary;478
14;12 Building the Foundation for Development on the Semantic Web;480
14.1;12.1 Development Tools for the Semantic Web;480
14.1.1;12.1.1 Frameworks for the Semantic Web Applications;480
14.1.1.1;12.1.1.1 What Is a Framework and Why We Need It?;480
14.1.1.2;12.1.1.2 Jena;482
14.1.1.3;12.1.1.3 Sesame;482
14.1.1.4;12.1.1.4 Virtuoso;482
14.1.1.5;12.1.1.5 Redland;483
14.1.2;12.1.2 Reasoners for the Semantic Web Applications;484
14.1.2.1;12.1.2.1 What Is a Reasoner and Why We Need It?;484
14.1.2.2;12.1.2.2 Pellet;485
14.1.2.3;12.1.2.3 RacerPro;485
14.1.2.4;12.1.2.4 Jena;486
14.1.2.5;12.1.2.5 Virtuoso;486
14.1.3;12.1.3 Ontology Engineering Environments;487
14.1.3.1;12.1.3.1 What Is an Ontology Engineering Environment and Why We Need It?;487
14.1.3.2;12.1.3.2 Protégé;488
14.1.3.3;12.1.3.3 NeOn;489
14.1.3.4;12.1.3.4 TopBraid Composer;490
14.1.4;12.1.4 Other Tools: Search Engines for the Semantic Web;491
14.1.5;12.1.5 Where to Find More?;491
14.2;12.2 Semantic Web Application Development Methodology;491
14.2.1;12.2.1 From Domain Models to Ontology-Driven Architecture;491
14.2.1.1;12.2.1.1 Domain Models and MVC Architecture;491
14.2.1.2;12.2.1.2 The Uniqueness of Semantic Web Application Development;493
14.2.1.3;12.2.1.3 Ontology-Driven Software Development;495
14.2.1.4;12.2.1.4 Further Discussions;497
14.2.2;12.2.2 An Ontology Development Methodology Proposed by Noy and McGuinness;497
14.2.2.1;12.2.2.1 Basic Tasks and Fundamental Rules;497
14.2.2.2;12.2.2.2 Basic Steps of Ontology Development;498
14.2.2.3;12.2.2.3 Other Considerations;500
14.3;12.3 Summary;502
14.4;Reference;503
15;13 Jena: A Framework for Development on the Semantic Web;504
15.1;13.1 Jena: A Semantic Web Framework for Java;504
15.1.1;13.1.1 What Is Jena and What It Can Do for Us?;504
15.1.2;13.1.2 Getting Jena Package;505
15.1.3;13.1.3 Using Jena in Your Projects;508
15.1.3.1;13.1.3.1 Using Jena in Eclipse;508
15.1.3.2;13.1.3.2 Hello World! from Semantic Web Application;510
15.2;13.2 Basic RDF Model Operations;514
15.2.1;13.2.1 Creating an RDF Model;515
15.2.2;13.2.2 Reading an RDF Model;520
15.2.3;13.2.3 Understanding an RDF Model;522
15.3;13.3 Handling Persistent RDF Models;528
15.3.1;13.3.1 From In-memory Model to Persistent Model;528
15.3.2;13.3.2 Setting Up MySQL;529
15.3.3;13.3.3 Database-Backed RDF Models;530
15.3.3.1;13.3.3.1 Single Persistent RDF Model;530
15.3.3.2;13.3.3.2 Multiple Persistent RDF Models;535
15.4;13.4 Inferencing Using Jena;537
15.4.1;13.4.1 Jena Inferencing Model;537
15.4.2;13.4.2 Jena Inferencing Examples;538
15.5;13.5 Summary;544
16;14 Follow Your Nose: A Basic Semantic Web Agent;546
16.1;14.1 The Principle of Follow-Your-Nose Method;546
16.1.1;14.1.1 What Is Follow-Your-Nose Method?;546
16.1.2;14.1.2 URI Declarations, Open Linked Data, and Follow-Your-Nose Method;548
16.2;14.2 A Follow-Your-Nose Agent in Java;549
16.2.1;14.2.1 Building the Agent;549
16.2.2;14.2.2 Running the Agent;556
16.2.3;14.2.3 More Clues for Follow Your Nose;558
16.2.4;14.2.4 Can You Follow Your Nose on Traditional Web?;559
16.3;14.3 A Better Implementation of Follow-Your-Nose Agent: Using SPARQL Queries;561
16.3.1;14.3.1 In-memory SPARQL Operation;562
16.3.2;14.3.2 Using SPARQL Endpoints Remotely;566
16.4;14.4 Summary;569
17;15 More Application Examples on the Semantic Web;571
17.1;15.1 Building Your Circle of Trust: A FOAF Agent You Can Use;571
17.1.1;15.1.1 Who Is on Your E-mail List?;571
17.1.2;15.1.2 The Basic Idea;572
17.1.3;15.1.3 Building the EmailAddressCollector Agent;575
17.1.3.1;15.1.3.1 EmailAddressCollector ;575
17.1.3.2;15.1.3.2 Running the EmailAddressCollector Agent;583
17.1.4;15.1.4 Can You Do the Same for Traditional Web?;584
17.2;15.2 A ShopBot on the Semantic Web;585
17.2.1;15.2.1 A ShopBot We Can Have;585
17.2.2;15.2.2 A ShopBot We Really Want;586
17.2.2.1;15.2.2.1 How Does It Understand Our Needs?;586
17.2.2.2;15.2.2.2 How Does It Find the Next Candidate?;590
17.2.2.3;15.2.2.3 How Does It Decide Whether There Is a Match or Not?;593
17.2.3;15.2.3 Building Our ShopBot;595
17.2.3.1;15.2.3.1 Utility Methods and Class;595
17.2.3.2;15.2.3.2 Processing the Catalog Document;601
17.2.3.3;15.2.3.3 The Main Work Flow;605
17.2.3.4;15.2.3.4 Running Our ShopBot;609
17.2.4;15.2.4 Discussion: From Prototype to Reality;611
17.3;15.3 Summary;612
18;Index;613