Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today.
The Semantic Web treats data as a distributed resource on the scale of the World Wide Web, and incorporates features to address the challenges of massive data distribution as part of its basic design. The aim of the first two editions was to motivate the Semantic Web technology stack from end-to-end; to describe not only what the Semantic Web standards are and how they work, but also what their goals are and why they were designed as they are. It tells a coherent story from beginning to end of how the standards work to manage a world-wide distributed web of knowledge in a meaningful way.
The third edition builds on this foundation to bring Semantic Web practice to enterprise. Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. While the overall story is the same, the examples have been brought up to date and applied in a modern setting, where enterprise and global data come together as a living, linked network of data. Also included with the third edition, all of the data sets and queries are available online for study and experimentation at data.world/swwo.
Author(s): Dean Allemang; Fabien Gandon; James A. Hendler
Series: ACM books
Edition: Third
Year: 2020
Book.pdf
Semantic Web for the Working Ontologist
Contents
Preface
1 What Is the Semantic Web?
1.1 What Is a Web?
1.2 Communicating with Data
1.3 Distributed Data
1.4 Summary
2 Semantic Modeling
2.1 Modeling for Human Communication
2.2 Explanation and Prediction
2.3 Mediating Variability
2.4 Expressivity in Modeling
2.5 Summary
3 RDF—The Basis of the Semantic Web
3.1 Distributing Data Across the Web
3.2 Merging Data from Multiple Sources
3.3 Namespaces, URIs, and Identity
3.4 Identifiers in the RDF Namespace
3.5 CHALLENGES: RDF and Tabular Data
3.6 Higher-Order Relationships
3.7 Naming RDF Graphs
3.8 Alternatives for Serialization
3.9 Blank Nodes
3.10 Summary
4 Semantic Web Application Architecture
4.1 RDF Parser/Serializer
4.2 RDF Store
4.3 Application Code
4.4 Data Federation
4.5 Summary
5 Linked Data
5.1 Weaving a Web of Data
5.2 HTTP and the Architecture of the Web
5.3 Hash or Slash
5.4 See It for Yourself…
5.5 Summary
6 Querying the Semantic Web—SPARQL
6.1 Tell-and-Ask Systems
6.2 RDF as a Tell-and-Ask System
6.3 SPARQL—Query Language for RDF
6.4 CONSTRUCT Queries in SPARQL
6.5 Using Results of CONSTRUCT Queries
6.6 SPARQL Rules—Using SPARQL as a Rule Language
6.7 Transitive queries (SPARQL 1.1)
6.8 Advanced Features of SPARQL
6.9 Summary
7 Extending RDF: RDFS and SCHACL
7.1 Inference in RDF with RDFS
7.2 Where are the Smarts?
7.3 When Does Inferencing Happen?
7.4 Expectation in RDF
7.5 Summary
8 RDF Schema
8.1 Schema Languages and Their Functions
8.2 The RDF Schema Language
8.3 RDFS Modeling Combinations and Patterns
8.4 Challenges
8.5 Modeling with Domains and Ranges
8.6 Nonmodeling Properties in RDFS
8.7 Summary
9 RDFS-Plus
9.1 Inverse
9.2 Managing Networks of Dependencies
9.3 Equivalence
9.4 Merging Data from Different Databases
9.5 Computing Sameness: Functional Properties
9.6 A Few More Constructs
9.7 Summary
10 Using RDFS-Plus in the Wild
10.1 Schema.org
10.2 Open Government Data
10.3 FOAF
10.4 Facebook's Open Graph Protocol
10.5 Summary
11 SKOS—Managing Vocabularies with RDFS-Plus
11.1 Simple Knowledge Organization System (SKOS)
11.2 Semantic Relations in SKOS
11.3 Concept Schemes
11.4 SKOS Integrity
11.5 SKOS in Action
11.6 Summary
12 Basic OWL
12.1 Restrictions
12.2 Challenge Problems
12.3 Alternative Descriptions of Restrictions
12.4 Summary
13 Counting and Sets in OWL
13.1 Unions and Intersections
13.2 Differentiating Multiple Individuals
13.3 Cardinality
13.4 Set Complement
13.5 Disjoint Sets
13.6 Prerequisites Revisited
13.7 Contradictions
13.8 Unsatisfiable Classes
13.9 Inferring Class Relationships
13.10 Reasoning with Individuals and with Classes
13.11 Summary
14 Ontologies on the Web—Putting It All Together
14.1 Ontology Architecture
14.2 Quantities, Units, Dimensions, and Types
14.3 Biological Ontologies
14.4 FIBO—The Financial Industry Business Ontology
14.5 Summary
15 Good and Bad Modeling Practices
15.1 Getting Started
15.2 Good Naming Practices
15.3 Common Modeling Errors
15.4 Summary
16 Expert Modeling in OWL
16.1 OWL Subsets and Modeling Philosophy
16.2 OWL 2 Modeling Capabilities
16.3 Summary
17 Conclusions and Future Work
Bibliography
Authors' Biographies
Index
