Semantic web for the working ontologist : effective modeling for linked data, RDFS, and OWL

Description

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. 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