You are previewing Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked Open Data.
O'Reilly logo
Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked Open Data

Book Description

A major limitation of conventional web sites is their unorganized and isolated contents, which is created mainly for human consumption. This limitation can be addressed by organizing and publishing data, using powerful formats that add structure and meaning to the content of web pages and link related data to one another. Computers can ""understand"" such data better, which can be useful for task automation. The web sites that provide semantics (meaning) to software agents form the Semantic Web, the Artificial Intelligence extension of the World Wide Web. In contrast to the conventional Web (the ""Web of Documents""), the Semantic Web includes the ""Web of Data"", which connects ""things"" (representing real-world humans and objects) rather than documents meaningless to computers. Mastering Structured Data on the Semantic Web explains the practical aspects and the theory behind the Semantic Web and how structured data, such as HTML5 Microdata and JSON-LD, can be used to improve your site’s performance on next-generation Search Engine Result Pages and be displayed on Google Knowledge Panels. You will learn how to represent arbitrary fields of human knowledge in a machine-interpretable form using the Resource Description Framework (RDF), the cornerstone of the Semantic Web. You will see how to store and manipulate RDF data in purpose-built graph databases such as triplestores and quadstores, that are exploited in Internet marketing, social media, and data mining, in the form of Big Data applications such as the Google Knowledge Graph, Wikidata, or Facebook’s Social Graph.

With the constantly increasing user expectations in web services and applications, Semantic Web standards gain more popularity. This book will familiarize you with the leading controlled vocabularies and ontologies and explain how to represent your own concepts. After learning the principles of Linked Data, the five-star deployment scheme, and the Open Data concept, you will be able to create and interlink five-star Linked Open Data, and merge your RDF graphs to the LOD Cloud. The book also covers the most important tools for generating, storing, extracting, and visualizing RDF data, including, but not limited to, Protégé, TopBraid Composer, Sindice, Apache Marmotta, Callimachus, and Tabulator. You will learn to implement Apache Jena and Sesame in popular IDEs such as Eclipse and NetBeans, and use these APIs for rapid Semantic Web application development. Mastering Structured Data on the Semantic Web demonstrates how to represent and connect structured data to reach a wider audience, encourage data reuse, and provide content that can be automatically processed with full certainty. As a result, your web contents will be integral parts of the next revolution of the Web.

Table of Contents

  1. Cover
  2. Title
  3. Copyright
  4. Contents at a Glance
  5. Contents
  6. About the Author
  7. About the Technical Reviewer
  8. Preface
  9. Chapter 1: Introduction to the Semantic Web
    1. The Semantic Web
      1. Structured Data
    2. Semantic Web Components
      1. Ontologies
      2. Inference
    3. Semantic Web Features
      1. Free, Open Access Data Repositories
      2. Adaptive Information
      3. Unique Web Resource Identifiers
    4. Summary
    5. References
  10. Chapter 2: Knowledge Representation
    1. Vocabularies and Ontologies
      1. The Vocabulary Collection
      2. General, Access, and Structural Metadata
      3. Person Vocabularies
      4. Book Vocabularies
      5. PRISM: A Publishing Vocabulary
      6. GoodRelations: An E-commerce Ontology
      7. Publication Ontologies
      8. DOAP: A Project Management Vocabulary
      9. Licensing Vocabularies
      10. Media Ontologies
      11. Vocabularies for Online Communities
    2. Knowledge Management Standards
      1. Resource Description Framework (RDF)
      2. Machine-Readable Annotations
      3. GRDDL: XML Documents to RDF
      4. R2RML: Relational Databases to RDF
      5. RDFS
      6. Web Ontology Language (OWL)
      7. Simple Knowledge Organization System (SKOS)
      8. Rule Interchange Format (RIF)
    3. Reasoning
    4. Parsers
    5. Summary
    6. References
  11. Chapter 3: Linked Open Data
    1. Linked Data Principles
    2. The Five-Star Deployment Scheme for Linked Data
    3. LOD Datasets
      1. RDF Crawling
      2. RDF Dumps
      3. SPARQL Endpoints
      4. Frequently Used Linked Datasets
      5. LOD Dataset Collections
      6. The LOD Cloud Diagram
    4. Creating LOD Datasets
      1. RDF Structure
      2. Licensing
      3. RDF Statements
      4. Interlinking
      5. Registering Your Dataset
    5. Linked Data Visualization
    6. Summary
    7. References
  12. Chapter 4: Semantic Web Development Tools
    1. Advanced Text Editors
    2. Semantic Annotators and Converters
      1. RDFa Play
      2. RDFa 1.1 Distiller and Parser
      3. RDF Distiller
      4. DBpedia Spotlight
      5. Google Structured Data Testing Tool
    3. RDFizers
      1. Apache Any23
      2. General Architecture for Text Engineering (GATE)
      3. OpenRefine
    4. Ontology Editors
      1. Protégé
      2. SemanticWorks
      3. TopBraid Composer
      4. Apache Stanbol
      5. Fluent Editor
    5. Ontology Analysis Tools
      1. ZOOMA
      2. Semantic Measures Library
    6. Reasoners
      1. HermiT
      2. Pellet
      3. FaCT++
      4. RACER
    7. Application Development Frameworks
      1. Jena
      2. Sesame
    8. Integrated Development Environments
      1. Eclipse
      2. NetBeans
      3. CubicWeb
    9. Linked Data Software
      1. Sindice
      2. Apache Marmotta
      4. Callimachus
      5. Neologism
      6. LODStats
    10. Semantic Web Browsers
      1. Tabulator
      2. Marbles
      3. OpenLink Data Explorer (ODE)
      4. DBpedia Mobile
      5. IsaViz
      6. RelFinder
    11. Summary
    12. References
  13. Chapter 5: Semantic Web Services
    1. Semantic Web Service Modeling
      1. Communication with XML Messages: SOAP
      2. Web Services Description Language (WSDL)
      3. Web Ontology Language for Services (OWL-S)
      4. Web Service Modeling Ontology (WSMO)
      5. Web Service Modeling Language (WSML)
      6. Web Services Business Process Execution Language (WS-BPEL)
    2. Semantic Web Service Software
      1. Web Service Modeling eXecution environment (WSMX)
      2. Internet Reasoning Service (IRS-III)
      3. Web Services Modeling Toolkit (WSMT)
      4. Semantic Automated Discovery and Integration (SADI)
    3. UDDI Semantic Web Service Listings
    4. Summary
    5. References
  14. Chapter 6: Graph Databases
    1. Graph Databases
      1. Triplestores
      2. Quadstores
    2. The Most Popular Graph Databases
      1. AllegroGraph
      2. Neo4j
      3. 4Store
      4. Oracle
    3. Summary
    4. References
  15. Chapter 7: Querying
    1. SPARQL: The Query Language for RDF
      1. Structure and Syntax
      2. SPARQL 1.0 and SPARQL 1.1
      3. Query Types
      4. Pattern Matching
      5. Solution Modifiers
      6. SELECT Queries
      7. ASK Queries
      8. CONSTRUCT Queries
      9. DESCRIBE Queries
      10. Federated Queries
      11. REASON Queries
      12. URL Encoding of SPARQL Queries
      13. Graph Update Operations
      14. Graph Management Operations
    2. Proprietary Query Engines and Query Languages
      1. SeRQL: The Sesame RDF Query Language
      2. CQL: Neo4j’s Query Language
    3. Identify Datasets to Query
    4. Public SPARQL Endpoints
    5. Setting Up Your Own SPARQL Endpoint
      1. OpenLink Virtuoso
      2. Fuseki
      3. D2R
      4. 4store SPARQL Server
      5. PublishMyData
    6. Summary
    7. References
  16. Chapter 8: Big Data Applications
    1. Big Semantic Data: Big Data on the Semantic Web
    2. Google Knowledge Graph and Knowledge Vault
      1. Get Your Company, Products, and Events into the Knowledge Graph
    3. Social Media Applications
      1. Facebook Social Graph
      2. Twitter Cards
    4. IBM Watson
    5. BBC’s Dynamic Semantic Publishing
    6. The Library of Congress Linked Data Service
    7. High-Performance Storage: The One Trillion Triples Mark
    8. Summary
    9. References
  17. Chapter 9: Use Cases
    1. RDB to RDF Direct Mapping
    2. A Semantic Web Service Process in OWL-S to Charge a Credit Card
    3. Modeling a Travel Agency Web Service with WSMO
    4. Querying DBpedia Using the RDF API of Jena
    5. Summary
    6. References
  18. Index