Learning SPARQL

Table of contents

1. Dedication
2. Preface
   1. Why Learn SPARQL?
   2. Organization of This Book
   3. Conventions Used in This Book
   4. Documentation Conventions
   5. Using Code Examples
   6. Safari® Books Online
   7. How to Contact Us
   8. Acknowledgments
3. 1. Jumping Right In: Some Data and Some Queries
   1. The Data to Query
   2. Querying the Data
   3. More Realistic Data and Matching on Multiple Triples
   4. Searching for Strings
   5. What Could Go Wrong?
   6. Querying a Public Data Source
   7. Summary
4. 2. The Semantic Web, RDF, and Linked Data (and SPARQL)
   1. What Exactly Is the “Semantic Web”?
   2. URLs, URIs, IRIs, and Namespaces
   3. The Resource Description Format (RDF)
      1. Storing RDF in Files
      2. Storing RDF in Databases
      3. Data Typing
      4. Making RDF More Readable with Language Tags and Labels
      5. Blank Nodes and Why They’re Useful
      6. Named Graphs
   4. Reusing and Creating Vocabularies: RDF Schema and OWL
   5. Linked Data
   6. SPARQL’s Past, Present, and Future
   7. The SPARQL Specifications
   8. Summary
5. 3. SPARQL Queries: A Deeper Dive
   1. More Readable Query Results
      1. Using the Labels Provided by DBpedia
      2. Getting Labels from Schemas and Ontologies
   2. Data That Might Not Be There
   3. Finding Data That Doesn’t Meet Certain Conditions
   4. Searching Further in the Data
   5. Searching with Blank Nodes
   6. Eliminating Redundant Output
   7. Combining Different Search Conditions
   8. FILTERing Data Based on Conditions
   9. Retrieving a Specific Number of Results
   10. Querying Named Graphs
   11. Queries in Your Queries
   12. Combining Values and Assigning Values to Variables
   13. Sorting, Aggregating, Finding the Biggest and Smallest and...
       1. Sorting Data
       2. Finding the Smallest, the Biggest, the Count, the Average...
       3. Grouping Data and Finding Aggregate Values within Groups
   14. Querying a Remote SPARQL Service
   15. Federated Queries: Searching Multiple Datasets with One Query
   16. Summary
6. 4. Copying, Creating, and Converting Data (and Finding Bad Data)
   1. Query Forms: SELECT, DESCRIBE, ASK, and CONSTRUCT
   2. Copying Data
   3. Creating New Data
   4. Converting Data
   5. Finding Bad Data
      1. Defining Rules with SPARQL
      2. Generating Data About Broken Rules
      3. Using Existing SPARQL Rules Vocabularies
   6. Asking for a Description of a Resource
   7. Summary
7. 5. Datatypes and Functions
   1. Datatypes and Queries
      1. Representing Strings
      2. Comparing Values and Doing Arithmetic
   2. Functions
      1. Program Logic Functions
      2. Node Type and Datatype Checking Functions
      3. Node Type Conversion Functions
      4. Datatype Conversion
      5. Checking, Adding, and Removing Spoken Language Tags
      6. String Functions
      7. Numeric Functions
      8. Date and Time Functions
      9. Hash Functions
   3. Extension Functions
   4. Summary
8. 6. Updating Data with SPARQL
   1. Getting Started with Fuseki
   2. Adding Data to a Dataset
   3. Deleting Data
   4. Changing Existing Data
   5. Named Graphs
      1. Dropping Graphs
      2. Named Graph Syntax Shortcuts: WITH and USING
      3. Deleting and Replacing Triples in Named Graphs
   6. Summary
9. 7. Building Applications with SPARQL: A Brief Tour
   1. SPARQL and Web Application Development
   2. SPARQL Query Results XML Format
   3. SPARQL Processors
      1. Standalone Processors
      2. Triplestore SPARQL Support
      3. Middleware SPARQL Support
      4. Public Endpoints, Private Endpoints
   4. Summary
10. Glossary
11. Index
12. About the Author
13. Colophon
14. Copyright