Learning SPARQL querying and updating with SPARQL 1.1
Get hands-on experience with SPARQL, the RDF query language that's become a key component of the semantic web. With this concise book, you will learn how to use the latest version of this W3C standard to retrieve and manipulate the increasing amount of public and private data available via SPA...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Beijing :
Sebastopol, California
2011.
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| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628039406719 |
Tabla de Contenidos:
- Table of Contents; Preface; Why Learn SPARQL?; Organization of This Book; Conventions Used in This Book; Documentation Conventions; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Chapter 1. Jumping Right In: Some Data and Some Queries; The Data to Query; Querying the Data; More Realistic Data and Matching on Multiple Triples; Searching for Strings; What Could Go Wrong?; Querying a Public Data Source; Summary; Chapter 2. The Semantic Web, RDF, and Linked Data (and SPARQL); What Exactly Is the "Semantic Web"?; URLs, URIs, IRIs, and Namespaces
- The Resource Description Format (RDF)Storing RDF in Files; Storing RDF in Databases; Data Typing; Making RDF More Readable with Language Tags and Labels; Blank Nodes and Why They're Useful; Named Graphs; Reusing and Creating Vocabularies: RDF Schema and OWL; Linked Data; SPARQL's Past, Present, and Future; The SPARQL Specifications; Summary; Chapter 3. SPARQL Queries: A Deeper Dive; More Readable Query Results; Using the Labels Provided by DBpedia; Getting Labels from Schemas and Ontologies; Data That Might Not Be There; Finding Data That Doesn't Meet Certain Conditions
- Searching Further in the DataSearching with Blank Nodes; Eliminating Redundant Output; Combining Different Search Conditions; FILTERing Data Based on Conditions; Retrieving a Specific Number of Results; Querying Named Graphs; Queries in Your Queries; Combining Values and Assigning Values to Variables; Sorting, Aggregating, Finding the Biggest and Smallest and...; Sorting Data; Finding the Smallest, the Biggest, the Count, the Average...; Grouping Data and Finding Aggregate Values within Groups; Querying a Remote SPARQL Service; Federated Queries: Searching Multiple Datasets with One Query
- SummaryChapter 4. Copying, Creating, and Converting Data (and Finding Bad Data); Query Forms: SELECT, DESCRIBE, ASK, and CONSTRUCT; Copying Data; Creating New Data; Converting Data; Finding Bad Data; Defining Rules with SPARQL; Generating Data About Broken Rules; Using Existing SPARQL Rules Vocabularies; Asking for a Description of a Resource; Summary; Chapter 5. Datatypes and Functions; Datatypes and Queries; Representing Strings; Comparing Values and Doing Arithmetic; Functions; Program Logic Functions; Node Type and Datatype Checking Functions; Node Type Conversion Functions
- Datatype ConversionChecking, Adding, and Removing Spoken Language Tags; String Functions; Numeric Functions; Date and Time Functions; Hash Functions; Extension Functions; Summary; Chapter 6. Updating Data with SPARQL; Getting Started with Fuseki; Adding Data to a Dataset; Deleting Data; Changing Existing Data; Named Graphs; Dropping Graphs; Named Graph Syntax Shortcuts: WITH and USING; Deleting and Replacing Triples in Named Graphs; Summary; Chapter 7. Building Applications with SPARQL: A Brief Tour; SPARQL and Web Application Development; SPARQL Query Results XML Format; SPARQL Processors
- Standalone Processors
