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Contents
Preface

Overview
Installation Guide
Quick Start & Tours
Sample ODBC & JDBC Applications
Conceptual Overview
Administration
Data Access Interfaces
Virtual Database Engine
SQL Reference
Virtuoso Cluster Programming
SQL Procedure Language Guide
Database Event Hooks
Data Replication, Synchronization and Transformation Services
Web Application Development
XML Support
RDF Data Access and Data Management
Data Representation
SPARQL
RDF Graphs Security
Automated Generation of RDF Views over Relational Data Sources
RDF Insert Methods in Virtuoso
Integration Middleware
Linked Data
Inference Rules & Reasoning
RDF and Geometry
Performance Tuning
RDF Data Access Providers (Drivers)
Web Services
Runtime Hosting
Internet Services
Free Text Search
TPC C Benchmark Kit
Using Virtuoso with Tuxedo
Appendix
Virtuoso Functions Guide

Abstract

Starting with version 4.5, Virtuoso provides built-in support for SPARQL, the standard query language for RDF and the semantic web. Adoption of SPARQL with Virtuoso is effortless, as any existing SQL client applications and stored procedures can take advantage of SPARQL simply by using it in the place of or inside SQL queries. Additionally, Virtuoso offers the standard SPARQL protocol to HTTP clients. From version 5.0.7, Virtuoso can be used as the RDF store/query processor of the Jena and Sesame RDF frameworks.

This chapter discusses Virtuoso's RDF triple storage and query capabilities. This discusses storing RDF data as well as mapping existing relational data into RDF for SPARQL access. Numerous SPARQL language extensions and standard compliance are covered.

In this chapter SPARQL and SPASQL are used as siblings.

See Also:

Table of Contents

16.1. Data Representation
16.1.1. IRI_ID Type
16.1.2. RDF_BOX Type
16.1.3. RDF_QUAD and other tables
16.1.4. Short, Long and SQL Values
16.1.5. Programatically resolving DB.DBA.RDF_QUAD.O to SQL
16.1.6. Special Cases and XML Schema Compatibility
16.1.7. SQL Compiler Support - QUIETCAST option
16.1.8. Dynamic Renaming of Local IRI's
16.2. SPARQL
16.2.1. SPARQL Implementation Details
16.2.2. Query Constructs
16.2.3. SPARQL Web Services & APIs
16.2.4. Troubleshooting SPARQL Queries
16.2.5. Extensions
16.2.6. SPARQL Inline in SQL
16.2.7. API Functions
16.2.8. Useful Internal Functions
16.2.9. Default and Named Graphs
16.2.10. Calling SQL from SPARQL
16.2.11. SPARQL DESCRIBE
16.2.12. Transitivity in SPARQL
16.3. RDF Graphs Security
16.3.1. RDF Graph Groups
16.3.2. NOT FROM and NOT FROM NAMED Clauses
16.3.3. Graph-Level Security
16.3.4. Understanding Default Permissions
16.3.5. Initial Configuration of SPARQL Security
16.3.6. Application Callbacks for Graph Level Security
16.4. Automated Generation of RDF Views over Relational Data Sources
16.4.1. Introduction
16.4.2. One Click Linked Data Generation & Deployment
16.4.3. Manual Linked Data Generation & Deployment using the Conductor's HTML-based wizard
16.5. RDF Insert Methods in Virtuoso
16.5.1. Using API functions
16.5.2. HTTP Post using Content-Type: application/sparql-query
16.5.3. HTTP PUT using Content-Type: application/rdf+xml
16.5.4. SPARQL Insert using LOAD
16.5.5. SPARQL Insert via /sparql endpoint
16.5.6. SPARQL Insert via HTTP Post using Content-Type: application/sparql-query and ODS wiki
16.5.7. Using WebDAV
16.5.8. Using Virtuoso Crawler
16.5.9. Using SPARQL Query and Sponger (i.e. we Sponge the Resources in the FROM Clause or values for the graph-uri parameter in SPARQL protocol URLs)
16.5.10. Using Virtuoso PL APIs
16.5.11. Using SIMILE RDF Bank API
16.5.12. Using RDF NET
16.5.13. Using the RDF Proxy (Sponger) Service
16.6. Integration Middleware
16.6.1. RDFizer Middleware (Sponger)
16.6.2. Enterprise Data Access & Integration
16.6.3. RDF Views over RDBMS Data Source
16.7. Linked Data
16.7.1. IRI Dereferencing For FROM Clauses, "define get:..." Pragmas
16.7.2. IRI Dereferencing For Variables, "define input:grab-..." Pragmas
16.7.3. URL rewriting
16.7.4. Examples of other Protocol Resolvers
16.7.5. Faceted Views over Large-Scale Linked Data
16.8. Inference Rules & Reasoning
16.8.1. Introduction
16.8.2. Making Rule Sets
16.8.3. Changing Rule Sets
16.8.4. Subclasses and Subproperties
16.8.5. OWL sameAs Support
16.8.6. Implementation
16.8.7. Enabling Inferencing
16.8.8. Examples
16.8.9. Identity With Inverse Functional Properties
16.8.10. Inference Rules and SPARQL with Transitivity Option
16.8.11. Inference Rules, OWL Support and Relationship Ontology
16.9. RDF and Geometry
16.9.1. Programmatic Manipulation of Geometries in RDF
16.9.2. Creating Geometries From RDF Data
16.9.3. Using Geometries With Existing Databases
16.9.4. GEO Spatial Examples
16.10. Performance Tuning
16.10.1. General
16.10.2. RDF Index Scheme
16.10.3. Index Scheme Selection
16.10.4. Dump and Reload Graphs
16.10.5. Erroneous Cost Estimates and Explicit Join Order
16.10.6. Loading
16.10.7. Using SPARUL
16.10.8. DBpedia Benchmark
16.10.9. RDF Store Benchmarks
16.11. RDF Data Access Providers (Drivers)
16.11.1. Virtuoso Jena Provider
16.11.2. Virtuoso Sesame Provider
16.11.3. Virtuoso Redland Provider