Oracle Graph support for semantic technologies consists mainly of Resource Description Framework (RDF) and a subset of the Web Ontology Language (OWL). These capabilities are referred to as the RDF Graph feature of Oracle Graph.

The RDF Graph feature enables you to create one or more RDF networks in an Oracle database. Each network contains RDF data.

This chapter assumes that you are familiar with the major concepts associated with RDF and OWL, such as {subject, predicate, object} triples, {subject, predicate, object, graph} quads, URIs, blank nodes, plain and typed literals, and ontologies. It does not explain these concepts in detail, but focuses instead on how the concepts are implemented in Oracle.

• For an excellent explanation of RDF concepts, see the World Wide Web Consortium (W3C) RDF Primer at http://www.w3.org/TR/rdf-primer/.

• For information about OWL, see the OWL Web Ontology Language Reference at http://www.w3.org/TR/owl-ref/.

The PL/SQL subprograms for working with RDF data are in the SEM_APIS package, which is documented in SEM_APIS Package Subprograms.

The RDF and OWL support are features of Oracle Graph, which must be installed for these features to be used. However, the use of RDF and OWL is not restricted to spatial data.

For information about OWL concepts and the Oracle Database support for OWL capabilities, see OWL Concepts .

• Introduction to Oracle Semantic Technologies Support
  Oracle Database enables you to store RDF data and ontologies, to query RDF data and to perform ontology-assisted query of enterprise relational data, and to use supplied or user-defined inferencing to expand the power of querying on RDF data.
• Key Terms and Concepts for Working with RDF Graphs
  Learn the Oracle terminology and the concepts for working with the RDF graph feature in Oracle Database.
• RDF Data Modeling
  In addition to its formal semantics, RDF data has a simple data structure that is effectively modeled using a directed graph.
• RDF Data in the Database
  RDF data in Oracle Database is stored in one or more RDF networks.
• RDF Metadata Tables and Views
  Oracle Database maintains several tables and views in the network owner’s schema to hold metadata related to RDF data.
• RDF Data Types, Constructors, and Methods
  The SDO_RDF_TRIPLE_S object type is used for representing the edges (that is, triples and quads) of RDF graphs.
• Using the SEM_MATCH Table Function to Query RDF Data
  To query RDF data, use the SEM_MATCH table function.
• Speeding up Query Execution with Result Tables
  Result tables are auxiliary tables that store the results for generic patterns of SPARQL queries executed against an RDF graph or RDF graph collection.
• Using the SEM_APIS.SPARQL_TO_SQL Function to Query RDF Data
  You can use the SEM_APIS.SPARQL_TO_SQL function as an alternative to the SEM_MATCH table function to query RDF data.
• Using the SEM_APIS.GET_SQL Function and SEM_SQL SQL Macro to Query RDF Data
  You can use the SEM_APIS.GET_SQL function as an alternative to the SEM_MATCH table function to query RDF data.
• Loading and Exporting RDF Data
  You can load RDF data into an RDF graph in the database and export that data from the database into a staging table.
• Using RDF Network Indexes
  RDF network indexes are nonunique B-tree indexes that you can add, alter, and drop for use with RDF graphs and inferred graphs in a RDF network.
• Using Data Type Indexes
  Data type indexes are indexes on the values of typed literals stored in an RDF network.
• Managing Statistics for the RDF Graphs and RDF Network
  Statistics are critical to the performance of SPARQL queries and OWL inference against RDF data stored in an Oracle database.
• Support for SPARQL Update Operations on an RDF Graph
  Effective with Oracle Database Release 12.2, you can perform SPARQL Update operations on an RDF graph.
• RDF Support for Oracle Database In-Memory
  RDF can use the in-memory Oracle Database In-Memory suite of features, including in-memory column store, to improve performance for real-time analytics and mixed workloads.
• RDF Support for Materialized Join Views
  The most frequently used joins in RDF queries are subject-subject and subject-object joins. To enhance the RDF query performance, you can create materialized join views on those two columns.
• RDF Support in Oracle SQL Developer
  You can use Oracle SQL Developer to perform operations related to the RDF Knowledge Graph feature of Oracle Graph.
• Enhanced RDF ORDER BY Query Processing
  Effective with Oracle Database Release 12.2, queries on RDF data that use SPARQL ORDER BY semantics are processed more efficiently than in previous releases.
• Applying Oracle Machine Learning Algorithms to RDF Data
  You can apply Oracle Machine Learning algorithms to RDF data.
• RDF Graph Management Examples (PL/SQL and Java)
  PL/SQL examples are provided in this topic.
• Software Naming Changes Since Release 11.1
  Because the support for RDF data has been expanded beyond the original focus on RDF, the names of many software objects (PL/SQL packages, functions and procedures, system tables and views, and so on) have been changed as of Oracle Database Release 11.1.
• For More Information About RDF Graph
  More information is available about RDF graph support and related topics.
• Required Migration of Pre-12.2 RDF Data
  If you have any RDF data created using Oracle Database 11.1. 11.2, or 12.1, then before you use it in an Oracle Database 12.2 environment, you must migrate this data.
• Oracle RDF Graph Features that Support Accessibility
  This section describes the accessibility support provided by Oracle RDF Graph features.