Oracle Spatial and Graph
RDF Semantic Graph - Training





Introductory Information on RDF/OWL




Tutorials and Other Conference Materials



Oracle Training


Please note that all of the tutorials and examples below require the following products: Oracle Database 11g Enterprise Edition, Oracle Spatial 11g Option, and Oracle Partitioning Option.


Oracle By Example Online Developer Training—RDF Semantic Data Management

Using the Oracle Spatial 11g Option July 2008

The NCI Ontology Is Used In This Example

This tutorial explains how to use Oracle Semantic Technologies to load, inference and query an ontology in Oracle Database using the National Cancer Institute (NCI) Semantic Network Ontology.


Hands On Lab—A Little Semantics Goes a Long Way With Oracle Database 11g



A Hands On Lab, by J Phil Brooks, Information Consultant, SE Data Team, Discover IT, Eli Lilly and Company.


Oracle Database Semantic Technologies: Understanding How to Install, Load, Query and Inference



A three hour workshop on Oracle Database Semantic Technologies given at the June 2011 Semantic Technologies Conference held in San Francisco, CA.


Tutorial—Oracle Database 11g Release 2 Semantic Technologies:

Using the Jena Adaptor for Oracle Database October 2009

This tutorial shows how to apply Jena APIs to the Semantic Technologies features of the Oracle Spatial Option by utilizing the Jena Adaptor for Oracle Database.


Tutorial—Oracle Database 11g Release 2 Semantic Technologies


Semantic Indexing for Documents October 2009

This tutorial shows how to use the Semantic Technologies features of the Oracle Spatial Option to semantically index documents stored in relational tables and search for these documents using SPARQL-based document search criteria. The OpenCalais semantic metadata extraction service from Thomson Reuters is used to extract information from the documents for indexing in Oracle Database.


Oracle By Example Online Developer Training—Converting Relational Data Into RDF Format

This Oracle By Example shows how to convert relational data to the W3C RDF graph data format.




Reference Materials

  • Supporting Keyword Columns with Ontology-based Referential Constraints in DBMS—The IEEE Computer Society selected Oracle's paper "Supporting Keyword Columns with Ontology-based Referential Constraints in DBMS" (PDF 79KB), by Eugene Chong, Souri Das, George Eadon and Jags Srinivasan as the winner of the Best Industrial Paper Award at the 2006 International Conference on Data Engineering. The associated presentation by Souri Das is also available. (PDF 111KB)
  • An Efficient SQL-based RDF Querying Scheme—Proceedings of the 31st VLDB Conference, Trondheim, Norway, 2005—This VLDB Conference paper proposes a SQL based scheme for querying RDF data. Specifically, the RDF_MATCH table function is introduced with the ability to perform pattern-based match against RDF data (graph). The expectation is that providing RDF querying capability as part of SQL will enable a database system to support a wider range of applications and facilitate building semantically rich applications. (PDF 154KB)
  • Supporting Ontology-based Semantic Matching in RDMS—By Souripriya Das, Eugene Inseok Chong, George Eadon, Jagannathan Srinivasan, Proceedings of the 30th VLDB Conference, Toronto, Canada. Ontologies are increasingly being used to build applications that utilize domain-specific knowledge. This paper addresses the problem of supporting ontology-based semantic matching in RDBMS. The approach enables users to reference ontology data directly from SQL using the semantic match operators, thereby opening up possibilities of combining with other operations such as joins as well as making the ontology-driven applications easy to develop and efficient. In contrast, other approaches use RDBMS only for storage of ontologies and querying of ontology data is typically done via APIs. This paper presents the ontology-related functionality including inferencing, discusses how it is implemented on top of Oracle RDBMS, and illustrates the usage with several database applications. (PDF 97KB)
  • Applying Semantic Web Technologies to Drug Safety Determination—Identifying signals of events that lead to undesirable outcomes is historically one of the most challenging aspects of determining drug safety, both during the drug discovery and development process and once a drug is released to the market....The Semantic Web provides new capabilities for data integration that exploits explicit semantics and well-defined ontologies...The Oracle RFD Data model integrated with Cerebra Server is a composite solution that addresses the complexities of mediating information in drug safety. A use case illustrates the situation and how the composite solution might help. (PDF 166KB)