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Contents
List of Examples
List of Figures
List of Tables
Title and Copyright Information
Preface
Audience
Documentation Accessibility
Related Documents
Conventions
What's New in Semantic Technologies?
Features Added for Release 11.1.0.7 (November, 2008)
Storage Model Enhancements and Migration
Support for OWL Inferencing
New Bulk Loading Interface for Improved Performance
Ontology-Assisted Querying of Relational Data
Required Procedure for Using Semantic Technology Support
1
Oracle Semantic Technologies Overview
1.1
Introduction to Oracle Semantic Technologies
1.2
Semantic Data Modeling
1.3
Semantic Data in the Database
1.3.1
Metadata for Models
1.3.2
Statements
1.3.2.1
Triple Uniqueness and Data Types for Literals
1.3.3
Subjects and Objects
1.3.4
Blank Nodes
1.3.5
Properties
1.3.6
Inferencing: Rules and Rulebases
1.3.7
Rules Indexes
1.3.8
Virtual Models
1.3.9
Semantic Data Security Considerations
1.4
Semantic Metadata Tables and Views
1.5
Semantic Data Types, Constructors, and Methods
1.5.1
Constructors for Inserting Triples Without Any Blank Nodes
1.5.2
Constructors for Inserting Triples With or Without Any Blank Nodes
1.6
Using the SEM_MATCH Table Function to Query Semantic Data
1.6.1
Performing Queries with Incomplete or Invalid Rules Indexes
1.6.2
Graph Patterns: Support for Curly Brace Syntax and OPTIONAL Keyword
1.7
Loading and Exporting Semantic Data
1.7.1
Bulk Loading Semantic Data Using a Staging Table
1.7.1.1
Recording Event Traces during Bulk Loading
1.7.2
Batch Loading Semantic Data Using the Java API
1.7.2.1
When to Choose Batch Loading
1.7.3
Loading Semantic Data Using INSERT Statements
1.7.4
Exporting Semantic Data
1.8
Creating and Managing Semantic Network Indexes
1.9
Quick Start for Using Semantic Data
1.10
Semantic Data Examples
1.10.1
Example: Journal Article Information
1.10.2
Example: Family Information
1.11
Required Procedure for Semantic Technologies Support
1.12
Partitioning Requirement
1.13
Downgrading to the Previous Oracle Database Release
1.14
Software Naming Changes for Semantic Technologies
2
OWL Concepts
2.1
Ontologies
2.1.1
Example: Cancer Ontology
2.1.2
Supported OWL Subsets
2.2
Using OWL Inferencing
2.2.1
Creating a Simple OWL Ontology
2.2.2
Performing Native OWL inferencing
2.2.3
Performing OWL and User-Defined Rules inferencing
2.2.4
Generating OWL inferencing Proofs
2.2.5
Validating OWL Models and Entailments
2.2.6
Using SEM_APIS.CREATE_ENTAILMENT for RDFS Inference
2.2.7
Enhancing Inference Performance
2.2.8
Performing Selective Inferencing (Advanced Information)
2.3
Using Semantic Operators to Query Relational Data
2.3.1
Using the SEM_RELATED Operator
2.3.2
Using the SEM_DISTANCE Ancillary Operator
2.3.2.1
Computation of Distance Information
2.3.3
Creating a Semantic Index of Type MDSYS.SEM_INDEXTYPE
2.3.4
Using SEM_RELATED and SEM_DISTANCE When the Indexed Column Is Not the First Parameter
2.3.5
Using URIPREFIX When Values Are Not Stored as URIs
3
SEM_APIS Package Subprograms
SEM_APIS.ADD_SEM_INDEX
SEM_APIS.ALTER_SEM_INDEX_ON_MODEL
SEM_APIS.ALTER_SEM_INDEX_ON_RULES_INDEX
SEM_APIS.ANALYZE_MODEL
SEM_APIS.ANALYZE_RULES_INDEX
SEM_APIS.BULK_LOAD_FROM_STAGING_TABLE
SEM_APIS.CLEANUP_FAILED
SEM_APIS.CREATE_ENTAILMENT
SEM_APIS.CREATE_RULEBASE
SEM_APIS.CREATE_RULES_INDEX
SEM_APIS.CREATE_SEM_MODEL
SEM_APIS.CREATE_SEM_NETWORK
SEM_APIS.CREATE_VIRTUAL_MODEL
SEM_APIS.DROP_ENTAILMENT
SEM_APIS.DROP_RULEBASE
SEM_APIS.DROP_RULES_INDEX
SEM_APIS.DROP_SEM_INDEX
SEM_APIS.DROP_SEM_MODEL
SEM_APIS.DROP_SEM_NETWORK
SEM_APIS.DROP_USER_INFERENCE_OBJS
SEM_APIS.DROP_VIRTUAL_MODEL
SEM_APIS.GET_MODEL_ID
SEM_APIS.GET_MODEL_NAME
SEM_APIS.GET_TRIPLE_ID
SEM_APIS.IS_TRIPLE
SEM_APIS.LOOKUP_RULES_INDEX
SEM_APIS.VALIDATE_ENTAILMENT
SEM_APIS.VALIDATE_MODEL
SEM_APIS.VALUE_NAME_PREFIX
SEM_APIS.VALUE_NAME_SUFFIX
4
SEM_PERF Package Subprograms
SEM_PERF.GATHER_STATS
Index
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