02-01-2013, 10:39 AM
Developing Semantic Web Applications using the Oracle Database 10g RDF Data Model
The Oracle 10g RDF Feature Delivers:
• The industry's first open, scalable, secure semantic
database
• An open and generic RDF data model and analysis
platform for semantic applications.
• Feature of Oracle Spatial (database option)
• Perform SQL-based access to triples and inferred data
• Support for user-defined rules, rule bases, rule indexes
• Support large graphs (billion of triples)
• Easily extensible by 3rd party tools/apps
Resource Description Framework (RDF)
• Originally conceived as W3C’s metadata model
• Document metadata for digital libraries, content rating, site maps, etc.
• Simple graph data model
• Leverages syntactic extensibility and modularity of XML namespaces
• Provides global extensibility through a common data model
• Directed labeled graph: “subject/property/object”
• Nodes are called “resources” and links “properties”
RDF in Oracle Spatial
• RDF data stored as a directed, logical graph
• Subjects and objects mapped to nodes, and
predicate to links that have subject start nodes
and object end nodes
• Links represent a complete RDF triple
Why is this Useful?
• Designed to represent knowledge in a distributed world
• A method to decompose knowledge into small pieces,
with rules about the semantics of those pieces
• RDF data is self-describing; it “means” something
• Allows you to model and integrate DBMS schemas
• Allows you to integrate data from different sources
without custom programming
• Allows data re-use from multiple sources
• Supports decentralized data management
• Infer implicit relationships across data
Analytical Intelligence Operations
• Unify and aggregate data from separate databases
• Store transactions between people
• Store objects moving in time and space
• Use text mining to extract knowledge from text (docs,
email, Web)
• Mostly used for graph search….
• Mature Systems: 10B triples (lower bound)
Query RDF Data
• SPARQL-like graph pattern embedded in SQL query
• Matches RDF/OWL graph patterns with patterns in stored data
• Returns a table of results
• Can use SQL operators/functions to process results
• Avoids staging when combined with queries on relational data
• Scales: millisecond query times for large data sets (10M+ triples)