Relational Database Semantic Web Integration via SQL Query Optimization

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Solution Overview

Problem

Existing approaches for integrating relational databases into the Semantic Web framework face challenges in efficiently mapping relational data to RDF and handling SPARQL queries, often requiring manual and inefficient mappings, and struggle with maintaining real-time consistency between relational and RDF representations.

Innovation Solution

A system and method that transforms relational databases' SQL schema into equivalent Semantic Web representations, allowing for seamless querying using SPARQL queries by translating SPARQL queries into SQL queries through a SQL query optimizer, without materializing RDF triples, and maintaining real-time consistency through a synthesized domain model.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual mapping from SQL schema to RDF is used, then integration into Semantic Web framework is achieved, but mapping complexity and time consumption increase

Engineering Contradiction:

Improveintegration into Semantic Web frameworkVSAvoidmapping complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system automatically generates RDF representations and domain models by executing SQL queries against the relational database schema itself. The database system serves itself to produce the semantic web representation without requiring external manual mapping tools or processes, thereby reducing mapping complexity while maintaining integration capability

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The synthesized domain model is pre-computed from the SQL schema during system initialization or when schema changes occur. This preliminary action creates a ready-to-use mapping structure that eliminates the need for manual mapping during runtime, reducing both mapping complexity and time consumption

Inventive Principle:

Principle #10Preliminary action

2Speed

If physical triple stores are materialized for RDF data, then SPARQL query performance improves, but storage requirements and system complexity increase

Engineering Contradiction:

ImproveSPARQL query performanceVSAvoidstorage requirements

Core Design Contradiction:

SpeedVSQuantity of substance

Solution Approach 1:

The system introduces a synthesized domain model as an intermediary layer between the relational database and SPARQL queries. This domain model acts as a virtual triple store that translates SPARQL queries into SQL queries without requiring physical materialization of RDF triples, thereby maintaining query performance while eliminating additional storage requirements

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

Instead of creating physical copies of data in triple store format, the system creates a virtual copy through the synthesized domain model that represents the same information structure. This allows SPARQL queries to operate on a logical representation without the overhead of physical materialization

Inventive Principle:

Principle #26Copying

3Adaptability or versatility

If separate RDF storage is implemented, then Semantic Web data access is enabled, but real-time consistency with relational data becomes difficult to maintain

Engineering Contradiction:

ImproveSemantic Web data accessVSAvoidreal-time consistency

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system merges the RDF data model with the existing relational database structure by using the same physical storage infrastructure. The synthesized domain model provides a unified view that simultaneously satisfies both relational and semantic web access requirements, ensuring real-time consistency without requiring separate RDF storage systems

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS8719252B2Accessing relational databases as resource description framework databases

Publication Date: 2014.05.06 SERVICENOW INC

AI summary

This invention is a system and method for integrating relational databases into a semantic web framework utilizing a simple mapping process and the SQL query optimizer present in the SQL database engine.