Automatic Semantic Mapping Generation for Relational Databases

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Solution Overview

Problem

Manual definition of semantic mappings between relational databases and linked data is time-consuming and energy-intensive, especially when dealing with hundreds or thousands of databases, making it inefficient for data integration.

Innovation Solution

A method and system for automatically generating semantic mappings by obtaining a first semantic mapping from a relational database to an ontology of linked data, and then using a schema mapping from one relational database to another to generate a second semantic mapping based on the first, thereby enhancing efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual definition of semantic mappings is used, then mapping accuracy and quality are improved, but time consumption and energy consumption increase significantly

Engineering Contradiction:

Improvemapping accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by automatically generating an initial semantic mapping using schema mapping relationships before manual refinement. This preliminary automated mapping provides a foundation that reduces the time required for manual definition while maintaining acceptable accuracy, directly addressing the contradiction between mapping quality and time consumption.

Inventive Principle:

Principle #10Preliminary action

2Productivity

If automated semantic mapping generation is used, then time consumption is reduced, but mapping quality and accuracy deteriorate

Engineering Contradiction:

Improvegeneration efficiencyVSAvoidmapping accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system introduces schema mapping as an intermediary layer between source relational databases and the target ontology. This intermediary enables automated semantic mapping generation by leveraging existing schema mapping relationships, thereby improving generation efficiency while maintaining mapping quality through the structured intermediary layer that preserves semantic relationships.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If semantic mappings are defined for multiple relational databases, then data integration completeness is improved, but work effort increases exponentially

Engineering Contradiction:

Improvedata integration coverageVSAvoidwork effort

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system achieves multi-functionality by using a unified approach that leverages schema mapping relationships to generate semantic mappings across multiple relational databases. This universal method allows the same automated process to be applied to numerous databases simultaneously, greatly expanding data integration coverage while avoiding exponential increases in work effort through consistent reusable procedures.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10445300B2Automatically generating a semantic mapping for a relational database

Publication Date: 2019.10.15 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A method for automatically generating a semantic mapping for a relational database RDB includes obtaining a first semantic mapping from a first RDB to an ontology of linked data; obtaining a schema mapping from the first RDB to a second RDB; and generating a second semantic mapping from the second RDB to the ontology of the linked data based on the first semantic mapping and the schema mapping.