Ontology-Guided Reference Data Discovery
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Solution Overview
Problem
Converting an existing database to a different reference data schema is a cumbersome, time-consuming, and error-prone task, especially when the user is unfamiliar with either schema or lacks documentation, due to the need for manual determination of associations between reference schemas.
Innovation Solution
An ontology-guided reference data discovery component maps reference data from one database to a common ontology, determining associations between the data sets based on their ontology mappings, and constructs a translation table to facilitate the conversion of reference data between different schemas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual mapping of reference schemas is performed, then association determination can be done with human judgment, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent introduces an intermediary ontology as a common reference framework between source and target reference schemas. Instead of directly mapping between two different schemas, the system maps both schemas to the ontology and then establishes associations through the ontology, which resolves conflicts and ambiguities automatically
Solution Approach 2:
The patent replaces manual mechanical mapping processes with automated computational algorithms. The system automatically compares reference values from source and target schemas against ontology definitions to determine associations, eliminating the need for manual examination of each reference table
2Ease of operation
If manual creation of translation tables is performed, then precise control over mapping can be maintained, but the task becomes complex and difficult when schemas are unfamiliar
Solution Approach 1:
The system performs self-service by automatically analyzing reference tables and generating translation tables without requiring user intervention. The ontology-guided algorithm autonomously determines mappings by comparing reference values against ontology definitions, making the process as easy as providing the source and target schemas
Solution Approach 2:
The patent performs preliminary action by pre-defining the ontology before the mapping process. The ontology serves as a pre-prepared reference framework that guides the automated mapping, eliminating the need for users to manually create translation tables from scratch
3Measurement precision
If exhaustive examination of all reference tables is performed, then complete and accurate mapping can be achieved, but the process becomes tedious and error-prone
Solution Approach 1:
The patent replaces the mechanical process of manually examining each reference table with automated computational algorithms that process all reference tables simultaneously. The system uses ontology-based matching to automatically identify associations across the entire database schema
Solution Approach 2:
The ontology serves as a universal reference framework that applies across all reference tables in the database. By mapping all reference values to the ontology, the system achieves complete and consistent mapping across the entire schema without requiring separate processing for each table
Data Source
AI summary
Mapping and translating reference data from multiple databases using an enterprise ontology. This is achieved by various means, including mapping values of a first database to corresponding fields within the ontology, mapping values of a second database to corresponding fields within the ontology, and determining relationships between the values of the first database and the values of the second database based on their respective mappings to common fields within the ontology.