Intermediary Knowledge Base for Cross-Standard Data Mapping
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Solution Overview
Problem
Interoperability between knowledge bases encoded with different coding standards poses challenges in healthcare, particularly in exchanging data for epidemiological, statistical, or research purposes, due to issues with memory usage and processing speed, as well as the complexity of mapping between various coding systems.
Innovation Solution
The method involves identifying matching entities between knowledge bases and creating one-to-one mappings, reducing the number of iterations required for linking and enhancing connection confidence, by using a central knowledge base to mediate translations and mappings between different coding systems, thereby reducing the complexity of multiplicity mappings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If direct mapping between knowledge bases with different coding standards is implemented, then interoperability is achieved, but memory usage and processing power requirements increase significantly
Solution Approach 1:
The patent introduces a central knowledge base as an intermediary between first and third knowledge bases with different coding standards. Instead of creating direct mappings between all entities in the first and third knowledge bases (which would consume excessive memory), the system creates mappings from the first knowledge base to the central knowledge base and from the central knowledge base to the third knowledge base. This mediator approach enables interoperability while significantly reducing memory requirements by breaking down the large mapping problem into smaller, manageable pieces.
2Adaptability or versatility
If direct mapping between knowledge bases with different coding standards is implemented, then interoperability is achieved, but processing speed decreases due to increased complexity
Solution Approach 1:
The patent segments the mapping process into multiple stages using a central knowledge base as an intermediate layer. Instead of performing a single complex mapping operation between the first and third knowledge bases, the system divides it into two simpler mapping operations: first knowledge base to central knowledge base, and central knowledge base to third knowledge base. This segmentation reduces the computational complexity of each individual mapping task, thereby improving processing speed while maintaining interoperability.
3Adaptability or versatility
If multiple-to-one mappings are used between knowledge bases, then all entities can be linked, but connection confidence decreases and mapping complexity increases
Solution Approach 1:
The central knowledge base acts as a mediator that enables the system to prefer one-to-one mappings over multiple-to-one mappings. By introducing this intermediate layer, the system can establish unique, confident correspondences between entities in the first knowledge base and the central knowledge base, and separately between the central knowledge base and the third knowledge base. This intermediary approach maintains mapping coverage while improving connection confidence, as each mapping relationship can be established with greater certainty rather than requiring ambiguous many-to-one mappings.
Data Source
AI summary
The subject-matter described herein relates to a computer-implemented method of enabling interoperability between a first knowledge base and a second knowledge base. Each knowledge base is graphically represented and includes a plurality of nodes each defining a concept and a plurality of relations linking the plurality of nodes. The first knowledge base and the second knowledge base are encoded using different coding standards. The method comprises: identifying an entity from the plurality of entities in the second knowledge base; obtaining a mapping between the identified entity from the second knowledge base and a matching entity from the first knowledge base; and creating and storing a link between the identified entity from the second knowledge base and the matching entity from the first knowledge base.