Ontology Update Merging for User-Edit Conflict Resolution
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Solution Overview
Problem
Existing systems struggle to effectively manage conflicts between data source updates and user edits to ontology data, leading to inefficiencies in database operations and inconsistent user-centric views.
Innovation Solution
A system that prioritizes user edits over data source updates in resolving conflicts, ensuring consistent user-centric evolution of ontology data by implementing a conflict resolution strategy that integrates user edits and data source updates before updating databases, thereby improving data quality and reducing network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data source updates are applied to ontology data, then data freshness is improved, but user edit consistency deteriorates
Solution Approach 1:
The system performs preliminary actions by tagging ontology entities with their source identifiers and version information before conflicts occur. This metadata is prepared in advance, enabling efficient conflict detection and resolution when data source updates arrive, without requiring complex real-time analysis of user edits versus automated updates.
Solution Approach 2:
The patent introduces an intermediary conflict resolution layer between data source updates and ontology data application. This intermediary evaluates conflicts based on predefined strategies (such as prioritizing user edits or selecting based on recency) and determines which updates to apply, thereby mediating between the competing requirements of data freshness and user edit consistency.
2Quantity of substance
If all data source updates are incorporated into databases, then data completeness is improved, but network traffic increases
Solution Approach 1:
The system extracts and applies only the necessary conflict resolution logic and metadata to the ontology data before database updates. By filtering out redundant information and applying only essential updates, the system reduces network traffic while maintaining data completeness in the databases.
Solution Approach 2:
The patent changes parameters by transforming raw data source updates into optimized ontology updates with attached metadata. This transformation modifies the data structure to include source identifiers and version information, enabling efficient conflict resolution and reducing the volume of data that needs to be transmitted over the network.
3Manufacturing precision
If conflict resolution strategies are implemented, then data quality is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by tagging ontology entities with their source identifiers and version information before conflicts occur. This metadata is prepared in advance, enabling efficient conflict detection and resolution when data source updates arrive, without requiring complex real-time analysis of user edits versus automated updates.
Solution Approach 2:
The conflict resolution mechanism operates autonomously using predefined strategies and metadata, without requiring complex external intervention. The system self-manages conflict detection, evaluation, and resolution based on embedded source identifiers and version information, reducing the need for additional complex control systems.
Data Source
AI summary
A method comprises receiving a set of data source updates for one or more datasets from data sources; receiving one or more sets of user edits to an ontology; transforming the set of data source updates to a list of updates to the ontology based on a mapping between the one or more datasets and a plurality of ontology entity types; merging the list of updates with the one or more sets of user edits into a merged dataset; and resolving conflicts in the merged dataset by prioritizing a user edit over a data source update, comprising: determining that a current user edit to a first ontology entity of a first ontology entity type is to create the first ontology entity and no earlier user edit to the first ontology entity was to delete the first ontology entity; and disregarding any later data source update to the first ontology entity.