Unified Ontology Query Interface Across Heterogeneous Databases
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Solution Overview
Problem
Existing systems struggle to efficiently manage and query ontology-based databases across multiple databases while maintaining data integrity, versioning, and access control, leading to inefficiencies and inconsistencies.
Innovation Solution
A unified query interface system that selects appropriate databases based on function type and ontology entity type, merges retrieval results, and transforms data to provide a consistent interface, while managing ontology entities in multiple forms and resolving conflicts between data source updates and user edits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is organized according to ontology across multiple databases, then data understanding and access are facilitated, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary layer (ontology model and query interface) between the user and multiple databases. This intermediary abstracts the complexity of distributed data storage while providing unified access, allowing users to query across databases without directly managing the underlying complexity of multiple data sources.
Solution Approach 2:
The ontology model serves as a universal framework that can represent and integrate data from multiple different databases with varying schemas and structures. This universal representation layer enables diverse data sources to be accessed through a common interface, reducing the perceived complexity for users.
2Productivity
If multiple databases store ontology data in different forms, then specialized capabilities are utilized, but query consistency becomes difficult to maintain
Solution Approach 1:
The patent allows each database to maintain its specialized local form and optimization characteristics while the ontology model provides a consistent global view. Each database can be optimized for its specific data type and access patterns, while the ontology ensures consistent querying across all databases through unified semantics.
3Reliability
If conflict resolution between data source updates and user edits is implemented, then data integrity is maintained, but processing time increases
Solution Approach 1:
The system performs preliminary conflict detection and resolution strategies before finalizing data updates. By anticipating potential conflicts and preparing resolution rules in advance, the system can quickly resolve conflicts when they occur without significant processing delays, maintaining both data integrity and performance.
4Loss of information
If versioning is implemented across multiple databases, then data lineage is tracked, but synchronization complexity increases
Solution Approach 1:
The patent merges versioning management into the ontology model, which serves as a centralized coordination point. Instead of implementing separate versioning systems in each database, the ontology model provides a unified versioning framework that tracks data lineage across all databases while simplifying synchronization through a single point of control.
Data Source
AI summary
A system for providing a unified query interface across multiple ontology-based databases and related methods are disclosed. The system is programmed to receive calls to an application programming interface for querying an ontology, where ontology data is represented in different databases respectively in different forms. For each function being called, system is programmed to select a database from the different databases based on the function type and each ontology entity type being processed by the function. The system is further programmed to retrieve data from each selected database, merge the retrieval results as appropriate, and transform the final result to ontology data in response to the calls.