Ontology Query Construction Using Optimal Graph Paths
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Solution Overview
Problem
Complex data structures and ontologies are challenging to query due to their sophistication and the restricted accessibility of query languages, hindering users from leveraging their full potential, especially in integrating paradigms like graphQL.
Innovation Solution
An apparatus and method for ontology query construction that includes a processor and memory to receive starting and ending models, determine an optimal path through a graph schema, and construct a query based on this path, using breadth-first search and inferencing techniques to simplify query construction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If complex data structures and ontologies are used to store sophisticated data, then data storage capacity and organization are improved, but query difficulty and accessibility worsen
Solution Approach 1:
The patent introduces a query construction system as an intermediary between users and complex ontologies. This system automatically generates queries by determining optimal paths through the graph schema from starting models to ending models, eliminating the need for users to directly interact with complex query languages while still accessing sophisticated data structures
Solution Approach 2:
The patent breaks down complex ontology queries into manageable segments by using graph schemas that divide the ontology into discrete models and relationships. The system processes queries by determining optimal paths through these segmented components, making the overall query construction more manageable and accessible to users
2Adaptability or versatility
If graph schemas with multiple models and relationships are used, then data organization and query capability are improved, but system complexity worsens
Solution Approach 1:
The patent implements a system that automatically determines optimal paths through graph schemas without requiring manual intervention. The query construction system self-services by autonomously navigating the complex graph structure from starting models to ending models, generating appropriate queries automatically and reducing the burden on users to manage system complexity
3Productivity
If automated query construction is implemented, then user productivity is improved, but computational requirements and processing time worsen
Solution Approach 1:
The patent pre-processes the ontology into a graph schema structure with defined models and relationships before queries are received. This preliminary organization of data into a navigable graph format enables faster optimal path determination during actual query processing, as the system only needs to navigate the pre-structured graph rather than parse and interpret raw ontology data in real-time
Data Source
AI summary
Apparatuses, methods, program products, and systems are disclosed for techniques for ontology query construction. An apparatus includes a processor and a memory that stores code that is executable by the processor. The code is executable by the processor to receive a starting model associated with a graph schema defining a graph, receive an ending model associated with the graph schema, determine an optimal path through the graph schema from the starting model to the ending model, and construct a query for querying the graph based on the determined optimal path.