Ontology Query Join Planning Across Databases With Access Controls
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Solution Overview
Problem
Existing systems struggle to efficiently manage and query ontology-based databases while supporting access control and data representation across multiple forms, leading to suboptimal performance and data processing inefficiencies.
Innovation Solution
A system that transforms ontology queries into database queries, selects appropriate databases for execution, and determines an optimal execution plan by estimating data processing using sampling and considering access controls, ensuring efficient data retrieval and management across multiple databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system transforms ontology queries into database queries and executes them across multiple databases, then the system can efficiently manage and query ontology-based databases with access control, but the complexity of determining optimal execution plans increases
Solution Approach 1:
The system segments the ontology database into multiple separate databases, each storing different forms or representations of the ontology data. This segmentation allows parallel query execution across databases while maintaining access control, resolving the contradiction by organizing data into manageable units that can be queried independently yet collectively
Solution Approach 2:
The system introduces an intermediary execution planning layer that transforms high-level ontology queries into optimized database-specific queries. This intermediary automatically determines the optimal execution plan by evaluating access controls, data representations, and query requirements, shielding users from complexity while maximizing retrieval efficiency
2Adaptability or versatility
If the system supports multiple data representations across different databases, then the system can utilize optimal database capabilities, but the difficulty of managing and querying the databases increases
Solution Approach 1:
The system implements a universal query interface that works across multiple database types and data representations. This universal layer handles the complexity of managing different data forms (structured, semi-structured, unstructured) while providing consistent query capabilities, allowing the system to leverage optimal database capabilities without increasing user-facing management difficulty
Solution Approach 2:
The system maintains multiple copies or representations of ontology data across different databases, each optimized for specific query types or access patterns. By copying data in different representations rather than requiring users to manage diverse data formats directly, the system achieves versatility while simplifying query management through a unified access mechanism
3Reliability
If the system applies access controls to ontology queries, then the system can securely manage user permissions, but the processing time for determining executable queries increases
Solution Approach 1:
The system performs preliminary evaluation of access controls during the execution plan determination phase, before actual query execution. By pre-assessing which databases and data representations a user can access based on their permissions, the system integrates security checks into the optimization process rather than as separate overhead, maintaining reliability while minimizing additional processing time
Solution Approach 2:
The system merges access control verification with the execution plan generation process. Instead of treating security checks as a separate step that adds time, the system combines permission validation with the optimization logic, determining both the optimal execution path and access authorization simultaneously, thus maintaining security without linearly increasing processing time
Data Source
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AI summary
A system for query execution planning over ontology-based databases and related methods are disclosed. The system is programmed to receive an ontology query from a user account against an ontology having access controls, and transform the ontology query into a set of database queries, including a plurality of joins. The system is programmed to compute the amounts of data processing associated with executing the plurality of joins in different orders on a sample of the databases representing the ontology, considering how much data in the ontology can be accessed by the user account under the access controls, and determine an execution plan corresponding to a preferred amount of data processing. Furthermore, the system is programmed to execute the set of database queries on the databases according to the execution plan, and transmit a reply to the ontology query to the user device based on a result of the execution.