Ontology-Based Data Query Across Isolated Enterprise Systems
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Solution Overview
Problem
Existing IT and OT systems in enterprises are isolated, leading to low data query efficiency and high costs due to the need to search multiple systems individually.
Innovation Solution
A data query method that involves a data service receiving an ontology identifier, merging knowledge graphs, and outputting instance data of the target ontology and connected ontologies, utilizing a self-describing interface and semantic data query interface to streamline data access across multiple systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is queried from multiple isolated systems individually, then data can be obtained from each system, but query efficiency is low and query costs are high
Solution Approach 1:
The patent merges multiple isolated knowledge graphs into a unified knowledge graph, integrating data from multiple systems into a single accessible structure. This allows users to query all required data through one interface rather than accessing each system separately, directly improving query efficiency and reducing time loss.
Solution Approach 2:
The patent introduces a data service as an intermediary layer between users and multiple knowledge graphs. This mediator manages the complexity of accessing multiple systems by providing a unified query interface, automatically routing queries to relevant knowledge graphs and aggregating results, thereby improving productivity without sacrificing data completeness.
2Ease of operation
If multiple knowledge graphs are merged into a unified knowledge graph, then data access is simplified and query efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the unified knowledge graph into multiple sub-knowledge graphs, each representing a specific domain or system. This segmentation allows the system to manage complexity by organizing data into manageable modules while maintaining a unified access interface, thus improving ease of operation without overwhelming system complexity.
Solution Approach 2:
The patent creates a universal data service interface that can access and query multiple different knowledge graphs through a single standardized interface. This multi-functional interface handles various query types and routes them appropriately, simplifying user operations while the underlying system manages the complexity of multiple knowledge graphs through standardized protocols.
Data Source
AI summary
Various embodiments of the teachings herein include a data query method. For example, a method may include: receiving first input information at a data service, the first input information comprising an identifier of a target ontology; and generating target data based at least in part on the identifier of the target ontology, the target data comprising instance data of the target ontology and/or instance data of at least a portion of ontologies having a connection relationship with the target ontology. The instance data of the target ontology and the instance data of said at least a portion of ontologies come from multiple systems.