Semantic Discovery Graph Visualization for Database Relationship Navigation
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Solution Overview
Problem
Database management systems face challenges in presenting large amounts of data in a way that allows users to easily identify and navigate relationships due to limited display sizes and the complexity of database information, requiring cumbersome navigation operations.
Innovation Solution
The implementation of a persistence system that generates a semantic representation of instance data, allowing users to visually explore and discover relationships through a graphical user interface, which includes converting data structures into graph representations and applying relevance-based visualization to declutter the interface and simplify navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If database information is displayed as stored in tables, then the complete data structure is preserved, but it becomes difficult to identify and navigate relationships due to limited display size and high information volume
Solution Approach 1:
The patent segments the database information display into multiple hierarchical levels: the current view shows relevant relationships, while the underlying table structure remains segmented and available for detailed examination. This allows users to see relationships at a glance without losing access to complete data structure information.
Solution Approach 2:
The patent introduces a new dimensional representation by displaying database relationships in a graphical format (nodes and edges) alongside or instead of traditional tabular views. This additional visual dimension enables users to perceive relationships spatially, making navigation and identification significantly easier while preserving access to the original tabular data structure.
2Loss of information
If all database tables and information are displayed, then complete data visibility is achieved, but navigation becomes cumbersome and user efficiency decreases
Solution Approach 1:
The patent applies local quality by dynamically adjusting the display based on user context and needs. The system highlights and displays only the locally relevant portions of the database (relationships connected to currently selected entities), while maintaining the ability to access other parts of the database when needed. This reduces navigation overhead and improves productivity without sacrificing complete data visibility.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and pre-organizing relationship paths, relevant entities, and navigation structures. When a user selects an entity, the system has already prepared the relevant relationship information for immediate display, eliminating the need for users to manually navigate through entire tables to find relationships, thus improving data consumption efficiency.
3Stability of the object's composition
If traditional table-based database views are used, then data storage fidelity is maintained, but relationship synthesis requires cumbersome navigation operations
Solution Approach 1:
The patent introduces an intermediary layer between the raw database tables and the user interface. This intermediary (the relationship visualization system) translates the stable tabular data structure into an intuitive graphical representation that shows relationships clearly. Users interact with this intermediary layer for easy navigation and relationship synthesis, while the underlying table structure remains unchanged and stable, preserving data storage fidelity.
Data Source
AI summary
Disclosed herein are system, method, and device embodiments for implementing semantic discovery. An embodiment operates by retrieving a plurality of entities from a database instance. A semantic graph representation of the plurality of entities is generated within a graphical user interface. Context information is received from a user. A focus node is determined from the plurality of nodes using the context information. A semantic context of the focus node is determined, wherein the semantic context includes the focus node, a subset of the plurality of nodes, and subset of the plurality of edges. Responsive to the receiving, a visual indication of the semantic context is displayed within the graphical user interface.