Database Visualization System for Data Dependency Management
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Solution Overview
Problem
In complex database management systems, especially in video game development, updating data without fully understanding dependency relationships between data can lead to unintended changes in other objects, making it difficult for users to maintain accurate data structures.
Innovation Solution
A database visualization system that extracts and displays reference source and referent data in association with the first data, using icons connected by lines or graphics to visualize dependency relationships, allowing users to easily understand and manage data interdependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is managed in a complex database structure with multiple users performing updates, then data functionality and versatility are improved, but understanding the dependency relationships between data becomes difficult and error-prone
Solution Approach 1:
The patent introduces an intermediary visualization system that mediates between the complex database and the user. This system automatically generates and displays dependency relationship graphs that show how data items relate to each other, making invisible dependencies visible without changing the underlying database structure or data functionality.
Solution Approach 2:
The system provides feedback to users about data dependencies before updates are executed. By displaying dependency relationship information in advance, users can see which data items will be affected by their updates, allowing them to make informed decisions about whether to proceed with the update.
2Productivity
If users update data without examining dependency relationships, then update speed and productivity are improved, but unintended changes occur in referent data causing errors
Solution Approach 1:
The system performs preliminary action by automatically analyzing and displaying dependency relationships before the user executes an update. This pre-update visualization allows users to quickly assess potential impacts without manually tracing dependencies, maintaining fast update speeds while preventing erroneous changes through informed decision-making.
Solution Approach 2:
The system prepares countermeasures by displaying dependency information that warns users of potential unintended consequences before updates occur. This preliminary warning allows users to adjust their update strategy or choose different data items to update, preventing harmful side effects before they happen.
3Reliability
If users manually examine dependency relationships before updates, then data update accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs self-service by automatically analyzing the database structure and generating dependency relationship visualizations without requiring user effort. The system autonomously traces data relationships and presents them in an easily interpretable format, eliminating the time-consuming manual examination process while maintaining high update accuracy.
Solution Approach 2:
The patent replaces the mechanical process of manual dependency tracing with an automated computational system. Instead of users manually following data relationships through complex database structures, the system automatically performs the analysis and presents results visually, dramatically reducing the time required while maintaining comprehensive accuracy.
4Adaptability or versatility
If the database structure is made more complex to handle multiple data relationships, then data management capability is improved, but the complexity of visualizing and understanding relationships increases
Solution Approach 1:
The system applies segmentation by dividing the complex dependency relationship visualization into manageable portions. It displays relationships in a hierarchical or progressive manner, allowing users to view overall structure first and then drill down into specific relationships as needed, making complex data manageable without simplifying the underlying database structure.
Data Source
AI summary
A display request is received by user input to an input device (step S1). With reference to a database, referent data or reference source of data associated with an icon clicked upon the display request is extracted (step S2). When more reference source or referent data are present in the extracted data (YES in step S3), the process returns to step S2. When no reference source or referent data is present in the extracted data (NO in step S3), an icon associated with the extracted data is drawn as connected (step S4), and the icon is displayed on a display screen (step S5).


