Dynamic Dashboard Widget Selection via Relevancy Scoring
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Solution Overview
Problem
Current data storage system management applications have static dashboard configurations, limiting users' ability to view all relevant visualizations simultaneously, leading to delays in recognizing critical system aspects due to the need for frequent reconfiguration or toggling between dashboards.
Innovation Solution
Implement a dynamic dashboard that continuously calculates and displays the most relevant widgets based on user needs by assigning relevancy scores using artificial intelligence algorithms, ensuring only the most critical information is presented at any given time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static dashboard configuration is used, then the dashboard structure is simple and stable, but the user cannot view all relevant visualizations simultaneously and must frequently reconfigure or toggle between dashboards
Solution Approach 1:
The dashboard transitions from a static configuration to a dynamic one where widgets are automatically selected and arranged based on real-time relevancy scoring. The system continuously evaluates widget importance using AI algorithms and adjusts the dashboard layout without requiring user intervention, making the dashboard adaptive to changing information needs while maintaining automated management of complexity
Solution Approach 2:
The dashboard system performs self-configuration by automatically calculating relevancy scores for available widgets and selecting the most relevant ones to display. The system serves itself by autonomously determining which visualizations should be shown based on predefined scoring criteria, eliminating the need for manual user reconfiguration while adapting to different operational contexts
2Loss of information
If multiple widgets are displayed to show comprehensive information, then the information coverage is complete, but the dashboard becomes cluttered and difficult to navigate
Solution Approach 1:
The system extracts only the most relevant widgets from the complete set of available visualizations based on relevancy scoring. By selectively displaying only the top-scoring widgets that currently matter most to the user's needs, the system maintains information completeness for critical data while filtering out less important visualizations that would clutter the interface
Solution Approach 2:
Different widgets are assigned different display priorities based on their calculated relevancy scores. The system applies local quality by giving prominent placement to high-scoring widgets while relegating or hiding lower-scoring ones, creating a differentiated display hierarchy that optimizes both information delivery and interface clarity
3Adaptability or versatility
If the dashboard is reconfigured frequently to show different information, then the user can access different visualizations, but the user experience deteriorates due to continuous manual intervention
Solution Approach 1:
The system performs preliminary action by pre-calculating and pre-selecting the most relevant widgets before the user needs to view them. Relevancy scores are computed in advance based on current system state and user context, so when the user needs information, the appropriate widgets are already prepared and displayed, eliminating the time loss associated with manual reconfiguration
Solution Approach 2:
The system implements continuous feedback loops where relevancy scores are repeatedly calculated and dashboard configurations are automatically updated based on changing conditions. This closed-loop system monitors information needs and adjusts the dashboard display in real-time without user intervention, maintaining adaptability while eliminating the time cost of manual adjustments
Data Source
AI summary
Techniques are directed to a method of displaying data storage system widgets to a user within a graphical user interface of a data storage system management application running on a computing device. The method includes (a) during operation of the data storage system management application, repeatedly calculating, by the computing device, relevancy scores for a plurality of available data storage system widgets based on expected needs of the user, (b) during operation of the data storage system management application, repeatedly selecting, by the computing device, a set of widgets having the highest calculated relevancy scores from the plurality of available widgets, and (c) during operation of the data storage system management application, repeatedly displaying the selected set of widgets to the user on a display screen, the displayed widgets each presenting data storage system management data to the user. A computer program product and apparatus are also provided.