Dashboard Interaction Relationship Graph for Component Management
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Solution Overview
Problem
Complex dashboards with numerous components face challenges in maintaining and managing interaction relationships between components, making it difficult for designers to identify linked components and determine impacts from changes such as removal or replacement.
Innovation Solution
A framework utilizing a data grid to define and manage interaction relationships between dashboard components, allowing decoupling and recoupling of components while maintaining defined formulas, and generating an interaction relationship graph to visualize source-to-target connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a dashboard includes a huge amount of components to display comprehensive data, then the data visualization capability is improved, but the complexity of managing and identifying interaction relationships between components increases
Solution Approach 1:
The patent introduces an interaction relationship graph as an intermediary visualization tool that mediates between the large number of dashboard components and the designer. This graph automatically displays interaction relationships, serving as a mediator that eliminates the need for designers to manually track complex connections among hundreds of components.
Solution Approach 2:
The system provides automatic feedback by generating and updating the interaction relationship graph based on component interactions. When components are added, removed, or modified, the graph automatically reflects these changes, giving designers immediate feedback about which components are linked without requiring manual analysis.
2Adaptability or versatility
If interaction relationships are manually managed in complex dashboards, then flexibility in component arrangement is improved, but the time and effort required to maintain relationships increases
Solution Approach 1:
The interaction relationship graph performs self-service by automatically generating, updating, and maintaining itself based on component interactions. The system autonomously tracks which components are linked and updates the visualization without requiring designer intervention, thereby maintaining flexibility while eliminating manual maintenance time.
Solution Approach 2:
The system performs preliminary action by pre-calculating and pre-displaying all interaction relationships in the graph before the designer needs to analyze them. This advance preparation eliminates the time required for manual relationship tracking during the design process.
3Measurement precision
If designers manually identify linked components, then precision in relationship identification is improved, but the difficulty and cumbersome nature of the task increases
Solution Approach 1:
The interaction relationship graph serves as an intermediary that precisely displays all component linkages. Instead of designers manually searching for relationships, the graph mediates by visually presenting exactly which components are linked, ensuring precision while eliminating the difficulty of manual identification.
Solution Approach 2:
The system uses visual indicators such as color changes in the interaction relationship graph to highlight different types of relationships or states of components. This visual encoding makes it easy to precisely identify linked components through color-coded representations rather than manual searching.
4Ease of operation
If components are modified without tracking relationships, then ease of component modification is improved, but the reliability of the dashboard decreases
Solution Approach 1:
The interaction relationship graph provides immediate feedback when components are modified. If a source component is removed or replaced, the graph shows which target components are affected, allowing designers to modify components easily while maintaining reliability by being aware of the impacts.
Solution Approach 2:
The system performs preliminary anti-action by预先 identifying and displaying components that would be negatively affected by modifications. Before a designer removes or replaces a component, the graph shows which other components depend on it, allowing the designer to take preventive measures to maintain dashboard reliability.
Data Source
AI summary
A technology for building and displaying interaction relationships between visual components of a dashboard is provided. In accordance with one aspect, interaction relationships are defined between the components of the dashboard using a data grid. A relationship may be defined by associating a component to a grid cell and defining a formula in the grid cell based on one or more other grid cells which are further associated to one or more other components. In accordance with another aspect, information of a dashboard including dashboard components, input data and output data in the dashboard is converted into dashboard data models. An interaction relationship graph may be generated based on interactions of the input data and output data of the components. The interaction relationship graph comprises source-to-target relationships between source and target components of the dashboard. The interaction relationship between the visual components of the dashboard may be presented using the dashboard data models containing the source-to-target relationships.