Linked Interactive Data Visualizations for What-If Analysis
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Solution Overview
Problem
Existing data visualization applications are difficult to use for complex datasets and lack clear interaction between multiple visualizations, making it hard for users to conduct 'what-if' analysis and visualize the effects of hypothetical changes.
Innovation Solution
Implementing a system that links multiple data visualizations through mathematical models, allowing users to interact with one visualization and dynamically update corresponding values in others, enabling real-time propagation of changes and creation of new hypothetical data marks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple data visualizations are displayed to analyze complex datasets, then the analytical capability is improved, but the user interface complexity increases and makes functionality difficult to use
Solution Approach 1:
The system segments the complex data analysis task into multiple independent but linked visualizations, each focusing on specific aspects of the data. Users can interact with individual visualizations independently while the system maintains automatic linkages, reducing the cognitive load of navigating a single complex interface while preserving comprehensive analytical capability.
Solution Approach 2:
The system introduces automatic linkage mechanisms as intermediaries between multiple visualizations. These linkages act as invisible mediators that automatically coordinate updates across visualizations based on user interactions, eliminating the need for users to manually manage complex inter-visualization relationships and simplifying the user interface.
2Adaptability or versatility
If multiple related data visualizations are displayed, then the comprehensive analysis capability is improved, but the relationship between visualizations becomes unclear and hard to understand
Solution Approach 1:
The system implements automatic feedback mechanisms where interactions with one visualization immediately trigger corresponding updates in linked visualizations. This real-time feedback loop makes the relationships between visualizations explicit and intuitive, as users can directly observe how changes propagate through the system, preventing loss of relationship information.
Solution Approach 2:
The system merges the display of multiple related visualizations into a unified interface where linkages are visually represented. By combining the visualizations while maintaining clear visual indicators of their relationships, the system preserves comprehensive analysis capability while preventing loss of relationship clarity between different data views.
3Adaptability or versatility
If users can dynamically change data values for what-if analysis, then the analytical flexibility is improved, but the system complexity increases
Solution Approach 1:
The system implements dynamic data values that can be freely adjusted by users for what-if analysis. The linkage system automatically adapts to these dynamic changes and propagates them through the visualization network, providing high analytical flexibility while the automatic update mechanisms hide the underlying system complexity from users.
Solution Approach 2:
The system provides self-service automatic update propagation where the linkage mechanism autonomously handles the complexity of coordinating changes across multiple visualizations. Users simply modify data values in one visualization, and the system automatically manages the propagation and coordination, eliminating the need for users to understand or manage the underlying system complexity.
Data Source
AI summary
A device concurrently graphs a first data visualization and a second data visualization on a display. The first data visualization and the second data visualization share a common axis corresponding to a shared data field from a data source. The first data visualization comprises graphical marks corresponding to data values of a first data field from the data source and the second data visualization comprises graphical marks corresponding to data values of a second data field. A user moves a first graphical mark from a first location corresponding to an actual data value of the first data field to a second location, creating a first hypothetical value of the first data field. The device moves a second graphical mark in the second data visualization to an adjusted location corresponding to a computed hypothetical value for the second data field according to the first hypothetical value of the first data field.