Multimodal Data Visualization Using Bandwidth Profiles
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Solution Overview
Problem
Existing data visualization methods fail to account for individual perceptual bandwidth differences among users, leading to ineffective communication of information, particularly for users with disabilities or impairments, as visualizations designed by one person may not be perceivable by others due to varying sensitivities and environmental factors.
Innovation Solution
A computer-implemented method and system that transforms a base visualization into a new visualization tailored to a user's specific perceptual bandwidth, using a calibration engine to generate user profiles and a mapping engine to adjust modalities and environmental factors, ensuring the new visualization falls within the user's perceptual range, thereby enabling optimal data consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a base visualization is designed with a specific set of channels and ranges, then the visualization can be created efficiently, but it may fall outside the perceptual bandwidth of certain users, making it ineffective for them
Solution Approach 1:
The system dynamically transforms the base visualization into a customized visualization by detecting the user's perceptual bandwidth and automatically adjusting channel ranges and data mappings. This dynamic adaptation allows the same base visualization to be effectively perceived by users with different perceptual capabilities without requiring manual redesign for each user.
Solution Approach 2:
The system changes the parameters of the visualization by mapping data from the original channel ranges to transformed channel ranges that fall within the user's perceptual bandwidth. This parameter transformation ensures that the visualization remains informative while becoming accessible to users with varying perceptual sensitivities.
2Reliability
If visualizations are customized for each user's perceptual bandwidth, then effectiveness for individual users improves, but the complexity of the system increases due to needing to detect and adapt to different users
Solution Approach 1:
The system performs self-service by automatically detecting the user's perceptual bandwidth and generating the appropriate customized visualization without requiring manual intervention from the user or designer. The automated detection and transformation processes handle the complexity internally, maintaining high reliability while keeping the user experience simple.
Solution Approach 2:
The system performs preliminary actions by pre-defining channel ranges and data mappings in the base visualization that can be systematically transformed. This preliminary structuring enables efficient automatic adaptation to different user perceptual bandwidths, reducing the complexity of real-time customization.
Data Source
AI summary
A computer-implemented method includes receiving a base visualization having first data in a first set of channels, where each channel in the first set of channels is associated with a respective range in the base visualization. It is detected that the respective ranges of the first set of channels fall outside a perceptual bandwidth of a first user. The base visualization is automatically transformed to a second visualization, based on the perceptual bandwidth of the first user. The second visualization includes second data in a second set of channels, where each channel in the second set of channels is associated with a respective range in the second visualization. The respective ranges of the second set of channels fall within the perceptual bandwidth of the first user.