Deterministic Color Mapping for Stable Categorical Data Visualization

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Solution Overview

Problem

Existing digital visualization systems struggle to maintain stable and discernible color mappings for categorical data, leading to user confusion and increased time in understanding graphical representations.

Innovation Solution

The system employs a deterministic mapping of categorical values to colors using hashing functions, ensuring consistent color assignments. Additionally, the colors are adjusted to achieve a just-noticeable difference in human visual perception, maintaining stability and discernibility.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Stability of the object's composition

If a limited, fixed list of distinct colors is used to map categories, then the colors are discernable in terms of human visual perception, but the color mapping is not stable across different times and contexts

Engineering Contradiction:

Improvecolor mapping stabilityVSAvoiduser recognition speed

Core Design Contradiction:

Stability of the object's compositionVSEase of operation

Solution Approach 1:

The patent applies parameter changes by transitioning from a fixed, limited color palette to a dynamic color generation system. Colors are determined by transforming categorical data through hashing functions and color space conversions (RGB to HSV/HSL), allowing the system to adapt color assignments based on the actual data categories while maintaining consistency. This resolves the contradiction by enabling stable mapping through deterministic transformation rather than fixed predefined colors.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the mechanical system of fixed color palettes with an algorithmic approach using hashing functions and color space mathematics. Instead of manually selecting from predefined colors, the system uses deterministic mathematical transformations to generate colors based on categorical data, ensuring stability while improving user recognition through consistent and meaningful color assignments.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If the number of categories of data exceeds the number of colors in the palette, then multiple slices may be depicted by reusing the same color, but it becomes difficult for users to discern different colors mapped to different categories

Engineering Contradiction:

Improvehandling of large number of categoriesVSAvoidcolor distinction between categories

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent changes the parameter space from a limited fixed palette to a continuous color space (HSV/HSL) where colors are generated based on hash values of categorical data. This allows the system to generate sufficiently distinct colors for any number of categories by transforming the categorical identifiers through hashing and color space conversion, ensuring that each category receives a uniquely discernible color even when the number of categories is large.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent moves from a two-dimensional fixed palette selection to a multi-dimensional color space transformation. By using hashing functions to generate unique identifiers and then converting through color space transformations (RGB to HSV/HSL), the system creates a multi-dimensional approach to color generation that ensures sufficient distinction between categories regardless of their number, resolving the visibility problem.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Reliability

If different colors are used to represent the same category at different times, then the color-category mapping is not stable, but users must consult the legend each time to determine color-category associations

Engineering Contradiction:

Improvecolor-category mapping consistencyVSAvoidtime to understand graphical representation

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent implements parameter changes by using deterministic transformations (hashing functions and color space conversions) to generate colors based on categorical data. This ensures that the same category always receives the same color across different visualizations and time periods, creating reliable and consistent color-category mappings that eliminate the need for users to consult legends repeatedly.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the mechanical system of manual color selection with an algorithmic deterministic generation system. By using hashing functions and color space mathematics, the system automatically generates consistent color assignments based on category identifiers, ensuring reliability and eliminating time loss associated with consulting legends or adapting to changing color schemes.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250111554A1Stable and discernable mapping of categorical data to colors for graphical display

Publication Date: 2025.04.03 CROWDSTRIKE

AI summary

Data is received. Each datum therein has one of a plurality of categorical values associated with a categorical variable. Each datum is deterministically mapped to a respective one of a plurality of colors in a color space based on its categorical value. The color to which each datum is deterministically mapped is then transformed to yield a minimum threshold separation between the respective colors. A graphical representation comprising the color to which each datum is respectively deterministically mapped, and as transformed to yield the minimum threshold separation between the respective colors, is displayed.