Tessellated Data Visualization System for Hierarchical Analysis
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Solution Overview
Problem
Existing methods for visualizing hierarchical data fail to accurately convey parent-child relationships and value changes over time in an intuitive manner, particularly in three-dimensional representations, leading to difficulties in understanding complex data sets.
Innovation Solution
A multi-dimensional visualization system that represents hierarchical data as a circular cluster of columns with child nodes extending from parent nodes, where each node's height corresponds to its quantitative value, allowing for intuitive representation and tracking of data elements over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If hierarchical data is visualized using treemaps with rectangles, then the data can be displayed in two dimensions, but it becomes difficult to accurately compare relative values and understand parent-child relationships
Solution Approach 1:
The patent transitions from two-dimensional treemap rectangles to three-dimensional columns arranged in a circular cluster. The vertical dimension (height) of each column represents the quantitative value, while the radial arrangement maintains parent-child relationships. This dimensional change allows simultaneous encoding of multiple data aspects (value magnitude, hierarchical structure, temporal changes) without compromising either information accuracy or visual intuitiveness.
2Loss of information
If data elements are represented as circles with area proportional to value, then hierarchical relationships can be shown, but human perception struggles to accurately grasp relative values
Solution Approach 1:
The patent replaces circular area encoding with vertical height encoding in three-dimensional columns. Human perception is superior at judging relative heights compared to relative areas. The columns maintain radial arrangement to preserve hierarchical relationships while using the vertical dimension to encode quantitative values, thereby improving both relationship representation and value comparison accuracy.
Solution Approach 2:
The patent applies different visual encoding strategies to different aspects of the data: radial position encodes hierarchical structure, vertical height encodes quantitative value, and color or texture can encode temporal changes. This localized encoding optimizes each visual attribute for its specific data dimension, improving overall comprehension.
3Loss of information
If treemap rectangles change size over time to show temporal dependence, then data evolution can be tracked, but it becomes difficult to keep track of particular data elements
Solution Approach 1:
The patent pre-assigns fixed radial positions to each data element based on its hierarchical identity, rather than allowing positions to change with value fluctuations. This preliminary positioning establishes stable reference points that persist over time. When values change, only the heights of columns at these fixed positions change, making temporal tracking straightforward while preserving information about data evolution.
Data Source
AI summary
A data visualization system and related methods may include generating a multi-dimensional graphical object, in which a tessellated arrangement of columns represents an underlying hierarchical data set. Parent-child relationships may be represented by adjacency of columns with respect to an X-Y plane. Magnitudes of underlying values and/or expressions may be represented by Z-axis heights of the columns.