Multi-Dimensional Data Visualization on a Two-Dimensional Interface
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Solution Overview
Problem
Existing data visualization technologies are limited to analyzing data in two dimensions, making it challenging to effectively explore and understand complex multi-dimensional data sets, especially when dealing with nine or more dimensions.
Innovation Solution
A system and method for processing multi-dimensional data on a two-dimensional form factor user interface, enabling the analysis of up to nine dimensions by importing data, joining datasets with common keys, filling missing values, categorizing columns, and adjusting plot dimensions to display data points with additional attributes and reference indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is visualized in traditional two-dimensional form, then the interface is simple and easy to operate, but the ability to analyze multi-dimensional data is limited
Solution Approach 1:
The patent applies dimensionality change by encoding multiple data dimensions (up to 9 dimensions) into a two-dimensional scatter plot using visual variables such as position, size, color, and shape of data points. This allows complex multi-dimensional data to be analyzed on a simple 2D interface without requiring additional spatial dimensions, thus resolving the contradiction between analysis capability and interface simplicity.
2Loss of information
If more data dimensions are added to the visualization, then the information content increases, but the difficulty of detecting and measuring data relationships increases
Solution Approach 1:
The patent uses color encoding to represent additional data dimensions beyond position. Different colors indicate different categories or values of specific parameters, allowing users to detect relationships and patterns across multiple dimensions simultaneously without increasing visual complexity. This resolves the contradiction by maintaining high information retention while keeping detection easy through intuitive color coding.
3Measurement precision
If the plot dimensions are adjusted to reduce data point overlap, then data point visibility improves, but the plot area and interface space consumption increases
Solution Approach 1:
The patent applies local quality by varying the visual properties (size, color, shape) of individual data points based on their specific data values. This allows overlapping points to be distinguished through their unique visual characteristics rather than requiring spatial separation, thus improving data point distinguishability without increasing the required plot area.
Data Source
AI summary
A system for processing an image in multiple dimensions of data for use on a two-dimensional form factor user interface is proposed. A system imports data inputs. A system determines the data inputs include at least one subject column and at least three parameter columns. A system determines first and second data inputs include a common key. A system joins the first and second data inputs and determines missing values. A system generates fill values for each missing value. A system categorizes each column the data inputs into subject columns and parameter columns. A system categorizes the first column into a parameter type. A system receives user inputs selecting at least one subject column and at least three parameter columns to be assigned to plot dimensions. A system determines positions associated with each data point based on the subject column and the three parameter columns.