Dynamic Y-Axis Graphing for Multi-Series Data Comparison
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Solution Overview
Problem
Conventional digital graphical representation systems face inefficiencies, inaccuracies, and inflexibilities when portraying multiple data series with different scales or units, often distorting data to fit a single representation, which obscures trends and reduces analysis accuracy.
Innovation Solution
The system generates dynamic graphical representations by normalizing data values and using dynamic y-axes that adjust based on user selection, allowing for flexible and accurate comparison of multiple data series without distorting their scales or units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple data series with different scales are portrayed in different graphical representations, then each data series can be displayed with its native scale, but users must alternate between different user interfaces resulting in excessive interaction and time consumption
Solution Approach 1:
The patent combines multiple data series with different scales into a single graphical representation by introducing multiple y-axes, each corresponding to a different data series scale. This allows users to view all data series simultaneously in one interface, eliminating the need to alternate between multiple user interfaces while preserving the native scale of each data series through its dedicated axis.
2Ease of operation
If multiple data series are portrayed in a single static graphical representation with different scales, then user interaction is reduced, but the data series are distorted to fit a common range, obscuring trends and contours
Solution Approach 1:
The patent resolves the scale conflict by adding another dimension to the graphical representation - multiple y-axes positioned at different locations in the chart. Each y-axis maintains its own scale and range, allowing data series to be plotted without distortion while still appearing in a single unified visual space. This dimensional approach preserves both the ease of single-interface operation and the accuracy of data trends.
3Device complexity
If a single static graphical representation is used for multiple data series with vastly different scales, then interface complexity is reduced, but the representation becomes rigid and cannot flexibly adapt to user focus on specific series
Solution Approach 1:
The patent transforms the static graphical representation into a dynamic one where the system can adapt to user focus. By implementing multiple y-axes with different scales, the graph becomes flexible enough to accommodate user interactions such as hovering or selecting specific data series, allowing the interface to dynamically adjust which data series is emphasized while maintaining the underlying multi-scale structure.
4Ease of operation
If data series are normalized to a common range for display, then they can be shown in a single graphical representation, but quantifiable values and discernable contours are lost
Solution Approach 1:
The patent segments the y-axis functionality into multiple independent axes, each dedicated to a specific data series and its native scale. This segmentation allows each data series to maintain its quantifiable values and discernable contours on its own axis, while all series are simultaneously visible in a single graphical representation through the coordinated display of multiple axes.
Data Source
AI summary
The present disclosure relates to systems, non-transitory computer-readable media, and methods for accurately, efficiently, and flexibly generating digital graphical representations reflecting multiple data series in-scale utilizing dynamic y-axes. In particular, in one or more embodiments, the disclosed systems generate a normalized graphical representation portraying multiple data series in a common scale with a dynamic y-axis that portrays individualized data values based on user selection of various data series. Specifically, the presently disclosed systems and methods can generate normalized values for each of the included data series, plot the normalized values along a normalized y-axis, and include a dynamic y-axis that reflects the initial values of any of the included data series.