Trellis Chart Scaling with Synchronized Axes

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Solution Overview

Problem

Conventional graphical user interfaces (GUIs) for trellis charts do not provide an efficient way for users to dynamically scale charts, making it difficult to zoom in for detailed viewing and compare charts with independently scaled axes.

Innovation Solution

The GUI dynamically adjusts the scaling of trellis charts by maintaining consistent axis scales across charts, allowing users to zoom in or out while omitting scale labels to prevent clutter, and enabling comparison of multiple charts with synchronized axes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If separate charts with independently scaled axes are used, then each chart can display its own data range, but users cannot easily compare charts and zooming is ineffective

Engineering Contradiction:
Improvechart scaling flexibilityVSAvoidchart comparison ease
Core Design Contradiction:
Adaptability or versatilityVSEase of operation

Solution Approach 1:

The patent merges the scaling control of multiple charts by implementing a common axis scale across all charts in the trellis chart. This allows users to zoom in or out and pan across the entire trellis chart uniformly, enabling easy comparison between charts while maintaining individual data visualization. The common scale is synchronized across all child charts, resolving the contradiction between individual chart adaptability and overall comparison ease.

Inventive Principle:
Principle #5Merging (Combining)

2Loss of information

If scale labels are displayed on all charts, then data values are clearly indicated, but the display becomes cluttered especially when zoomed in

Engineering Contradiction:
Improvescale label informationVSAvoidvisual clutter
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent applies local quality by making scale label visibility dynamic and location-specific. Scale labels are automatically adjusted based on the zoom level and chart position - they appear on outer charts when zoomed out for context, and are omitted from inner charts when zoomed in to reduce clutter. This selective display maintains necessary information while preventing visual overload in different viewing scenarios.

Inventive Principle:
Principle #3Local quality

3Measurement precision

If users zoom in to view chart details, then detailed data becomes visible, but the overall trellis chart context is lost

Engineering Contradiction:
Improvechart detail visibilityVSAvoidvisible trellis chart area
Core Design Contradiction:
Measurement precisionVSArea of stationary object

Solution Approach 1:

The patent implements a nested viewing structure where users can zoom into individual child charts while the parent trellis chart maintains its overall context. The zoomed-in view is nested within the broader trellis chart framework, allowing users to examine detailed data in a specific chart while understanding its position and relationship to other charts in the overall structure.

Inventive Principle:
Principle #7Nested doll (Nesting)

Data Source

PatentUS10198836B2Trellis chart scaling
Publication Date: 2019.02.05 SALESFORCE INC
  • US10198836B2 patent drawing
  • US10198836B2 patent drawing
  • US10198836B2 patent drawing

AI summary

A non-transitory tangible computer readable medium containing instructions configured to cause one or more processors to execute a process. The process comprises analyzing a dataset to determine a number of variables and one or more types of variables associated with the dataset. One or more processors remove a number of predefined discrete grouping variables from the number of variables associated with the dataset and produces a set of remaining variables. The one or more processors select a chart type based on the number of variables and the one or more types of variables associated with the set of remaining variables and generate one or more charts depicting the dataset. The number of charts generated corresponds to the number of data points associated with the predefined discrete grouping variables.