Data-Bound Axis Generation for Adaptive Data Visualizations
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Solution Overview
Problem
Existing data visualization techniques require manual drawing or specialized coding to create and update axes, making it time-consuming and labor-intensive to adapt to changes in datasets or scales.
Innovation Solution
Automatically generate a data-bound axis by creating an axis dataset based on the scale of graphic objects, allowing for easy customization and automatic updates when the scale changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual drawing or specialized coding is used to create axes, then customization and precision are improved, but time consumption and labor intensity increase
Solution Approach 1:
The system automatically generates axes by binding graphic objects to data scales, allowing the axis to self-update when data changes. This eliminates manual redrawing while maintaining precision through data-driven automatic adjustment of tick marks, labels, and axis positions.
Solution Approach 2:
The patent pre-establishes the binding relationship between graphic objects and data scales before data changes occur. This preliminary binding enables automatic axis generation and update, avoiding the need for manual intervention when data or scales change.
2Ease of manufacture
If manual drawing or specialized coding is used to create axes, then design control is improved, but ease of operation deteriorates
Solution Approach 1:
The axis automatically binds to data scales and updates itself when data changes, eliminating the need for manual operation. Users simply need to provide the data, and the system handles axis generation and updates autonomously.
Solution Approach 2:
The patent replaces manual mechanical drawing operations with automated computational processes. The system uses data binding and programmatic generation to create axes, substituting manual operations with automated algorithms that calculate tick marks, labels, and positions based on data scales.
3Adaptability or versatility
If axes are manually created, then adaptability to design changes is improved, but productivity deteriorates
Solution Approach 1:
The patent creates dynamic axes that automatically adapt to data changes through binding relationships. When data scales change, the bound graphic objects and axes automatically adjust their positions, tick marks, and labels, providing both adaptability and high productivity simultaneously.
Solution Approach 2:
The system establishes a feedback loop where data changes automatically trigger axis updates through the binding relationship. The axis continuously monitors data scale changes and adjusts itself accordingly, ensuring adaptability while eliminating manual intervention and improving productivity.
Data Source
AI summary
Embodiments are disclosed for generating a data-bound axis for a data visualization. In some embodiments, a method of generating a data-bound axis for a data visualization includes receiving a data set and generating a chart including a plurality of graphic objects based on the data set and a visual property of the plurality of graphic objects. A scale associated with the chart is determined based on the data set and the plurality of graphic objects. At least one axis graphic object is generated based on the scale. The at least one axis graphic object is added to the plurality of graphic objects of the chart.