Visualization Selection System for Automated Chart Generation
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Solution Overview
Problem
Existing report generation tools limit users to displaying information in tabular form, with users avoiding the use of charts and maps due to difficulties in associating data with axes and completing chart creation tasks.
Innovation Solution
A computer-implemented method that selects a portion of a data set in a first visualization, generates a list of relevant visualizations based on the context, and renders a second visualization chosen by the user, using a set of rules to define input and display quantitative information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users manually create charts and maps by associating data with axes and completing chart creation tasks, then visualization quality can be controlled, but the complexity and difficulty of operation increases significantly
Solution Approach 1:
The system automatically generates visualizations by having the data and context serve themselves. The visualization generator module autonomously selects appropriate chart types, maps data to visual elements, and renders charts without requiring users to manually associate data with axes or complete complex creation tasks.
Solution Approach 2:
The system performs preliminary analysis of the data set and context before visualization generation. By pre-processing the data, understanding its structure and relationships, and pre-selecting appropriate visualization types based on context, the system eliminates the need for users to perform difficult manual configuration tasks.
2Adaptability or versatility
If report generation tools provide diverse chart and map types, then visualization versatility improves, but users still avoid using them due to operational complexity
Solution Approach 1:
The system introduces an intermediary visualization generator module that acts as a mediator between the user's simple data selection and the complex visualization creation process. This intermediary automatically handles the complexity of selecting and configuring diverse chart types, providing versatility without exposing users to tool complexity.
Solution Approach 2:
The visualization system serves itself by automatically determining which diverse chart types are appropriate for given data and context. The system independently navigates the complexity of multiple visualization options and selects the most suitable ones, eliminating the need for users to understand or manage tool complexity.
3Reliability
If users are required to perform multiple steps to create visualizations, then control over the visualization process is maintained, but productivity decreases
Solution Approach 1:
The system performs the multi-step visualization creation process autonomously. The visualization generator module automatically executes all necessary steps including data analysis, chart type selection, data mapping, and rendering without requiring user intervention at each step, thereby maintaining process reliability while dramatically improving productivity.
Solution Approach 2:
The system performs preliminary preparation work including data validation, context analysis, and visualization planning before the actual visualization creation. This preliminary action enables the system to execute the visualization generation process efficiently and reliably without requiring users to perform multiple manual steps.
Data Source
AI summary
A computer implemented method includes selecting a portion of a data set in a first visualization. A list of visualizations relevant to the context inferred from the selection of the portion of the data set in the first visualization is generated. A second visualization from the list of visualizations is rendered.