Visualization Engine Adapting Data Presentation to Display Attributes
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Solution Overview
Problem
Users face time-consuming and skill-intensive processes when generating graphical representations of numerical data from search engine results, requiring specialized programs and expertise.
Innovation Solution
A computer program system and method that automatically generates visualizations of data points by analyzing display device capabilities and screen dimensions, using machine learning and AI to determine optimal presentation types, sizes, and detail levels, eliminating the need for user expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users manually select and import data into spreadsheet programs to generate visual representations, then the quality and customization of data visualization can be improved, but the time consumption and operational complexity increase significantly
Solution Approach 1:
The system automatically retrieves data points from search engines, determines optimal visualization parameters, and generates visual representations without requiring user intervention in data selection or import processes. The system serves itself by autonomously completing tasks that previously required manual user actions.
Solution Approach 2:
The system performs preliminary actions by pre-determining the optimal visualization type, size, and level of detail based on display device capabilities before the user even requests the visualization. Data is retrieved and processed in advance, so when the user needs the visualization, it is already prepared or can be generated immediately.
2Manufacturing precision
If users employ specialized graphing programs and skills to produce optimal data presentations, then the effectiveness and optimality of data visualization can be improved, but the ease of operation deteriorates due to requiring specialized knowledge
Solution Approach 1:
The system automatically determines the optimal visualization parameters including type, size, and level of detail by analyzing display device capabilities and data characteristics. This eliminates the need for users to possess specialized knowledge of graphing programs or visualization best practices, as the system performs these expert functions autonomously.
Solution Approach 2:
The system acts as an intermediary between the user's simple data retrieval request and the complex requirements of optimal data visualization. It translates user intent into optimized visual presentations by automatically selecting appropriate visualization types and parameters based on display capabilities, shielding the user from complexity.
3Productivity
If automated systems generate visualizations without considering display device attributes, then the speed of visualization generation can be improved, but the adaptability and optimal rendering across different devices deteriorates
Solution Approach 1:
The system determines visualization parameters specific to each display device's capabilities and attributes. Instead of using a one-size-fits-all approach, it customizes the visualization type, size, and level of detail to match the particular characteristics of the target display device, ensuring optimal rendering for each specific context.
Solution Approach 2:
The system dynamically adjusts visualization parameters based on real-time analysis of display device capabilities. Rather than using static, pre-defined visualization settings, it adapts the visualization characteristics to match the specific attributes of the display device, making the system flexible and responsive to different rendering environments.
Data Source
AI summary
Provided are a computer program product, system, and method for generating a visualization of data points returned in response to a query based on attributes of a display device and display screen to render the visualization. A determination is made of inputs comprising area dimensions of the display screen and capabilities of the display device to render data points retrieved in response to a query. The inputs and the data points are provided to a visualization engine to output a type of visual presentation for the data points, a size of the visual presentation to render on the display screen, and a level of detail to aggregate the data points to render on the display screen. A visualization is generated to render on the display screen the data points in the type of visual presentation according to the size of the visual presentation and with the level of detail.