Exploration Mode Chart Rendering for Large Data Sets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing analytical applications face challenges in rendering large-scale charts efficiently, often resulting in data point overlap and reduced data visibility, as they either limit the data shown or take significant time to render, which can lead to less data being available for analysis.
Innovation Solution
The proposed solution involves generating exploration mode charts that allow for the visualization of large data sets by partitioning data into multiple charts, with a main chart, primary charts, and helper charts, enabling users to view all data points without overwhelming the user interface, while improving system performance through parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the amount of data shown in a chart is limited to accelerate rendering or reduce overlap, then rendering speed and visual clarity are improved, but the quantity of data available for analysis is reduced
Solution Approach 1:
The patent divides a large data set into multiple smaller data subsets, each rendered in a separate chart. This segmentation allows the system to render charts faster (improving productivity) while still providing access to all the original data points across the collection of charts (maintaining quantity of data). Users can navigate between multiple charts to view complete data sets without overwhelming the interface with a single large chart.
2Ease of operation
If the amount of data shown in a chart is limited to reduce data point overlap, then visual clarity is improved, but the quantity of data available for analysis is reduced
Solution Approach 1:
By segmenting the data into multiple charts with fewer data points each, the patent eliminates data point overlap and improves visual clarity in each individual chart. At the same time, the collection of multiple charts collectively displays all the data points from the original large data set, ensuring that the total quantity of data remains intact for analysis.
3Quantity of substance
If multiple charts are generated to display all data points, then the quantity of data is improved, but the device complexity increases
Solution Approach 1:
The system automatically segments the data set into appropriate subsets and generates the corresponding multiple charts based on predefined criteria. This automated segmentation process manages the complexity by systematically dividing the data rather than requiring manual intervention, thereby improving data quantity while keeping system complexity manageable through algorithmic organization.
Solution Approach 2:
The patent creates a multi-functional chart system where multiple charts work together as a unified visualization tool. Each individual chart serves as a functional unit displaying a subset of data, while collectively they provide the complete data view. This multi-functionality approach manages complexity by creating standardized, interchangeable chart units that can be systematically combined.
Data Source
AI summary
A process for providing a plurality of exploration mode charts to supplement a base chart is provided herein. A request for exploration mode charts may be received. The request may include a data set definition. A total number of data points for the request may be determined based on the data set definition. A total number of exploration mode charts may be determined based at least in part on the total number of data points for the request. Chart data may be obtained for a plurality of exploration mode charts based on the data set definition. The plurality of exploration mode charts may include a number of charts less than or equal to the total number of exploration mode charts. The plurality of exploration mode charts may be rendered via the chart data. The rendered exploration mode charts may be provided.