Dynamic Cell Density Visualization for Growing Time Series Data
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Solution Overview
Problem
Conventional visualization techniques fail to effectively display and analyze large numbers of time intervals for long, multi-dimensional time series data, making it difficult for users to identify patterns, trends, and anomalies, especially when data is continually growing.
Innovation Solution
A visualization method that uses a cell-based display with varying density, where the size of the display region remains constant by reducing the size of blocks as more data is added, allowing for real-time monitoring and easy identification of data patterns through color coding and drill-down capabilities, enabling users to view multiple time series in a single view without scrolling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional visualization techniques are used to display time series data, then the display can accommodate a limited number of time intervals, but as data continues to grow, users cannot effectively analyze patterns, trends, and anomalies in a single view
Solution Approach 1:
The display is segmented into a grid of cells arranged in rows and columns, where each cell represents a specific time interval. This segmentation allows the system to organize large amounts of time series data into a structured format that can be viewed comprehensively without scrolling, resolving the contradiction between displaying many time intervals and maintaining ease of analysis in a single view.
Solution Approach 2:
The patent transitions from conventional linear time series displays to a two-dimensional grid layout where time intervals are distributed across both rows and columns. This dimensional change enables the system to accommodate a much larger number of time intervals while maintaining a compact, scrollable view that preserves analytical effectiveness.
2Quantity of substance
If the display region size is increased to accommodate more time intervals, then more data can be displayed, but the display becomes harder to navigate and analyze
Solution Approach 1:
The display region is divided into a grid of cells with varying densities, where cells in different regions can represent different numbers of time intervals. This segmentation allows the system to pack more data into the display without uniformly increasing the entire display area, thereby maintaining navigation ease while accommodating more time intervals.
Solution Approach 2:
Different regions of the display grid are assigned different cell densities based on local data requirements. Some cells may represent single time intervals while others represent aggregated intervals, allowing the display to adapt its granularity locally. This local quality variation enables efficient use of display space and maintains ease of navigation while displaying a large total number of time intervals.
Data Source
AI summary
To visualize growing time series data, first data values of a time series are presented for display in a single view, where the data values are for display in cells according to a first density in the view. Additional data values of the time series are received, and a density of the view is modified in response to receiving the additional data values. The first data values and additional data values are presented for display in cells arranged according to the modified density in the view.