Heat Map Data Visualization Using Tree Structure Aggregation
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Solution Overview
Problem
Heat maps struggle with large data sets, often requiring truncation or aggregation of data values, which hinders data analysis by limiting the number of cells in the grid and masking original data information.
Innovation Solution
A method that uses a tree data structure to map data records to cells in a grid, allowing for dynamic value aggregation and updated display properties based on zoom states, enabling efficient visualization of large data sets by merging values when necessary, while maintaining access to underlying data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple data values are represented by a single cell with aggregation, then the heat map can display large data sets within limited grid cells, but the original data information becomes hidden and data analysis is hindered
Solution Approach 1:
The patent implements a hierarchical tree data structure where internal nodes represent aggregated values and leaf nodes represent individual data records. This nesting allows multiple levels of aggregation: individual records can be viewed when zoomed in, while aggregated summaries are automatically displayed when zoomed out, enabling the heat map to accommodate large data sets without permanently hiding original data information
Solution Approach 2:
The patent introduces dynamic zoom functionality that changes the level of aggregation based on user interaction. When users zoom in, individual data records become visible; when users zoom out, aggregated values are displayed. This dynamic adjustment allows the same heat map to serve both detailed analysis and high-level overview needs, resolving the contradiction between displaying many data values and preserving original information
2Quantity of substance
If the heat map grid is expanded to accommodate more data values, then more data can be displayed without aggregation, but the grid complexity and device requirements increase
Solution Approach 1:
The patent merges multiple data records into single visual cells through aggregation functions (sum, average, count, etc.) when the number of records exceeds the number of available grid cells. This merging reduces the visual complexity of the heat map while preserving the ability to access individual records through the tree structure and zoom functionality, thus accommodating large data sets without proportionally increasing grid complexity
Data Source
AI summary
Large data sets (e.g., with millions of records) are represented by a heat map within a user interface (UI). Each record in the data set includes a label. The labels of the records are assigned to leaf nodes of a data structure. The leaf nodes are mapped to a grid of cells according to a layout method. Furthermore, values are determined for the cells based on data records having the labels mapped to the cells. A visual property is selected for each cell based on the corresponding value. Since the data labels are stored in leaf nodes that are connected to internal nodes, if a zoom state of the heat map results in a display of a number of data labels that exceeds the number of cells in the grid, values of the cells can be updated according to values determined from the internal nodes without losing the connections between the cells and the underlying leaf nodes.