Configurable Aggregate Layout for Hierarchical Data Visualization
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Solution Overview
Problem
Current data visualization techniques, such as treemaps, lack flexibility in varying aggregation functions, depth level selection, and intuitive filtering, making it difficult for users to gain meaningful insights from hierarchical data sets.
Innovation Solution
Implementing a system that allows users to configure aggregate functions, select visible depth levels, and filter data visualizations intuitively, enabling users to customize the representation of data through a user interface and automate the selection of appropriate aggregation functions based on user expectations and data properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed aggregation function is used in treemap generation, then the system complexity is reduced and implementation is simplified, but the adaptability to different user needs and data types is limited
Solution Approach 1:
The system dynamically selects aggregation functions based on data properties and user preferences rather than using a fixed method. The aggregation function can change adaptively depending on the hierarchical level, data type, and user configuration, making the treemap generation flexible and versatile across different scenarios
Solution Approach 2:
The system allows changing the aggregation function parameter from fixed to variable, enabling selection among multiple functions (summation, count, average, etc.). This parameter change transforms the rigid system into an adaptable one that can respond to different data characteristics and user needs
2Adaptability or versatility
If the number of visible depth levels is fixed, then the rendering process is simplified and faster, but the user's ability to explore data at different levels of detail is restricted
Solution Approach 1:
The system dynamically adjusts the number of visible depth levels based on user interaction and data characteristics. Users can configure which depth levels to display, and the system adapts the rendering process accordingly, enabling flexible exploration of hierarchical data at appropriate levels of detail
Solution Approach 2:
The treemap system is designed to handle multiple depth levels universally, allowing users to view and interact with data at any hierarchical level. The same rendering engine supports both shallow and deep hierarchical views, making the system versatile for different analytical needs
3Ease of operation
If default filtering is applied without user input, then the initial visualization is ready faster, but the user cannot easily isolate and analyze specific data patterns or outliers
Solution Approach 1:
The system provides self-service filtering capabilities where users can directly interact with the treemap visualization to select and filter data points of interest. Users can click on cells to drill down or filter related data without requiring complex configuration, making the filtering process intuitive and efficient
Solution Approach 2:
The system prepares filtering options and drill-down capabilities in advance, so when users want to analyze specific patterns, the filtering mechanisms are already in place and ready to use. Common filter scenarios are pre-configured to reduce the time needed for users to start their analysis
Data Source
AI summary
Systems and methods in accordance with various embodiments of the present invention provide for representing a hierarchical dataset as graphical elements in a configurable data visualization having at least one graphical attribute. At least one aggregate function of a plurality of aggregate functions are determined. Aggregate values of the hierarchical dataset for each hierarchical depth level is determined. The aggregate function is used to determine the aggregate values. The data visualization based on the aggregate values is rendered.