Configurable Hierarchical Data Visualization with Depth Control
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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 effectively analyze hierarchical data and appreciate secondary effects.
Innovation Solution
Implementing a system that allows users to configure aggregation functions, select depth levels, and filter data intuitively through a user interface, enabling customizable data visualization with enhanced user control over depth levels and filtering.
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, but the adaptability to different user needs and data types is limited
Solution Approach 1:
The system transitions from a static, fixed aggregation function to a dynamic configuration where users can select different aggregation functions (SUM, AVERAGE, COUNT, MIN, MAX) based on their specific analysis needs. This allows the treemap generation to adapt to various data types and user requirements while maintaining a manageable system through standardized options.
Solution Approach 2:
The invention introduces configurable parameters including aggregation function selection, depth level specification, and filter criteria. These parameters enable users to customize the treemap generation process without fundamentally changing the system architecture, thus improving adaptability while controlling complexity through parameter-based configuration.
2Loss of information
If multiple depth levels are displayed simultaneously, then the information completeness is improved, but the visual clarity and ease of understanding deteriorates
Solution Approach 1:
The invention segments the hierarchical data into multiple selectable depth levels, allowing users to view the data structure in discrete stages. Instead of displaying all levels simultaneously which would create visual clutter, users can select specific depth levels (e.g., 1-5 levels) to view, maintaining visual clarity while preserving access to complete information when needed.
Solution Approach 2:
The system adds a temporal/interactive dimension to depth level display by allowing users to navigate through different depth levels sequentially rather than displaying all levels in a single static view. This transforms the spatial arrangement problem into an interactive exploration experience, maintaining clarity at each level while providing access to the complete hierarchical structure.
3Productivity
If default filtering is applied, then the data processing speed is improved, but the user control over data selection is reduced
Solution Approach 1:
The system provides a universal filtering mechanism that can operate in multiple modes: default filtering for quick analysis, custom filtering for specific user needs, and no filtering for complete data display. This multi-functional approach allows the same filtering infrastructure to serve both productivity enhancement and user control requirements.
Solution Approach 2:
Users are empowered to configure their own filter criteria based on their specific analysis needs. The system provides the tools and interface for users to define their own filtering rules, allowing them to balance between processing speed and data completeness according to their preferences, rather than imposing a fixed filtering approach.
Data Source
AI summary
Systems and methods in accordance with various embodiments of the present invention provide for representing a plurality of data values of a hierarchical dataset as graphical elements in a configurable data visualization. A first data visualization may be displayed in a data visualization display page, along with a user interface. A selection of a rendered root node and rendered leaf nodes to be displayed in a second data visualization is received from the user interface. Based on the selection of the rendered root node and rendered leaf nodes, a number of depth levels to display is determined. Also, which of the depth levels to display are identified based on the selection of the rendered root node and rendered leaf nodes. The second data visualization is rendered based on the determined number of depth levels and the identified depth levels.