Summary Graphs for Large Dataset Visualization
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Solution Overview
Problem
Displaying large datasets in graph form can be cumbersome, making it difficult for users to interact with the data meaningfully due to clutter, and even subsets of data from large databases can be too extensive to be effectively displayed on a single screen.
Innovation Solution
A visualizer constructs summary graphs that collapse multiple data instances into summary nodes and property edges, allowing users to navigate and expand details, enabling a "fish eye" view that integrates summaries with non-summarized data, and can be queried and stored in the same format as non-summarized data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all data from large databases is displayed in graph form, then complete data coverage is achieved, but the display becomes cluttered and difficult to interact with
Solution Approach 1:
The patent divides the large dataset into multiple levels of granularity: summary level (aggregated data) and detailed level (individual data instances). Users can navigate between these levels, viewing summarized data at one level and expanding to detailed instances when needed, thus maintaining both complete data coverage and ease of interaction.
Solution Approach 2:
The patent introduces an additional dimension of interaction by allowing users to expand and collapse nodes in the graph. This transforms a static 2D display into a multi-level hierarchical structure that can be navigated vertically (between summary and detail levels) while maintaining the horizontal graph layout, effectively adding a Z-dimension to the display.
2Ease of operation
If a subset of data is displayed to reduce clutter, then ease of interaction improves, but complete data coverage is lost
Solution Approach 1:
The patent implements a dynamic display system where the graph adapts to user interactions. Nodes can be expanded to show more details or collapsed to show summaries, allowing the data coverage to dynamically adjust based on user needs while maintaining ease of interaction at any level of detail.
Solution Approach 2:
The patent implements a nested structure where detailed data instances are contained within summary nodes. When a summary node is expanded, it reveals the individual data instances that compose it, creating a nested hierarchy that preserves complete data coverage while allowing users to interact with data at appropriate levels of abstraction.
3Loss of information
If detailed data instances are displayed, then data completeness is maintained, but screen space requirements increase
Solution Approach 1:
The patent applies different levels of detail to different parts of the graph based on user interaction. Summary nodes provide aggregated information for areas with many instances, while expanded nodes provide detailed information for specific areas of interest, optimizing screen space usage while maintaining information completeness where needed.
Solution Approach 2:
The patent segments the display into summary regions and detailed regions. Summary nodes condense multiple data instances into single visual elements, reducing screen space requirements, while detailed views can be expanded in specific locations when users need to examine individual instances, maintaining information completeness without permanently increasing screen space usage.
Data Source
AI summary
Systems, methods, and other embodiments associated with visualizing data using summary graphs are described. One example method includes constructing a summary graph for display. The summary graph represents the data as a summary node having a plurality of property edges connected to the summary node. The summary node represents the set of values for the node in the data.