Venn Diagram Visualization for Ranked Data Categories
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Solution Overview
Problem
Existing methods for managing system development issues often overlook lower priority 'Long Tail' data due to focusing on high priority attributes, leading to suboptimal return on investment as they filter out lower priority issues permanently.
Innovation Solution
A Venn diagram is used to display ranked categories of data, where entries are assigned to categories based on attributes and ranked by unique criteria, allowing for visual representation and identification of high value/priority entries through overlapping circles and tag clouds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a manager/developer selects a subset of high priority issues based on a single attribute (e.g., severity) and addresses these first, then the maximum benefit is achieved given constraints on time and resources, but issues having a lower priority for the attribute are filtered out permanently due to continually discovered higher priority issues
Solution Approach 1:
The patent segments the single priority attribute into multiple independent criteria (e.g., severity, frequency, impact, effort). Each criterion is evaluated separately and visualized in its own circle, allowing issues to be assessed from multiple perspectives simultaneously rather than being filtered by a single attribute.
Solution Approach 2:
The patent transitions from a one-dimensional single-attribute priority ranking to a multi-dimensional evaluation space using a Venn diagram. Each criterion adds a new dimension, and the overlapping regions represent issues that satisfy multiple criteria, preserving lower priority issues that may excel in other dimensions.
2Ease of operation
If traditional query tools and filtering methods are used to retrieve and filter data, then data can be retrieved based on specific attributes, but it is difficult to analyze the data and compare two result sets
Solution Approach 1:
The patent merges multiple query result sets into a single Venn diagram visualization. Each circle represents a query result set, and the overlapping regions automatically show the intersection of results, enabling direct visual comparison without requiring separate analysis of multiple result sets.
Solution Approach 2:
The Venn diagram serves as an intermediary visualization layer between the raw query results and the user's analysis needs. It transforms complex multi-set relationships into an intuitive visual format that preserves all comparative information while easing analysis.
3Ease of manufacture
If visual approaches such as tag clouds or bar charts are used to present data, then qualitative characterization or quantity-based presentation is achieved, but relationships between multiple criteria and entries cannot be identified
Solution Approach 1:
The patent performs preliminary organization of data by criteria before visualization. Each criterion is pre-defined and its result set is prepared in advance, then automatically positioned in the Venn diagram structure. This preliminary organization preserves the relationships between criteria and entries while enabling intuitive visual presentation.
Data Source
AI summary
A solution that displays ranked categories of data in a Venn diagram is provided. In particular, entries of data are assigned to one of a plurality of categories based on one or more attributes of the entries. The categories are then ranked for each of one or more criteria. Each criterion can use a unique set of the attributes to rank the categories. A Venn diagram is generated that includes a circle for each criterion and displays the rankings of the various categories using one or more visual representations of each category. For example, the rankings can be displayed using tag clouds for each category that are placed in each circle. Two or more circles can overlap in which case categories that have one or more entries that meet all the corresponding criteria can be displayed in the overlapping portion of the circles.