Visualization Interface Threshold Selectability for Data Groupings
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing visualization interfaces for three-dimensional data lack an efficient method for users to selectively choose data portions, making it cumbersome to understand and analyze data effectively.
Innovation Solution
A graphical visualization program that allows users to control selectability through a threshold setting based on data attributes like size, volume, color, or opacity, using a selectability slide bar to determine which data objects or groupings are selectable, ensuring only data meeting the set criteria can be selected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If all data objects are made selectable in the visualization interface, then users can access any data portion, but it becomes difficult to distinguish and select relevant data from overlapping objects
Solution Approach 1:
The patent applies local quality by assigning different selectability states to different data objects based on their individual properties. Each data object can have its own selectability attribute that is determined by evaluating its characteristics against threshold criteria, allowing selective interaction rather than uniform selectability across all objects
Solution Approach 2:
The patent changes the parameter of selectability from a binary state to a threshold-based continuous evaluation. By introducing selectability thresholds that can be adjusted based on data object properties (such as opacity, size, or custom attributes), the system dynamically determines which objects are selectable, resolving the contradiction between accessibility and selectability clarity
2Productivity
If selectability thresholds are set to include all data objects, then comprehensive data access is enabled, but irrelevant or low-quality data becomes selectable reducing analysis effectiveness
Solution Approach 1:
The patent introduces adjustable threshold parameters that define the boundary between selectable and non-selectable data objects. These thresholds can be set based on various data attributes (opacity, size, custom properties) and can be modified to balance between comprehensive access and precise selection, directly addressing the contradiction between productivity and precision
Solution Approach 2:
The selectability thresholds are designed to be dynamic and adjustable rather than fixed. Users can modify threshold values to adapt to different analysis needs, allowing the system to transition between being more inclusive (higher productivity) or more selective (higher precision) based on the current analytical context
3Loss of information
If multiple data objects with similar properties are displayed, then comprehensive data visualization is achieved, but it becomes cumbersome to specify which portions should be selectable
Solution Approach 1:
The patent implements self-service by allowing data objects to automatically evaluate their own selectability based on their intrinsic properties and predefined threshold criteria. Instead of requiring users to manually specify which objects should be selectable, the system autonomously determines selectability status, eliminating the complexity of manual specification while maintaining complete visualization
Solution Approach 2:
The system uses parameter-based automatic determination of selectability by comparing data object properties (such as opacity values, size metrics, or custom attributes) against threshold parameters. This automated parameter comparison eliminates the need for complex manual selection specifications while preserving all data in the visualization
Data Source
AI summary
A user of a graphical visualization program controls what data is selectable through the program interface. Data for display may be grouped and assigned an opacity value. The opacity value may correspond to the number of data points within an n-dimensional grouping, a particular type or other grouping parameter. Two or more data groupings may overlap within the interface. The visualization program may set a threshold selectability level, for example based on user input. The input may be received based on an selection threshold slide bar within a graphical portion of the display. When a user selects a data grouping at a point where two or more data groupings overlap, the data groupings that satisfy the threshold selection level may be selected. Data groupings that do not satisfy the threshold selection level will not be selectable.