Multidimensional Data Visualization System with Spatial Merging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data modeling systems lack the ability to provide intuitive, spatial representations of multiple data categories on a single scale, requiring multiple models and computational comparisons to visualize patterns and trends, which is inefficient and redundant.
Innovation Solution
A system that creates a virtual environment for displaying multidimensional data models, allowing users to navigate and manipulate data intuitively by combining data categories into logical combinations, using a user interface that enables the selection and combination of data categories, and displaying these in various formats such as 2D and 3D visualizations, including cartographic and tree structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple independent models are used to display different data categories, then each data category can be visualized separately, but the system complexity increases and redundancy is created
Solution Approach 1:
The patent combines multiple data categories into a single integrated spatial representation model. Different data categories (e.g., population density, income levels, education statistics) are displayed simultaneously on the same geographical map using multiple visual encoding channels, eliminating the need for multiple separate models and reducing system complexity while maintaining the ability to visualize diverse data types
Solution Approach 2:
The spatial representation model serves as a universal framework that can display multiple types of data categories through a single interface. The system uses a unified model structure that supports various data visualizations (heat maps, choropleth maps, scatter plots) within the same spatial framework, making the system adaptable to different data types without requiring separate specialized models
2Loss of information
If multiple independent models are used to visualize patterns and trends, then comprehensive analysis is possible, but computational overhead and processing time increase
Solution Approach 1:
The system merges multiple data categories into a single spatial model that enables simultaneous visualization and comparison. By displaying multiple data dimensions in one integrated view, the system eliminates the need for sequential computational comparisons across multiple models, reducing processing time while maintaining complete analytical capability
Solution Approach 2:
The patent adds visual encoding dimensions (color intensity, size, shape) to the spatial representation, allowing multiple data categories to be displayed simultaneously without increasing computational complexity. This dimensional enrichment enables comprehensive data analysis within a single model by encoding additional information channels that can be processed and compared efficiently
3Measurement precision
If data is displayed in detailed formats, then precision is improved, but the interface becomes less intuitive and harder to navigate
Solution Approach 1:
The system applies different levels of detail and visualization styles to different regions or aspects of the data based on user interaction. Frequently accessed or important data categories receive more detailed representation, while less critical areas maintain simpler visualizations. This localized differentiation maintains precision where needed while preserving overall interface intuitiveness and ease of navigation
Data Source
AI summary
A virtual environment is provided for displaying multidimensional models of data. Embodiments of the system provide an interface which allows a user to navigate intuitively and efficiently between alternative views of the data represented in the model, and to combine additional data categories with the existing model. Embodiments of the system draw upon cellular data stored in a database structure to represent the data in a graphical form on a visual display, wherein cellular data are data partitioned by at least two interrelated data categories into discrete ‘cells’. Models may be manipulated, viewed and compared using a user control device, such as a touch screen display. Alterations to the data stored in the database may be represented by commensurate changes to the objects displayed in the model, and the relational forms and shapes formed between the categories of data.