3D Graph Rendering Engine for Big Data Visualization
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Solution Overview
Problem
Current data processing technologies are inadequate for handling and visualizing large and complex 'big data' sets, making it difficult to extract valuable insights and make confident decisions.
Innovation Solution
A system and method for generating and viewing three-dimensional (3D) graphs, where each partition of the graph corresponds to a data record and its surface features vary based on data field values, allowing for efficient visualization and correlation of data using a rendering engine and graph data viewer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional data processing applications are used to handle big data sets, then data processing can be performed with simple tools, but the applications are inadequate for analyzing, visualizing, and extracting value from large and complex data sets
Solution Approach 1:
The patent transforms complex multi-dimensional data into a three-dimensional spherical visualization where each dimension of data is represented spatially. The rendering engine maps data fields to spherical coordinates and visual properties, allowing complex relationships to be perceived intuitively in 3D space rather than through complex tabular or graphical interfaces.
Solution Approach 2:
The data set is divided into multiple data records, each represented as a distinct partition or region on the spherical surface. This segmentation allows individual data records to be visualized separately while maintaining their relationships within the whole, enabling analysis of both individual and collective data properties.
2Loss of information
If data sets are visualized in traditional two-dimensional formats, then visualization can be achieved with simple displays, but it is difficult to efficiently compare and contrast data relationships and extract insights
Solution Approach 1:
The system transitions from traditional two-dimensional data visualization to a three-dimensional spherical representation. Data relationships are encoded in spatial arrangements, angles, and distances on the sphere's surface, allowing multiple variables to be simultaneously visualized and compared without the clutter inherent in 2D charts and graphs.
Solution Approach 2:
The rendering engine varies visual properties of spherical partitions based on data field values, including color, brightness, and texture. This allows different data dimensions to be encoded visually, enabling users to quickly identify patterns, outliers, and relationships through intuitive visual cues rather than interpreting numerical data.
Data Source
AI summary
A rendering engine can generate a three-dimensional (3D) graph. The 3D graph can include a plurality of partitions contiguously connected. Each partition corresponds to a respective data record in a data set and a surface of each partition corresponds to a given parameter that references a given data field in the respective data record. Visual indicia of the surface of each partition can vary as a function of a value for the given data field of the respective data record.