Graphical Risk Model for Unbiased Data Collection
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Solution Overview
Problem
Conventional risk assessment methods suffer from biases in data collection and fail to effectively visualize the interconnections between risks, making it difficult to accurately analyze and present risk data.
Innovation Solution
A method and system that uses graphical objects on a user device to collect and display risk data through gesture inputs, creating a graphical risk model that represents interconnectedness, likelihood, severity, and velocity, with features like node-link graphs, node clusters, and centrality analysis to provide a holistic and unbiased view of risk data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surveys are used to collect risk data, then data collection can be performed, but biases lead to inaccuracies in the collected risk data
Solution Approach 1:
The patent replaces textual survey mechanisms with graphical interaction mechanisms. Users interact with graphical objects representing risks through gestures (clicking, dragging, sliding) to collect risk data. This substitution eliminates the biases inherent in textual surveys while maintaining accurate data collection, as the graphical interface provides intuitive and direct input methods that reduce cognitive biases and response errors.
2Loss of information
If spreadsheets are used to present risk data, then risk data can be stored and analyzed, but interconnections between risks are buried in tables, columns and rows
Solution Approach 1:
The patent transforms the two-dimensional spreadsheet structure into a three-dimensional graphical representation. Risks are represented as graphical objects that can be spatially arranged and interconnected through lines and nodes. This dimensional transition makes interconnections between risks visually explicit and easily perceivable, eliminating the need to navigate through rows and columns to understand relationships between risks.
Solution Approach 2:
The patent merges multiple data dimensions (risk properties, interconnections, and relationships) into a single integrated graphical model. The graphical risk model combines risk identification, interconnectedness, and data collection into one unified interface, making all risk information accessible and visible simultaneously rather than分散 across multiple spreadsheet elements.
3Difficulty of detecting and measuring
If conventional risk assessment methods are used, then risk data can be collected and analyzed, but it is difficult to visualize interconnections and perform sophisticated analysis
Solution Approach 1:
The patent introduces a graphical risk model as an intermediary between raw risk data and analysis objectives. This intermediary layer visually represents risks and their interconnections through graphical objects and connecting lines, making complex relationships easily detectable and measurable. The graphical model serves as a mediator that simplifies the detection of risk interconnections and enables sophisticated analysis through intuitive visual inspection rather than complex data processing.
Data Source
AI summary
A method, comprising: displaying, on a user device, graphical objects representing risks; receiving, from the user device, gesture inputs via the graphical objects to collect risk data for the risks; providing a graphical risk model representing the risks and the collected risk data for display on the user device.