Automated Visualization Format Selection via Business Rules
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Solution Overview
Problem
Current data visualization systems require extensive user interaction and knowledge to select the appropriate visualization format, making the process time-consuming and inefficient, especially with the increased number of visualization options available.
Innovation Solution
The proposed method uses Adaptive Data Markup Language (ADML) to identify and recommend optimal visualization formats by analyzing data patterns, user preferences, and applying business rules, eliminating the need for user intervention and dynamically generating a visualization script for displaying input data in the most suitable format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user interaction is required to select visualization format, then user can choose appropriate format, but time consumption and complexity increase
Solution Approach 1:
The system automatically analyzes data parameters and user preferences to select the optimal visualization format without requiring user interaction. The algorithm evaluates data characteristics (categorical, numerical, time-series) and applies business rules to determine the most appropriate chart type, enabling the system to serve itself in the format selection process.
Solution Approach 2:
The system pre-establishes a comprehensive set of business rules and data parameter mappings before visualization is needed. By having the format selection logic pre-configured based on data characteristics, the system eliminates the need for real-time user decision-making during the visualization process.
2Measurement precision
If user knowledge about visualization environment is required, then user can make informed selections, but accessibility and ease of use decrease
Solution Approach 1:
The system introduces an intelligent intermediary layer that translates data characteristics into appropriate visualization formats. This intermediary algorithm acts as a mediator between the raw data and the user, automatically applying domain knowledge and business rules to select the optimal format without requiring the user to possess specialized visualization expertise.
Solution Approach 2:
The system performs the knowledge-intensive task of format selection autonomously by analyzing data parameters against pre-defined business rules, eliminating the need for users to have expert knowledge about visualization environments while maintaining high accuracy in format selection.
3Adaptability or versatility
If multiple visualization options are provided, then user has more choices, but selection process becomes more complex and time-consuming
Solution Approach 1:
The system applies different selection strategies based on local data characteristics. By evaluating specific data parameters (categorical vs numerical, time-series patterns, distribution characteristics) and applying context-appropriate business rules, the system narrows down the broad range of visualization options to the most suitable format for that specific data context, maintaining versatility while reducing complexity.
Solution Approach 2:
The system dynamically adjusts the selection process by changing parameters such as data type, data volume, and business context to determine the optimal visualization format. By monitoring and responding to these parameter changes, the system can efficiently navigate through multiple visualization options and select the most appropriate one without requiring users to manually evaluate each option.
Data Source
AI summary
Disclosed herein is a method and a system for processing input data for display in an optimal visualization format. The method includes receiving of the input data and identifying one or more visualization formats for displaying the input data based on preferences of the user. An optimal visualization format is identified by applying business rules on each of the identified visualization formats for displaying the input data in the optimal visualization format. In an embodiment, the instant disclosure helps in selecting a most relevant visualization format for displaying the input data. Also, one or more business interpretations and statistics related to the input data are displayed along with the input data, thereby helping users in analyzing and interpreting the input data.