AI Visualization Authoring with Automated Data Concept Transformation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face challenges in transforming data sets to create desired visualizations when the formatting is incompatible or unclear, often requiring specialized programs or separate data processing tools.
Innovation Solution
An AI-powered visualization paradigm that separates high-level visualization intents from low-level data transformation steps, using a program synthesizer and/or generative multimodal model to automate data transformation, allowing users to define data concepts in natural language or through examples, and providing feedback for understanding the transformation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually transform data into particular formats using specialized programs or separate data processing tools, then the desired visualization can be created, but the device complexity and ease of operation deteriorate due to requiring multiple external tools and manual intervention
Solution Approach 1:
The patent merges data transformation capabilities and visualization authoring into a single integrated system. The program synthesizer combines multiple functions (data understanding, transformation logic generation, and visualization creation) that previously required separate specialized programs, thereby reducing device complexity while improving ease of operation.
Solution Approach 2:
The system enables self-service data transformation by allowing users to define data concepts in natural language without requiring specialized knowledge of data processing tools. The program synthesizer automatically generates the necessary transformation logic, eliminating the need for users to manually intervene with external software.
2Adaptability or versatility
If specialized programs or separate data processing tools are used to modify incompatible data sets, then formatting compatibility is achieved, but the productivity and loss of time worsen due to requiring additional software and manual processing steps
Solution Approach 1:
The program synthesizer provides universal data transformation capabilities that can handle multiple data formats and visualization requirements through a single system. Instead of requiring different specialized programs for different data formats, the synthesizer adapts to various input formats and generates appropriate transformations, thereby improving productivity while maintaining format compatibility.
Solution Approach 2:
The program synthesizer acts as an intermediary between raw data and visualization tools. It automatically generates the transformation logic needed to convert incompatible data formats into visualization-ready formats, eliminating the need for users to manually use separate data processing tools and significantly improving productivity.
3Ease of operation
If users define data concepts using natural language or examples, then the ease of operation improves, but the extent of automation and manufacturing precision may worsen without AI-powered program synthesis
Solution Approach 1:
The patent replaces manual mechanical data transformation processes with AI-powered program synthesis. Instead of users manually configuring transformation parameters or writing code, the generative model automatically synthesizes transformation programs from natural language definitions, thereby achieving high automation while maintaining ease of operation.
Solution Approach 2:
The system changes the parameter representation from traditional structured data formats to natural language concepts. Users define data concepts using intuitive natural language or examples, and the program synthesizer translates these into precise transformation parameters, maintaining both ease of operation and automation through parameter transformation rather than manual configuration.
4Manufacturing precision
If manual data transformation steps are required, then the manufacturing precision of data formatting is maintained, but the loss of time and productivity deteriorate due to manual intervention
Solution Approach 1:
The program synthesizer performs preliminary analysis of the data and automatically generates transformation logic before the actual transformation execution. By pre-computing the transformation steps based on natural language definitions and data characteristics, the system ensures formatting precision while minimizing the time users need to spend on manual intervention.
Solution Approach 2:
The patent replaces manual mechanical data transformation with automated program synthesis. The AI model generates precise transformation code automatically, maintaining formatting precision that was previously only achievable through careful manual manipulation, while reducing transformation time from minutes or hours to seconds.
Data Source
AI summary
A method, computer program product, and computing system for processing a request to generate a visualization concerning a plurality of data concepts. A new data concept for the visualization is generated by transforming an existing data concept using a program synthesizer and a generative model. The visualization is rendered by processing a mapping of the new data concept to a visual channel of the visualization.