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Generative AI Agents as Generalized Data Visualization Tools
Morgan A Vincent1, Benjamin J Lear2
1Department of Chemistry, Penn State University, University Park, PA, USA.
Methods in Molecular Biology (Clifton, N.J.)
|July 9, 2026
Summary
Scientists can now create data visualizations using natural language prompts with AI chatbots. These tools simplify plotting by acting as a front-end for coding languages, removing the need for specialized software knowledge.
Area of Science:
- Scientific Visualization
- Data Science
- Artificial Intelligence
Background:
- Data visualization is essential for scientists.
- Current tools (GUI-based like Origin/Excel, text-based like Python/R) require specialized knowledge of plotting structures.
- This creates a barrier to entry for effective data presentation.
Purpose of the Study:
- To demonstrate the use of Large Language Model (LLM)-based generative AI chatbots for data visualization.
- To show how natural language interfaces can simplify data processing and plotting.
- To reduce the technical expertise required for creating scientific plots.
Main Methods:
- Utilizing LLM-based generative AI chatbots capable of writing and executing code.
- Employing a natural language interface to interact with the AI for data manipulation and visualization.
- Leveraging the AI as a generalized front-end for existing text-based plotting tools.
Main Results:
- AI chatbots can successfully process data and generate visualizations based on natural language commands.
- The need for in-depth knowledge of specific plotting tool terminology is significantly reduced.
- A simplified workflow for data visualization is achieved through AI interaction.
Conclusions:
- LLM-based AI chatbots offer a powerful and accessible method for scientific data visualization.
- Natural language interfaces democratize the creation of plots, making it easier for scientists to present their findings.
- This approach streamlines the visualization process, enhancing scientific communication.
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