Data visualization with AI

Data visualization provides a clear, visual representation of research findings. However, this process can be extremely time-consuming. Researchers often face difficulties when choosing an appropriate type of chart or graph and creating visually appealing representations. These tasks are especially challenging for those who do not have strong design skills, which can lead to delays when preparing research for publication.

In addition, the iterative nature of working with visualizations — requiring many rounds of edits to represent data accurately — further increases the time required. As a result, researchers may spend more time creating visualizations than analyzing the data itself, slowing overall progress.

Artificial intelligence offers an effective solution to these problems by automating many routine and complex visualization tasks. Moreover, AI can handle formatting and design, producing professional-looking visuals without requiring specialized graphic design skills. This automation not only saves time but also allows researchers to focus on analysis and interpretation.

AI is also capable of working with large datasets and generating complex visualizations. By increasing the speed and quality of data visualization, AI makes scientific results more accessible and easier to understand.

One of the easiest AI tools to learn is Napkin.AI. It is ideal for researchers who want to quickly and efficiently convert complex data into clear charts, Charts and diagrams. Napkin. AI combines AI capabilities with an intuitive interface, making it accessible even to users without prior AI experience.

To create visuals, you simply paste a text fragment into the context window and click Generate visuals. The AI then offers possible figures and diagram options for the selected text.

The platform also allows you to work with existing visual materials. AI makes it easy to adjust the appearance of charts: change colors, background, brightness, image resolution, add shapes (the sketch function), and add labels and legends (the label function). The resulting visualizations can be downloaded in one of the available formats: PNG, SVG, or PDF.

Napkin.AI analyzes the structure of the data and suggests optimal ways to visualize it. For example, if you are working with time series data, the tool will suggest line charts; for categorical data, it may suggest bar charts or pie charts. This is especially useful for those who are unsure how best to present their data.

Automation of the visualization process helps researchers focus on data analysis rather than formatting. The tool does not require programming skills, making it especially suitable for humanities scholars and early-career researchers.

A major advantage of platforms such as Datawrapper and RAWGraphs is the presence of detailed guides for creating different types of charts, maps, tables, and other visualization formats. These guides not only help beginner researchers master the tools, but also teach the principles of effective information presentation.