Scientific illustrators work in domains where ambiguity is expensive. A visual can make or break a scientific paper: it can explain a mechanism, guide a reader through a process, or help a non-specialist understand something that would otherwise remain locked behind expert language.
That makes the craft of scientific illustration highly relevant for information designers, technical communicators, and anyone working with complex knowledge. The best scientific visuals do three things extremely well: they guide attention, reduce unnecessary detail, and make complex relationships legible.
A scientific figure might start as a dense set of concepts, pathways, labels, and experimental details. A technical manual might start as engineering notes, screenshots, CAD exports, safety requirements, and product knowledge scattered across teams. These are different domains, but it's the same chaos.
The guiding principles for conceptual figures of the scientific journal Nature make the core principle very clear: scientific diagrams contain layers of complex information, and the job of visual communication is to guide the eye to the most important information first. Hierarchy should reflect the information hierarchy, using color, focus, and drawing technique deliberately.
For information designers, the lesson is: do not start with layout. Start with priority. Ask yourself these questions:
What must the reader understand first?
What is background?
What can be simplified?
What must remain accurate?
What can safely disappear?
That last question is where the hard work begins.
Nature’s guidance explicitly compares visual editing to text editing: art editors do not merely redraw figures to make them look prettier; they redesign them to make them understandable. The same guidance asks brutally practical questions: what is essential, what is missing, what can be removed, what is repeated, and what is decorative?
This applies directly to technical documentation and knowledge systems.
A good information designer should treat diagrams, manuals, help pages, and dashboards with the same editorial discipline:
remove decorative icons that do not aid understanding;
reduce repeated labels and competing arrows;
use consistent shapes and colors;
separate primary actions from supporting context; and
give complex information enough space to be legible.
Nature’s figure guidelines also warn against overcrowded figures and “faux figures”: visuals that are basically tables dressed up with decorative icons. A real figure should show a process, phenomenon, or action; if it only categorizes ideas, a table or list may work better.
That is a useful slap on the wrist for all of us. Not every piece of information deserves to become an infographic. Some information just wants to be a clear table and go home.
A service technician, product manager, buyer, auditor, and first-time user may all need information about the same product. But they do not need the same view: a public-facing explainer needs a strong hierarchy and clear boundaries, while an expert figure can accommodate more complexity. Scientific guidelines on visualizations make the exact same point: visualizations should be shaped by the goal and the intended audience, because the audience determines how much complexity a reader can handle and what type of visual explanation makes sense.
That means one source of truth may need multiple expressions. For example, a detailed technical manual, a quick-start guide, a troubleshooting flow, and a service checklist.
The work isn't about simplifying everything for everyone. The work is to create the right level of complexity for the right user at the right moment.
In technical content, color is often used to align with the corporate identity. But colors can be used more effectively. For example, primary action colors, warning or risk colors, neutral tones for background structure, consistent colors for repeated concepts, and accessible contrast for text and labels. The goal of color usage is never brand decoration, but cognitive control.
In a Nature Methods article, Prof. Bang Wong explains that visual communication depends on authors encoding information and readers decoding it correctly. It points to research on graphical perception showing that people judge certain visual variables more accurately than others. Position on a common scale and length are easier to interpret than area, volume, or color hue.
For information designers, the implication is simple: do not make users work harder than necessary. The best visual is not the one that impresses another designer. It is the one that the intended user can decode quickly and correctly, even under pressure.
Don't forget, technical documentation is often used in imperfect conditions: on a workshop floor, during installation, under time pressure, on mobile devices, by non-native speakers, or by users who are tired, distracted, or stressed.
This means accessible design can determine the operational quality. Clear hierarchy, legible type, enough space, descriptive labels, and consistent patterns all reduce cognitive load. They help more people get the information right the first time.
For technical B2B organizations, this has direct commercial value.
Clear visuals help users understand products faster.
Clear documentation reduces avoidable support questions.
Clear diagrams make sales and onboarding easier.
Clear knowledge structures make content easier to reuse, translate, and govern.
Clear visual systems make AI-assisted documentation safer because source content becomes more structured and less ambiguous.
Scientific illustrators have been working this way for decades, and it is important for information designers and technical communicators to draw on that experience to hone their craft.
Cleveland & McGill: foundational research on graphical perception and the accuracy of different visual decoding tasks.
Nature: guidance on scientific illustration principles, including hierarchy, visual editing, clarity, and accessibility.
Nature: “How to make scientific visualizations that shine”, including audience, design restraint, and accessibility guidance.
Nature Methods: Bang Wong, “Design of data figures”, on graphical perception and the importance of encoding information so readers can decode it correctly.
Nature Reviews: figure design guidance on logical information flow, brevity, labels, color, consistency, and avoiding overcrowded figures.
This article was written and edited by a human being, with the help of AI. Illustration by The Project Twins for Nature Magazine, Vol 634.
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