The aesthetics of science — How to visualize your research

Robert Paauwe  by Robert Paauwe / Reading Time: 5 Minutes /

In 2012, the European Organization for Nuclear Research (CERN) announced a major discovery related to the Higgs boson (an elementary particle). Unfortunately, most of their presentation looked like this:

©CERN 2012

Although the findings were a major discovery in particle physics, there was a particular hype in the media regarding the visual appeal of the presentation. The purpose of presenting your work (poster, presentation, blogs, video, etc.) is to communicate. In the case of CERN, the combination of bad typography, poor choice of colors, and the amount of information presented resulted in the aesthetic appeal of your average high school science project. Even if the audience is used to complex graphs and dense information, overloading them with information still harms your story. In this blog I will present some easy, initial steps how to make your research more appealing and communicative without turning into a full-time graphic designer.

Originally, ‘less is more’ was introduced as a minimalist design principle by architect Ludwig Mies van der Rohe. It refers to the principle that by using less means to achieve a certain effect will lead to a more appealing result. This is applicable not only for design and architecture, but also for conveying information. A great example of this is the data-ink ratio, as proposed by Edward Tufte. The data-ink ratio is the proportion of ink in a graphic devoted to the display of information that is essential. Hypothetically, the data-ink ratio can be calculated by dividing the amount of ink used to display data by the amount of total ink in used in the graphic. This may sound very abstract, but the visualization below based on Tufte’s work should make it clear. Both graphs convey the same amount of information, however the right graph uses less ink to display this information.


The question you should ask yourself when making a presentation is: is what I am doing contributing to the message I am conveying, or am I trying to be fancy? It is better to stick to plain and clear, than (try) to be fancy and miss the point. Adding more things for the sake of adding more things does not help your message, or worse adding things because it was the easiest way to do it (did you copy your tables directly from SPSS?).

Which font you use can make the difference in how your work is is perceived. There is not a universally ‘best’ font. It all depends on where and how you apply it (FontFeed is a great resource for information on typography). Selecting a font should be a conscious decision. Some fonts are great for titles, but terrible for entire texts (e.g., Arial Black, Akzidenz Grotesk). Other fonts are amazing for the entirety of the text, but not very eye-catching as titles (e.g., Times New Roman, Adobe Caslon). Some examples:


But most importantly, if you use a custom font, remember to export your presentation to PDF! The machine you will presenting on will not have that font, and your presentation will look horribly mutilated. By exporting it to PDF, you will ensure your presentation looks the way you intended.

The colors you use have a huge impact on if and how your message is received. We all remember that one presentation that burned our eyes whilst squinting to read the slides. A good rule of thumb for color is to have enough contrast between background and type, and do not use complementary colors (colors that are opposite in the color wheel; red-green, yellow-violet, blue-orange, etc.). Some examples:


A great tool to help you find good color schemes is Adobe Kuler, a tool that helps you generate color schemes based on certain principles. More interestingly, they also maintain a huge database of amazing color schemes for you to use, created by their community. To illustrate this, below are some examples that work well based on popular color schemes on Kuler.


Since Google, it has become amazingly easy to find high resolution images with zero effort. However, at conferences, in papers, and on blogs, I still encounter grainy and stretched low resolution images. When searching for images, simply use:

Google Images > Search Tools > Size > Large or greater.

There are no excuses for not doing this.

Most likely, your university emphasizes that you should use their predesigned templates. Also, it is very easy for you because you do not have to think about your design. However, it makes your presentation uniform and look like all the other presentations. Do not use these templates. All APA articles look the same. All university presentations look alike. Make your own templates.

Of course, these few thoughts are only the tip of the iceberg when it comes to making your research compelling and visually appealing. The best way to check if people understand your data, is by asking non-scientists and people outside of your field of expertise to look at your presentation, poster graphs, or tables. If they get the idea (without you explaining every detail), you are in the right direction. Furthermore, if you are interested in novel ways of visualizing data, take a look at Information is Beautiful. They have a large variation of infographics and several ways of making your data more communicative.

To conclude; do nice aesthetics make bad presentations good? No. Neither do poor graphics completely ruin a presentation (regardless of what designers will tell you). However, by being more considerate of the visuals and style you use, you can empower your story, be more communicative, and ensure your message comes across. Will CERN’s next presentation look appealing? I do not know. Will yours? I hope so.

24 thoughts on “The aesthetics of science — How to visualize your research

  1. Awesome article Robert! Very helpful how those little principles can make such a big difference. I love your remark that font choice should be a conscious decision! Staring at my screen every day writing articles in Times New Roman makes me cringe from the pain of boredom.

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  10. Pingback: Comparing conferences – different crowds, different questions | Socializing Science

  11. Pingback: Visualizing Research and Work – TechKNOW Tools

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