Contrast: What is it good for?
A lot actually…
Creating effective visualizations of qualitative data requires not only translating that data from swaths of transcriptions and recordings to bullet points, but also figuring out how to convey the insights buried in that data. How can you draw attention to those key insights and tell the compelling narrative that your data is sharing?
You can use hierarchy, color, shape, etc. to do this, but will these elements on their own have the most impact? Not always and that’s why Contrast is one of the fundamental principles of design that qualitative researchers need to consider when working within the visual design framework.
So, what is Contrast in visual design?
Contrast is defined as two or more elements that are visually different from each other in composition. It is used to create a focal point and establish a strong hierarchy with the most important elements having emphasis through strategic use of color, shape, size, alignment, font, etc. Contrast creates better visual design, because it is all about difference and as humans, we are hardwired to pay attention to ‘different’.
Humans evolved physically to rely on visual perception as one of our main senses – it is estimated that nearly 70% of all the data we process is visual. In psychology, visual perception refers to the brain’s ability to interpret and make sense of visual cues received from the eyes. It involves separating the foreground from the background, recognizing objects from different orientations and accurately interpreting spatial cues.
According to a study done at the University of Toronto done in 2021, the ability to quickly scan an environment to determine relative threat was an essential part of survival for humans that still lingers with us today. It was found in this study that smooth, long, horizontal contour scenes were rated as positive/safe, while short angular contour scenes were rated as negative/threatening.
Image from University of Toronto, "Contour features predict valence and threat judgements in scenes" study. DOI: 10.1038/s41598-021-99044-y
This aligns with previous studies that have found that people across all cultures tend to prefer landscape imagery with horizontal lines over other types of subjects. Why? It has been hypothesized that horizontal lines equate to wide-open spaces like a savannah or beach where a threat can't hide or is visible from far away and thus can be avoided.
Ok, so what does this have to do with the design principle of Contrast?
Let’s take a look.
Photo by Sean Oulashin on Unsplash
Photo by Chris Abney on Unsplash
Photo by David Clode on Unsplash
Compared to Jungles and Rocky terrains, Beaches and Savannahs are relatively high contrast environments. Which means that humans can see changes or differences in their environment relatively easily. Higher contrasts draw the human eye.
As researchers working to visualize our qualitative data, we can capitalize on human physiological and psychological preference for looking at high contrast environments. High contrast is also more accessible for most people, so by strategically incorporating Contrast into qualitative data visualizations, researchers can reach a wider audience and draw attention to those key findings and insights.
This is all well and good, but How can I use Contrast in my Qualitative Data Design?
Great Question! You can use Contrast when designing your Qualitative Data in several ways:
1) Size. Yes, it matters (in design)
The word “contrast” is probably the first thing you looked at in the image above. The greater the difference between elements, the greater the contrast. Changing the size of elements works for photos, text, shape, etc. The larger the element, the more focused on that element the viewer will be.
Contrasting elements’ size is an easy way to add difference and help direct the viewer’s eyes.
2) Weight and Text. The heavier it is, the more noticeable it is
Let’s take another look at our contrast statement:
You can see that the boldness of the word “contrast” immediately draws the eye. It is heavy and demands our attention.
Adding visual weight, such as a thicker line, bolding text, changing the size of an object, or using a bolder color, can make elements appear heavier and draw the viewer’s attention to those elements.
You can also pair different font types together to create weight contrast. A busier or heavier font with draw attention faster than a simple, fine font.
3) Shape and Color. Respect the Classics
The most common and classic methods to create contrast in data visualizations is using color and shape.
Color is one of the most intuitive ways to create contrast. If you know a little bit of color theory, you can contrast colors in visually interesting ways. For example, Red is often viewed as a negative, while green is positive. This is a classic method for visualizing comparisons, pros & cons, etc. for qualitative data.
Shape is also a very classic way to create contrast. Think of or take a look at a map. Different shapes usually mean different things. We can (and often do) apply those same principles to qualitative data visualization and design. For example, shape -similar to icons - can be used when mapping a consumer’s journey or distinguishing between categories.
Let’s take a look at this image below:
In grid A, there is minimum contrast. Sure, the squares are different sizes, but that’s about it. It’s not very dynamic or interesting to look at.
In grid B there are too many different colors. Where is the user supposed to look to know what is the most important?
In grid C the center shape takes precedence. Between the shape being different and the contrasting color, the user knows what the most important part of the layout is.
Grid D is also a good choice due to the strong color contrast, but not as strong as C.
Here’s the key:
Contrast doesn’t happen in a vacuum. Just like whitespace, you use it to support other elements of visual design to direct the eye. If whitespace is the workhorse of design, Contrast is arguably the cart.
References:
Lee, Dawn. "Graphic Design for Course Creators." PressBooks. PressBooks, Accessed August 19, 2024. https://pressbooks.pub/graphicdesignforcoursecreators/chapter/design-contrast/.
"Vision and Visual Perception Challenges." Interaction-design.org. Interaction Design Foundation, Accessed August 19, 2024. https://www.interaction-design.org/literature/article/vision-and-visual-perception-challenges.
"What Is Visual Perception?" Interaction-design.Org. Interaction Design Foundation, Accessed August 19, 2024. https://www.interaction-design.org/literature/topics/visual-perception#:~:text=In%20psychology%2C%20visual%20perception%20refers,interpreting%20spatial%20relationships%20between%20objects.
University of Toronto. "Study Provides Insight into how We Sense Threats in Our Environment." Phys.Org. Phys Org, October 21, 2021. https://phys.org/news/2021-10-insight-threats-environment.html.
Damiano, Claudia, Dirk Walther, and William Cunningham. "Contour Features Predict Valence and Threat Judgements in Scenes." Nature.Com. Scientific Reports, September 30, 2021. https://doi.org/10.1038/s41598-021-99044-y.
