This is the fifth and final post in our series ‘Principles of Data Visualization’ #PoDV
In the past few weeks we discussed the goals of data visualization, and how preattentive attributes and analytical patterns enable us to process visual information. However, when designing visualizations we often want to highlight certain aspects of the visual over others. In these cases, Gestalt’s Principles come in handy.
Using the Gestalt Principles to Bring Out Patterns in Visualizations
Gestalt principles describe how our mind organizes individual visual elements into groups, to make sense of the entire visual. When designing a visual, these principles can be used to highlight patterns that are important to us, and downplay other patterns. The image below illustrates the principles of Gestalt which are relevant to visualization (you can see a more extensive list on Wikipedia).
Here’s what we notice from each of the illustrations:
- Proximity: We see three rows of dots instead of four columns of dots because they are closer horizontally than vertically.
- Similarity: We see similar looking objects as part of the same group.
- Enclosure: We group the first four and and last four dots as two rows instead of eight dots.
- Symmetry: We see three pairs of symmetrical brackets rather than six individual brackets.
- Closure: We automatically close the square and circle instead of seeing three disconnected paths.
- Continuity: We see one continuous path instead of three arbitrary ones.
- Connection: We group the connected dots as belonging to the same group.
- Figure & ground: We either notice the two faces, or the vase. Whichever we notice becomes the figure, and the other the ground
These principles allow us to perform many tasks such as reduce the noise from charts, choose the ideal aspect ratio, and show relationships between elements more clearly. Let’s look at a dashboard, and see these principles in action.
An Example from Recorded Future
We’ll consider the following visualization from Recorded Future, a web intelligence company. This visualization compares the mentions of Apple, Google, and Microsoft across the web over the next five years.
This visualization features two chart types – An area chart, which is grayed out in the background, and a bubble chart, which is color-coded in the foreground. Let’s analyze this simple visualization, and identify which elements from this white paper it uses.
Figure & ground
The first thing you notice when looking at this visualization is that the bubbles stand out against the backdrop of the area charts. This is appropriate considering the designer wants the viewer to explore deeper information that’s embedded within the bubbles. The area chart which is grayed out simply shows the trend over time, and isn’t meant to be explored. This is a great example of the Gestalt principle of Figure & Ground.
The bubbles are organized in 3 distinct groups along the horizontal line. We can identify the 3 groups of bubbles easily because of how close they are to each other. Notice that enough space is given between each group to make them distinct. This uses the principle of Proximity.
Further, we notice that the bubbles are of three colors – green, purple, and blue. This Similarity brings out the grouping even more clearly.
To fully understand the next few pointers, do read last week’s post if you haven’t already.
Going up, going down, remaining flat
These patterns are most visible in the area chart. We notice that the overall trend for Apple is upward, while Google’s Microsoft’s stays flat.
There are many peaks along the area chart, but one of them for Microsoft is particularly noticeable in Jan 2015. This peak is narrower than the other peaks.
Tightly, loosely distributed
We notice the loose distribution of bubbles for all three companies around 2018 and 2019, and tight distribution around 2014.
Zoning in on the bubbles for Microsoft, we notice an outlier for Microsoft in mid-2015. The other bubbles fall within a more normal range. Noticing these patterns make us want to further probe into them.
We use the preattentive attribute of position to track the rise and fall of the area chart. Similarly, we notice the abnormal bubble in Microsoft’s chart because of it’s higher position compared to the other bubbles.
Size / Area
The bubbles vary in size. Their size corresponds to the number of web mentions for a particular topic. This makes it easy to spot the important mentions, and explore them in detail.
Hue / Color
As mentioned earlier, the color of the bubbles makes it easy to classify them into three groups. This employs the preattentive attribute of Hue.
Finally, the low intensity of the area chart places it in the background, giving priority to the bubbles.
Being aware of the preattentive attributes, analytical patterns, and Gestalt principles can make a visual come alive to us. Also, when designing visualizations the Gestalt principles allow us to prioritize important patterns, and downplay the noisy ones. Understanding these basic principles of data visualization will help us craft outstanding visualizations, and tell compelling stories, much to the delight our colleagues, and end users.
If you’ve missed any of the previous posts in this series, here they are:
- Everyone Does it, but No One Talks about It – Data Visualization
- To Explain, or Explore: That is the Question in Data Visualization
- Two to Tango: The Role of Eyesight & Memory in Data Visualization
- How We Decode Visual Information
Additionally, if you’d like to read the entire series in one sitting, get our white paper ‘Principles of Data Visualization.’