Some of these details will make it easier for them to understand the chart in the manner the designer intended. In general, we should have in mind that different details might spark different emotions and expectations in our viewers. While the red chart likely leads you to think 'Wow, Berlin summers are quite hot,' the blue version may push you to think of summers as rainy and rather cold. Without any intention, the two variations of my visualization triggered different emotional reactions. To make it easily accessible for local people, I also created a version in German-and just for the sake of variety and to make them easily distinguishable at a glance, I created this version in a blue color scale. When designing my contribution to the #SWDchallenge of September 2019 on the topic 'Visualizing Uncertainty', I depicted the variation in monthly temperatures in my hometown of Berlin.įor me, it was straightforward to use a warm, reddish color palette and to display the temperature range in degrees of Celsius.

Whether intentional or not, the colors we use in any visualization inevitably spark emotions in our viewers.

In our effort to create meaningful visualizations from our data, we transmit our message not only through the particular chart type and title we choose, but also through our choice of colors for the data itself and for any additional design elements. Mark RothkoĪs data visualization practitioners we are both engineers and designers. I am interested in expressing the big emotions.

If you are only moved by color relationships, you are missing the point.

Emotional color wheel