In this page, we'll introduce principles of design thinking and how they apply to data viz. There's a lot more to making a great visualization than you might think! Some common features of visualizations you may be familiar with or have used in the past may not have been good choices for clarity or accessibility. At the same time, there are very few "musts" in data viz and many of the choices you make along the way will depend on your perspective and what you believe communicates your message best to your viewers.
Data viz experts and authors Andy Kirk and Stephanie Evergreen both emphasize the importance of the question "what story are you trying to tell?" as a foundational part of designing your viz. This is an important question across many data visualization purposes - you are making a data visualization to help a reader or viewer understand something better than words or a table would allow. You can start by asking yourself who your audience is and what your core message is.
All of these factors may lead to certain choices about type of plot, presentation, interactivity, and tools used to create the visualization. You'll need to find a balance between comphrension, aesthetics, and information.
A great resource to learn more about visualization design is the "Introduction to Data Visualization" course Chapman has access to in Sage Campus.
Additional resources are available through the Leatherby Libraries and on the open web to learn more about a design process thinking approach to data viz.