My role
In addition to setting up general guidelines that anyone in the organization can follow, I led an effort to establish fundamental data visualization styles for a supplier-facing design system (discussed in another portfolio entry). In order to demonstrate what those guidelines looked like without showing the actual documentation, which is considered proprietary, I have recreated a version that suits the styles found here in my website. The hypothetical situation here is if rnche.com wanted to show a series of charts that all looked and felt the same, while also adhering to ethical standards, keeping the data free from any bias. These are examples that might guide a team creating the charts.
Focused on clarity
I believe the best guidance we could give teams looking to visualize data is on how to do so without misleading or obfuscating. This means leaving out unnecessary embellishments, being careful to follow established norms regarding the zero line and negative values, how to crop in on a portion of the full scale, focusing in on exactly what you want to show and not combining multiple jobs, things like that. You could write a book covering all this, and of course, people have. My job was to distill the information into guidelines that didn’t take weeks to read while still conveying the most crucial information.
Following are examples of the information covered.
Accessibility and color
The color system developed for data visualization might be just as complicated as a design system’s foundational color set. This is primarily because, while color can be a great aid in understanding a chart, not all people see colors the same. In order to deliver a chart that all viewers can see equally, contrasting brightness values are more important, functionally, than hues.
