Data visualization is the presentation of data in a pictorial or graphical format. It uses color to display data in many different ways, but the question is how to be reasonable and understandable? According to Robert Simmon, "people aren’t computers. Computer colors are linear and symmetrical, human color perception is non-linear and uneven". Base on this reason, we should choose color carefully when visualize a dataset, consider more about how people can recognize the information from data visualization, and beware of using computer's perception.
As Simmon mentions, "any dataset can be categorized as one of three types—sequential, divergent, and qualitative—each suited to a different color scheme". It explains both dataset and color has the same attribution, and they can translate each other in their own way. Also, the article argues color affiliated with our physical environment and cultural values are linked to certain colors. It supports the view of a good data visualization should use color base on human understanding of the world. Meanwhile, we have to focus on the principles of perception, but not aesthetics in data visualization because it is more about communication rather than aesthetically pleasing.