In this week's reading was more into the field I have been learning about for the past 7 years. However, this topic focused more on the use of color through data and not a general theory. It was a helpful revision and a light read. Agreeing with most of what Simmons explained, I enjoyed the general umbrella of “show[ing] patterns and relationships that are otherwise hidden…”
A constant battle a designer has is transmitting a color from screen to print and then back to screen again. The “lost in translation” from RGB and CMYK was always a weak point. However, the designer now must think of color from the nonlinear human eyes and the linear commuter system. Working with lightness is translatable with both worlds. Specifically, the NASA Ames example was a beautiful selection of colors because of the continuous change of lightness. Going through the different data types; sequential, divergent and qualitative, and the ideal color use was extremely helpful.
I was interested to read about the use of unnatural colors when it comes to data interpretation. The painful rainbow gradient is a trending use of colors, when in reality, it serves a weaker function. A more realistic color choice will allow the concept to express more intuitively. For example, Missing or invalid data should be clearly separated from valid data. Instead of typing NA in a table, or a blank space, adding a strong color will allow to stand out.
Ending the whole blog with helpful tools is the highlight of the reading. It is one thing to read about color and another thing to test color with a specific purpose in mind.