I came from scientific background (but turned into data science). From that perspective, I've benefited a lot from the "design" site of data visualization. I got a lot of inspiration by D3.js (even the color choice). Another example is ggplot2 in R - while many plots can be done with the base library, it's much more pleasant to create aesthetically appealing plots.
Sure, it is important to distinguish between goals. But to me "arts" and "vis" are rather two axes, than categories. And I enjoy (and benefit from) the cross pollination between these disciplines. (In this line "the only benefit" is to me far more important than the urge to label things.)
Sure, it is important to distinguish between goals. But to me "arts" and "vis" are rather two axes, than categories. And I enjoy (and benefit from) the cross pollination between these disciplines. (In this line "the only benefit" is to me far more important than the urge to label things.)