—Mapping a set of categorical values to different colors is an elementary technique in data visualization. Users of visualizationsoftware routinely rely on the default colormaps provided by a system, or colormaps suggested by software such as ColorBrewer.In practice, users often have to select a set of colors in a semantically meaningful way (e.g., based on conventions, color metaphors,and logological associations), and consequently would like to ensure their perceptual differentiation is optimized. In this paper, wepresent an algorithmic approach for maximizing the perceptual distances among a set of given colors. We address two technical problemsin optimization, i.e., (i) the phenomena of local maxima that halt the optimization too soon, and (ii) the arbitrary reassignmentof colors that leads to the loss of the original semantic association. We paid particular attention to different types of constraints thatusers may wish to impose during the optimization process. To demonstrate the effectiveness of this work, we tested this technique intwo case studies. To reach out to a wider range of users, we also developed a web application called Colourmap Hospital.
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