Reading Small Scalar Data Fields: Color Scales vs. Detail on Demand vs. FatFonts

We empirically investigate the advantages and disadvantages of color and digit-based methods to represent small scalar fields. We compare two types of color scales (one brightness-based and one that varies in hue, saturation and brightness) with an interactive tooltip that shows the scalar value on demand, and with a symbolic glyph-based approach (FatFonts). Three experiments tested three tasks: reading values, comparing values, and finding extrema. The results provide the first empirical comparisons of color scales with symbol-based techniques. The interactive tooltip enabled higher accuracy and shorter times than the color scales for reading values but showed slow completion times and low accuracy for value comparison and extrema finding tasks. The FatFonts technique showed better speed and accuracy for reading and value comparison, and high accuracy for the extrema finding task at the cost of being the slowest for this task.