Label placement preferences for digital maps - Jaelle Scheuerman; Jason L. Harman; Rebecca R. Goldstein; Dina Acklin; Chris J. Michael (Discover Psychology, 2023)
Abstract Objectives Digital map applications produce maps on the fly, using label placement algorithms to optimize the map layout for various factors. Previous work has made great strides in quickly generating layout placement algorithms that minimize collisions or reduce clutter, but little has been done to explore optimizing layouts while considering the visual preferences of map users. This dataset was collected as part of a study to better understand people’s visual preferences for various label positions in map layouts and to support the development of new label placement algorithms that can generate map layouts that consider those preferences. Data description This dataset of label placement preferences includes two parts. The first part contains 956 binary choice responses that asked participants to choose their favorite of two maps. Labels on each map differed in either their alignment to the point of interest or distance from it. The dataset also includes 1912 ranked choice responses where participants were asked to rank 3 maps that differed in both alignment and distance. The alignment and distance positions considered are the same across both parts of the study.