From Top-Right to User-Right: Perceptual Prioritization of Point-Feature Label Positions

• Main Authors: Bobák, Petr, Čmolík, Ladislav, Čadík, Martin
• Format: Journal Article
• Language: English
• Published: 12.06.2024
• Subjects: Computer Science - Graphics; Computer Science - Human-Computer Interaction
• DOI: 10.48550/arxiv.2407.11996

In cartography, Geographic Information Systems (GIS), and visualization, the position of a label relative to its point feature is crucial for readability and user experience. Alongside other factors, the point-feature label placement (PFLP) is typically governed by the Position Priority Order (PPO), a systematic raking of potential label positions around a point feature according to predetermined priorities. While there is a broad consensus on factors such as avoiding label conflicts and ensuring clear label-to-feature associations, there is no agreement on PPO. Most PFLP techniques rely on traditional PPOs grounded in typographic and cartographic conventions established decades ago, which may no longer meet today's user expectations. In contrast, commercial products like Google Maps and Mapbox use non-traditional PPOs for unreported reasons. Our extensive user study introduces the Perceptual Position Priority Order (PerceptPPO), a user-validated PPO that significantly departs from traditional conventions. A key finding is that labels placed above point features are significantly preferred by users, contrary to the conventional top-right position. We also conducted a supplementary study on the preferred label density, an area scarcely explored in prior research. Finally, we performed a comparative user study assessing the perceived quality of PerceptPPO over existing PPOs, advocating its adoption in cartographic and GIS applications, as well as in other types of visualizations. Our research, supported by nearly 800 participants from 48 countries and over 45,500 pairwise comparisons, offers practical guidance for designers and application developers aiming to optimize user engagement and comprehension, paving the way for more intuitive and accessible visualizations.