Describing Explored Places through OpenStreetMap Data
Eve Emily Sophie Schade, Gian-Luca Savino, Jasmin Niess, Johannes Schöning
Abstract
Mobile navigation applications are good at providing efficient navigation instructions. However, they currently lack the capability to facilitate free exploration. Therefore, users are limited to encountering only places close to the shortest paths, neglecting places that could diversify navigation and foster spatial learning. To better understand what characteristics places have that users like to explore we collected a dataset with a mobile application that encourages free exploration using gamification (n = 39, t = 455 days, 106.50 𝑘𝑚 2 ). Using OpenStreetMap data, we found highly frequented freely explored places comprising office, educational, retail, touristic and commercial places. When comparing the characteristics of the freely explored places to those along the shortest path, those categories were different. Based on our findings, we propose that implementing more diverse routing algorithms can enhance navigation diversity, improve spatial learning, and optimise the utilisation of urban spaces for travel.
• Human-centered computing → Human computer interaction (HCI); Field studies; Empirical studies in HCI ; Empirical studies in ubiquitous and mobile computing.
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