Describing Explored Places through OpenStreetMap Data
ISBN
979-8-4007-1394-1/25/04
Type
conference paper
Date Issued
2025
Author(s)
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 𝑘𝑚2). 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.
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 𝑘𝑚2). 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.
Funding(s)
SNSF: Understanding and Improving the Society-level Effects of Navigation Techniques (207430)
Language
English
Keywords
describing places
exploration
field-study
navigation
alternative routing
wayfinding
HSG Classification
contribution to scientific community
Publisher
Association for Computing Machinery
Publisher place
New York, NY, USA
Event Title
CHI ’25: CHI Conference on Human Factors in Computing Systems
Event Location
Yokohama, Japan
Event Date
April 26–May 01, 2025
Subject(s)
Division(s)
Contact Email Address
eve.schade@unisg.ch
File(s)![Thumbnail Image]()
Name
Describing Explored Places through OpenStreetMap Data
Size
3.55 MB
Format
Adobe PDF
Checksum (MD5)
9290750f4919d1a2d14209b27a051d72