CartoGAZEweb

This data contains the dataset for the Master’s thesis “Use Cases and Limitations of Webcam Eye Tracking for Cartography Research” by Rahimeh Gharibpour, under supervisor Dr. Merve Keskin, submitted to the University of Salzburg, UNIGIS program. Full Thesis PDF. The thesis explores webcam-based eye tracking as a low-cost, scalable alternative to traditional lab-based systems for studying map cognition in cartographic research. The experiment replicated a subset of tasks from the CartoGAZE (2023) study, available at here, focusing on spatial memory and recognition of road and hydrographic features on 2D static Google road maps. A total of 30 map stimuli were used, divided into three blocks: * Block 1: 10 map stimuli focusing on the memorability of main roads and road junctions. * Block 2: 10 map stimuli focusing on the memorability of major water bodies and rivers. * Block 3: 10 map stimuli combining elements from the first two blocks to assess their collective memorability. The study involved 35 participants in an online experiment, accessible via here, with data from 28 participants analyzed after applying a 70% calibration accuracy threshold. Cognitive load was assessed using both behavioral metrics (response times, success rates) and eye-tracking metrics (average fixation duration, fixations per second, average saccade length). Results suggest that webcam-based eye tracking can replicate general attentional patterns observed in lab-based studies, but with reduced precision due to lower sampling rates (15–20 Hz vs. 250 Hz), environmental variability, and technical factors such as device differences and participant movement. See the GitHub repository for the source code dataset: https://github.com/rahgh/WebcamET_CartoGAZE-data-set