The Visitor and Kangaroo constitute the first large-scale Yarbus replication benchmark dataset for sequential gaze analysis. The Visitor dataset contains eye-tracking recordings from 144 participants who viewed the same painting under seven task conditions, closely replicating the classical Yarbus paradigm in a controlled laboratory setting. Semantically defined Areas of Interest (AOIs) enable systematic analysis of gaze transitions, revisit dynamics, and scanpath sequences across tasks and individuals. The complementary Kangaroo dataset includes logic problem stimuli supporting independent investigation of visual problem-solving strategies. Data are released in open formats with raw, event-level, and AOI-based exports, providing a reproducible resource for methodological and cognitive research on task-driven attention.

The paper presents a detailed analysis of how geological maps are read and interpreted differently by experts in geology and those new to the field. It primarily focuses on three eye-tracking experiments. The first experiment employs a remote eye-tracker to evaluate user reading of scans of geological maps presented on the screen. In the second experiment, the usability of the Czech Geological Survey’s (CGS) online map application was also evaluated using a remote eye-tracker. In the last experiment, paper geological maps were used as stimuli, and eye movement data were recorded using eye-tracking glasses. Participants in the study were categorized into three groups: geologists, geographers, and geoinformatics professionals. Recorded data were visualized using a newly developed open-source online tool called GazePlotter to visualize sequence charts. A variety of experiments helped us to showcase the possibilities of GazePlotter. Findings indicate that geologists tend to concentrate more on the map content than the other groups and generally spend less time completing tasks. The study also uncovers several usability issues within the CGS online map application.

The outbreak of the COVID-19 pandemic caused dashboards to become widely used by the public and decision-makers. Nevertheless, dashboard interfaces have been related to business intelligence since their origins, and the search for improvements in their design is not new. This article’s objective is to conduct a user evaluation of COVID-19 dashboards that contain geospatial information. This is done through a formative study to identify problematic aspects of user/dashboard interaction. This is enhanced by comparing two self-developed dashboards that, according to previous tests, have functionalities with different appearances. User evaluation is performed through mixed research that combines objective (eye-tracking) and subjective (a questionnaire and an interview) methods. The results generate recommendations for better-designed dashboard interfaces that can transfer information appropriately. The vital elements needed to achieve this are interactivity, the option to choose the metrics, and the distribution of the elements in the layout, all playing a role in a more user-friendly interaction between the user and the dashboard.

research-article Share on Scanpath Comparison using ScanGraph for Education and Learning Purposes: Summary of previous educational studies performed with the use of ScanGraph Authors: Stanislav Popelka Department of Geoinformatics, Palacky University Olomouc, Czech Republic Department of Geoinformatics, Palacky University Olomouc, Czech RepublicView Profile , Marketa Beitlova Department of Geoinformatics, Palacky University Olomouc, Czech Republic and Science and Research Centre, Faculty of Health Sciences, Palacky University Olomouc, Czech Republic Department of Geoinformatics, Palacky University Olomouc, Czech Republic and Science and Research Centre, Faculty of Health Sciences, Palacky University Olomouc, Czech RepublicView Profile Authors Info & Claims ETRA '22: 2022 Symposium on Eye Tracking Research and ApplicationsJune 2022 Article No.: 51Pages 1–6https://doi.org/10.1145/3517031.3529243Online:08 June 2022Publication History 1citation45DownloadsMetricsTotal Citations1Total Downloads45Last 12 Months45Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Day and night mode is widely used when working with any digital device, including map navigation. Many users have the day and night mode change set automatically. However, it is not proven if this functionality helps improve the transfer of information between the map and the user when changing the lighting conditions. The short paper aims to evaluate the influence of day and night modes on the map users’ perception. User testing was realised in the eye-tracking laboratory with 43 participants. These participants were categorised by the average number of hours spent driving per week and their use of map navigation. The eye-tracking experiment focuses on the orientation of the participants in the day and night mode of map views when changing the lighting conditions. For that, the Euro Truck Simulator game environment was chosen, where the participants were guided by the map navigation in the bottom right corner of the screen. The lighting conditions in the ET laboratory have been adjusted to match the lighting conditions for both day and night as realistically as possible, and the map navigation mode was switched between day and night mode. The explanatory research suggested that using day mode during nighttime may cause disorientation and dazzle; using night mode during daytime does not cause that problem, but the user perception is slightly slower.

The demo describes new features of ScanGraph, an application intended for a finding of participants with a similar stimulus reading strategy based on the sequences of visited Areas of Interest. The result is visualised using cliques of a simple graph. ScanGraph was initially introduced in 2016. Since the original publication, new features were added. First of them is the implementation of Damerau-Levenshtein algorithm for similarity calculation. A heuristic algorithm for cliques finding used in the original version was replaced by the Bron-Kerbosch algorithm. ScanGraph reads data from open-source application OGAMA, and with the use of conversion tool also data from SMI BeGaze, which allows analysing dynamic stimuli as well. The most prominent enhancement is the possibility of similarity calculation among participants not only for a single stimulus but for multiple files at once.