GUIDAETA -- A Versatile Interactions Dataset with extensive Context Information and Metadata
Stefan Lengauer, Sarah Annabelle Von G\"otz, Marie-Therese Hoesch, Florian Dieter Steinwidder, Mariia Tytarenko, Michael Bedek, Tobias Schreck

TL;DR
GUIDAETA is a large, versatile dataset of guided user interactions with extensive context and metadata, supporting diverse research in human-computer interaction, cognitive science, and related fields.
Contribution
It introduces a comprehensive, large-scale interaction dataset with rich context and metadata, filling a gap in publicly available data for various research applications.
Findings
Largest dataset of its kind with over 250 users and 716 tasks
Includes detailed context, widget info, and user metadata
Enables diverse research in HCI, cognitive science, and security
Abstract
Interaction data is widely used in multiple domains such as cognitive science, visualization, human computer interaction, and cybersecurity, among others. Applications range from cognitive analyses over user/behavior modeling, adaptation, recommendations, to (user/bot) identification/verification. That is, research on these applications - in particular those relying on learned models - require copious amounts of structured data for both training and evaluation. Different application domains thereby impose different requirements. I.e., for some purposes it is vital that the data is based on a guided interaction process, meaning that monitored subjects pursued a given task, while other purposes require additional context information, such as widget interactions or metadata. Unfortunately, the amount of publicly available datasets is small and their respective applicability for specific…
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