Eye Tracking the User Experience - An Evaluation of Ontology Visualization Techniques

Tracking #: 861-2071

Bo Fu
Natasha Noy
Margaret-Anne Storey

Responsible editor: 
Guest editors linked data visualization

Submission type: 
Full Paper
Various ontology visualization techniques have been developed over the years, offering essential interfaces to users for browsing and interacting with ontologies, in an effort to assist with ontology understanding. Yet few studies have focused on evaluating the usability of existing ontology visualization techniques. This paper presents an eye-tracking user study that evaluates two commonly used ontology visualization techniques, namely, indented list and graph. The eye-tracking experiment and analysis presented in this paper complements the set of existing evaluation protocols for ontology visualization. In addition, the results found from this study contribute to a greater understanding of the strengths and weaknesses of the two visualization techniques, and in particular, how and why one is more effective than the other. Based on approximately 500MB of eye movement data containing around 30 million rows of gaze data generated by a Tobii eye tracker, we found evidence suggesting indented lists are more efficient at supporting information searches and graphs are more efficient at supporting information processing.
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