The research findings provide evidence that time-oriented data visualizations can contribute to faster information processing, better understanding and improved recall. Thus, they are used in many application domains - medicine, law enforcement, traffic and navigation control to name but a few. Simultaneously, human's time perception varies depending inter alia on culture, language, personal experience and situational factors. Although, the differences caused by the aforementioned aspects were acknowledged and addressed in the Human Computer Interaction (HCI) field for decades their impact on time-oriented data visualizations was largely neglected. To fill this gap, we investigate the influence of time spatializations (organization of time along axes) on the response time and accuracy of inferences based on time-oriented data visualizations. Moreover, we examine users' preferences toward different time arrangements. Our findings show that user-adapted organization of time along axes can speed up the decision-making process and increase the user experience. © 2014 Springer International Publishing.
CITATION STYLE
Nawrot, I., & Doucet, A. (2014). Timeline localization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8510 LNCS, pp. 611–622). Springer Verlag. https://doi.org/10.1007/978-3-319-07233-3_56
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