Publisher
ACMCitation
Nusrat, S., Alam, J., & Kobourov, S. (2020). Recognition and Recall of Geographic Data in Cartograms. ACM International Conference Proceeding Series.Rights
© 2020 Association for Computing Machinery.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
We investigate the memorability of two types of cartograms, both in terms of recognition of the visualization and recall of the data. A cartogram, or a value-by-area map, is a representation of a map in which geographic regions are modified to reflect a given statistic, such as population or income. Of the many different types of cartograms, the contiguous and Dorling types are among the most popular and most effective. With this in mind, we evaluate the memorability of these two cartogram types with a human-subjects study, using task-based experimental data and cartogram visualization tasks based on Bertin's map reading levels. In particular, our results indicate that Dorling cartograms are associated with better recall of general patterns and trends. This, together with additional significant differences between the two most popular cartogram types, has implications for the design and use of cartograms, in the context of memorability.Note
Immediate accessVersion
Final accepted manuscriptae974a485f413a2113503eed53cd6c53
10.1145/3399715.3399873