Map-based Visualizations Increase Recall Accuracy of Data

Bahador Saket, Carlos Scheidegger, Stephen G. Kobourov, and Katy Börner. Eurovis 2015.

We investigate the memorability of data represented in two different visualization designs. In contrast to recent studies that examine which types of visual information make visualizations memorable, we examine the effect of different visualizations on time and accuracy of recall of the displayed data, minutes and days after interaction with the visualizations. In particular, we describe the results of an evaluation comparing the memorability of two different visualizations of the same relational data: node-link diagrams and map-based visualization. We find significant differences in the accuracy of the tasks performed, and these differences persist days after the original exposure to the visualizations. Specifically, participants in the study recalled the data better when exposed to map-based visualizations as opposed to node-link diagrams. We discuss the scope of the study and its limitations, possible implications, and future directions.

Get the paper as a PDF file, and the supplemental material describing the analyses in detail. The full data is available as a gzipped tarball that includes the raw data and the RMarkdown script used to generate the supplemental material document.