  Observing the relationship between two or more variables over space and time
is essential in many domains. For instance, looking, for different countries,
at the evolution of both the life expectancy at birth and the fertility rate
will give an overview of their demographics. The choice of visual
representation for such multivariate data is key to enabling analysts to
extract patterns and trends. Prior work has compared geo-temporal visualization
techniques for a single thematic variable that evolves over space and time, or
for two variables at a specific point in time. But how effective visualization
techniques are at communicating correlation between two variables that evolve
over space and time remains to be investigated. We report on a study comparing
three techniques that are representative of different strategies to visualize
geo-temporal multivariate data: either juxtaposing all locations for a given
time step, or juxtaposing all time steps for a given location; and encoding
thematic attributes either using symbols overlaid on top of map features, or
using visual channels of the map features themselves. Participants performed a
series of tasks that required them to identify if two variables were correlated
over time and if there was a pattern in their evolution. Tasks varied in
granularity for both dimensions: time (all time steps, a subrange of steps, one
step only) and space (all locations, locations in a subregion, one location
only). Our results show that a visualization's effectiveness depends strongly
on the task to be carried out. Based on these findings we present a set of
design guidelines about geo-temporal visualization techniques for communicating
correlation.
