A Comparison of Animated Maps with Static Small-Multiple Maps for Visually Identifying Space-Time Clusters

Abstract

Although animated maps are widely promoted as ideal vehicles for learning and scientific discovery, there has been little empirical work that demonstrates their relative effectiveness in relation to static small-multiple alternatives. In this article, we attempt to clarify the issues related to the potential of animation from an explicitly geographic perspective, but one that is also grounded in broader cognitive science and human-computer interaction considerations. We compared the effectiveness of animated with static small-multiple maps, specifically in relation to map readers' ability to identify clusters that move over space and through time. In this study, we focused on several factors that might impact (or help explain) map readers' ability to correctly identify clusters. These factors included animation pace, cluster coherence, and gender. We found that map readers answer more quickly and identify more patterns correctly when using animated maps than when using static small-multiple maps. We also found that pace and cluster coherence interact so that different paces are more effective for identifying certain types of clusters (none vs. subtle vs. strong), and that there are some gender differences in the animated condition. This study is one of a small number of controlled experiments directed to the relative advantages of animated and static small-multiple maps. It provides the basis for further research that is needed to better understand the cognitive load involved in reading animated maps, to better describe and understand gender differences, and to investigate the efficacy of animated maps for other types of map reading tasks.

La visualización del tiempo: de los sistemas de información geográfica a la animación cartográfica

“…Sin embargo, estas técnicas no se popularizaron hasta que software y hardware económicos y baratos estuvieron disponibles en los años noventa; en tanto que casi no se realizaron ejemplos de animaciones cartográficas durante los años setenta y ochenta. Al mismo tiempo aumentó el conocimiento empírico sobre las opciones para conseguir un mejor entendimiento de los fenómenos a partir de visualizaciones dinámicas: Por ejemplo observaron Griffin et al (2006) en una investigación empírica que los participantes en el estudio lograron identificar clusters más rápida y precisamente en representaciones dinámicas que en representaciones estáticas, mientras, Dorling y Openshaw (1992), usando animaciones, encontraron concentraciones (tanto en el espacio como en el tiempo) de casos de leucemia en el norte de Inglaterra, que habían sido desconocidas anteriormente. Por lo tanto se intentará en los siguientes capítulos, en primer lugar, exponer las características particulares de datos temporales, para poder mostrar, en segundo lugar, cómo estas particularidades pueden ser implementadas tanto dentro de los Sistemas de información Geográfica (SIG) como afuera de los mismos.…”

The Role of Map Animation for Geographic Visualization

“…In studies reviewed by Tversky and colleagues, typical 'success' measures are either response time, also known as completion time (a measure of efficiency) or accuracy of response (a measure of quality). In some experiments comparing map animations with static small multiple displays participants answer more quickly, but not more accurately, with animations (Koussoulakou and Kraak, 1992); in other experiments they take longer, and answer fewer questions more accurately (Cutler, 1998), or the time it takes to answer the question does not matter for accuracy at all (Griffin et al, 2006).…”

“…light type, position, distance, angles, colour attributes). The speed with which an animation is viewed is crucial (Griffin et al, 2006) and whether the viewing order of the frames in an animation is predefined (i.e. without any interaction mechanisms) (Hegarty, Kriz and Cate, 2003).…”

Effects of Spatial Distribution on Change Detection in Animated Choropleth Maps

“…We set our duration time as 1, 2, and 3 sec for the experiment. We referred to Griffin et al (2006) s duration time, which was 5, 7, 9, and 11 sec for 6 scenes.…”

“…In response to this necessity, recent research projects on animated maps have conducted various experiments using survey-based experiments and eye tracking experiments, with the adoption of methods and theories from psychology and vision studies (Montello, 2002;Andrienko et al, 2010). These empirical studies have addressed a wide range of research topics, including comparisons of static small-multiple maps and animated maps (Kossoulakou and Kraak, 1992;Slocum et al, 2004;Griffin et al, 2006), comparisons between visual variables effectiveness in animated maps or interactive maps (Cinnamon, 2009;Çöltekin et al, 2009;Garlandini and Fabrikant, 2009;Hegarty et al, 2010), and the impact of interactivity (Mayer, 2001;Mayer and Chandler, 2001) and dynamic variables such as rate of change and abrupt or smooth transitions (Goldsberry and Battersby, 2009;Fish, 2010). Some studies have concluded that dynamic animated maps that are too complex leads to difficulties in conveying information (Bétrancourt and Tversky, 2000;Morrison and Tversky, 2001;Goldsberry and Battersby, 2009), because of human cognitive limits such as split attention, retroactive inhibition, and cognitive overload (Harrower, 2007).…”