The role of relevance and cognition in attention-guiding geovisualisation

It is a delicate task to design suitable geovisualisations that allow users an efficient visual processing of the depicted geographic information. Today, such a design task is subject to three major challenges: the ever growing amount of geospatial data at various levels of detail, the diversified applications of that data, and the continuously expanding range of display sizes. In this work, the aim was to enhance the visualisation of relevant geographic information by focusing on utility and usability issues of designing geographic information representations. The relevance of information as an element of utility and its cognitively adequate visualisation as an element of usability was considered. To enhance utility, irrelevant data was separated from relevant data by implementing relevance as a filter and embodying relevance values as attributes of the selected objects. To represent these relevant objects and the context information design principles were formulated and a design methodology proposed that tends to facilitate a user’s attentional capacities when processing geovisualisations. In order to design this attention-guiding geovisualisation, use was made of approaches and findings from relevance theory and cognitive psychology with emphasis on neuroscientific principles. A combination of relevance filtering and a cognitively adequate visualisation improved the overall usefulness of geovisualisations and made a substantial contribution to their practical acceptability. This interdisciplinary approach allowed a more precise and valid evaluation of geovisualisation designs

How do decision time and realism affect map-based decision making?

We commonly make decisions based on different kinds of maps, and under varying time constraints. The accuracy of these decisions often can decide even over life and death. In this study, we investigate how varying time constraints and different map types can influence people’s visuo-spatial decision making, specifically for a complex slope detection task involving three spatial dimensions. We find that participants’ response accuracy and response confidence do not decrease linearly, as hypothesized, when given less response time. Assessing collected responses within the signal detection theory framework, we find that different inference error types occur with different map types. Finally, we replicate previous findings suggesting that while people might prefer more realistic looking maps, they do not necessarily perform better with them