Analyzing eye movement patterns to improve map design

Recently, the use of eye tracking systems has been introduced in the field of cartography and GIS to support the evaluation of the quality of maps towards the user. The quantitative eye movement metrics are related to for example the duration or the number of the fixations which are subsequently (statistically) compared to detect significant differences in map designs or between different user groups. Hence, besides these standard eye movement metrics, other - more spatial - measurements and visual interpretations of the data are more suitable to investigate how users process, store and retrieve information from a (dynamic and/or) interactive map. This information is crucial to get insights in how users construct their cognitive map: e.g. is there a general search pattern on a map and which elements influence this search pattern, how do users orient a map, what is the influence of for example a pan operation. These insights are in turn crucial to be able to construct more effective maps towards the user, since the visualisation of the information on the map can be keyed to the user his cognitive processes. The study focuses on a qualitative and visual approach of the eye movement data resulting from a user study in which 14 participants were tested while working on 20 different dynamic and interactive demo-maps. Since maps are essentially spatial objects, the analysis of these eye movement data is directed towards the locations of the fixations, the visual representation of the scanpaths, clustering and aggregation of the scanpaths. The results from this study show interesting patterns in the search strategies of users on dynamic and interactive maps

Can experts interpret a map's content more efficiently?

This paper describes the statistical comparison of the results from an experiment with a ‘between user’-design. The first group of participants consists out of novices whereas the second group consists out of experts which have experience in map use and have had training in cartography. The same stimuli (twenty screen maps) are presented in a random order to the participants who have to locate a number of labels on the map image. The participants are asked to indicate when they located a name by a button action, resulting in a time measurement. Furthermore, the participant’s eye movements are registered during the whole test. The combined information reveals a same trend in the time intervals needed to locate the subsequent labels in both user groups. However, the experts are significantly faster in locating the names on the map (P<0.010). The recorded eye movements further confirm and explain this finding: the expert’s fixations are significantly shorter (P<0.001) and can consequently have more fixations per second (P<0.001). This means that an expert can interpret the map content more efficiently and can thus search a larger part of the map in the same amount of time

Visual analytics on eye movement data reveal search patterns on dynamic and interactive maps

In this paper the results of a visual analytics approach on eye movement data are described which allows detecting underlying patterns in the scanpaths of the user’s during a visual search on a map. These patterns give insights in the user his cognitive processes or his mental map while working with interactive maps

Investigating the effectiveness of an efficient label placement method using eye movement data

This paper focuses on improving the efficiency and effectiveness of dynamic and interactive maps in relation to the user. A label placement method with an improved algorithmic efficiency is presented. Since this algorithm has an influence on the actual placement of the name labels on the map, it is tested if this efficient algorithms also creates more effective maps: how well is the information processed by the user. We tested 30 participants while they were working on a dynamic and interactive map display. Their task was to locate geographical names on each of the presented maps. Their eye movements were registered together with the time at which a given label was found. The gathered data reveal no difference in the user's response times, neither in the number and the duration of the fixations between both map designs. The results of this study show that the efficiency of label placement algorithms can be improved without disturbing the user's cognitive map. Consequently, we created a more efficient map without affecting its effectiveness towards the user

Listen to the map user : cognition, memory, and expertise

This paper aims to extend current research regarding map users' cognitive processes while working with screen maps. The described experiment investigates how (expert and novice) map users retrieve information from memory that was previously gathered from screen maps. A user study was conducted in which participants had to draw a map from memory. During this task, they were instructed to say out loud every thought that came into mind. Both user groups addressed the same general cognitive structures and processes to solve the task at hand. However, the experts' background knowledge facilitated the retrieval process and allowed them to derive extra information through deductive reasoning. The novices used more descriptive terms instead of naming the objects and could remember less, and less detailed map elements

Study of the attentive behavior of novice and expert map users using eye tracking

The aim of this paper is to gain better understanding of the way map users read and interpret the visual stimuli presented to them and how this can be influenced. In particular, the difference between expert and novice map users is considered. In a user study, the participants studied four screen maps which had been manipulated to introduce deviations. The eye movements of 24 expert and novice participants were tracked, recorded, and analyzed (both visually and statistically) based on a grid of Areas of Interest. These visual analyses are essential for studying the spatial dimension of maps to identify problems in design. In this research, we used visualization of eye movement metrics (fixation count and duration) in a 2D and 3D grid and a statistical comparison of the grid cells. The results show that the users' eye movements clearly reflect the main elements on the map. The users' attentive behavior is influenced by deviating colors, as their attention is drawn to it. This could also influence the users' interpretation process. Both user groups encountered difficulties when trying to interpret and store map objects that were mirrored. Insights into how different types of map users read and interpret map content are essential in this fast-evolving era of digital cartographic products

Analysing the spatial dimension of eye movement data using a visual analytic approach

Conventional analyses on eye movement data only take into account eye movement metrics, such as the number or the duration of fixations and length of the scanpaths, on which statistical analysis is performed for detecting significant differences. However, the spatial dimension in the eye movements is neglected, which is an essential element when investigating the design of maps. The study described in this paper uses a visual analytics software package, the Visual Analytics Toolkit, to analyse the eye movement data. Selection, simplification and aggregation functions are applied to filter out meaningful subsets of the data to be able to recognise structures in the movement data. Visualising and analysing these patterns provides essential insights in the user's search strategies while working on a (n interactive) map