Izabela Gołębiowska

Bio: Izabela Gołębiowska is an academic researcher from University of Warsaw. The author has contributed to research in topics: Choropleth map & Geovisualization. The author has an hindex of 6, co-authored 23 publications receiving 133 citations.

How Do People View Multi-Component Animated Maps?

Abstract: Quite a few examples in the cartographic and information visualisation literature suggest that multi-component animated maps may be appropriate for examining complex spatio-temporal phenomena. Such space–time visualisations typically consist of multiple dynamic map or data windows, linked by means of interactive tools. Little empirical evidence exists, however, providing support of the potential advantages of such complex visual space–time displays. This research aimed at filling this gap. An empirical study was carried out to obtain insight on how multi-component animated maps are used to explore dynamic spatio-temporal phenomena. We examined which particular components attract users’ attention and in what sequence, and whether display effectiveness can be characterized by users’ viewing behaviours. Based on behavioural data collected with the eye-tracking method, we find that component size, and employed dynamic variables attracted users’ attention most. We are also able to identify visual behaviour patterns that result in performance differences between participants, using multi-component animated map. Finally, we highlight component layout design issues that should be further examined empirically, in order to reduce potential split attention effects.

Legend Layouts for Thematic Maps: A Case Study Integrating Usability Metrics with the Thinking Aloud Method

Abstract: The legend is a critical tool in reading and interpreting a thematic map The goal of the study reported here is to understand how the legend works as a map is read The methodology combined usability performance metrics with the thinking aloud method Subjects were asked to perform two sets of tasks using two thematic maps with different legend layouts While latency and accuracy of answers for the first set of tasks did not differ significantly between users of the different layouts, users clearly preferred legends that were simple or familiar The thinking aloud protocols from the second part of the study revealed different patterns of legend comprehension for each legend design In addition, the study identified four problem-solving strategies that were adopted by the subjects Finally, some principles for designing legends were developed from the results of the study

For your eyes only? Evaluating a coordinated and multiple views tool with a map, a parallel coordinated plot and a table using an eye-tracking approach

Abstract: Geographic visualization tools with coordinated and multiple views CMV typically provide sets of visualization methods. Such configuration gives users the possibility of investigating data in various visual contexts; however, it can be confusing due to the multiplicity of visual components and interactive functions. We addressed this challenge and conducted an empirical study on how a CMV tool, consisting of a map, a parallel coordinate plot PCP, and a table, is used to acquire information. We combined a task-based approach with eye-tracking and usability metrics since these methods provide comprehensive insights into users’ behaviour. Our empirical study revealed that the freedom to choose visualization components is appreciated by users. The individuals worked with all the available visualization methods and they often used more than one visualization method when executing tasks. Different views were used in different ways by various individuals, but in a similarly effective way. Even PCP, which is claimed to be problematic, was found to be a handy way of exploring data when accompanied by interactive functions.

What Went Wrong for Bad Solvers during Thematic Map Analysis? Lessons Learned from an Eye-Tracking Study

Abstract: Thematic map analysis is a complex and challenging task that might result in map user failure for many reasons. In the study reported here, we wanted to search for differences between successful and unsuccessful map users, focusing—unlike many similar studies—on strategies applied by users who give incorrect answers. In the eye-tracking study, followed by a questionnaire survey, we collected data from 39 participants. The eye-tracking data were analyzed both qualitatively and quantitatively to compare participants’ strategies from various perspectives. Unlike the results of some other studies, it turned out that unsuccessful participants show some similarities that are consistent across most analyzed tasks. The main issues that characterize bad solvers relate to improper use of the thematic legend, the inability to focus on relevant map layout elements, as well as on adequate map content. Moreover, they differed in the general problem-solving approach used as they, for example, tended to choose fast, less cautious, strategies. Based on the collected results, we developed tips that could help prevent unsuccessful participants ending with an incorrect answer and therefore be beneficial in map use education.

Rainbow Dash: Intuitiveness, interpretability and memorability of the rainbow color scheme in visualization.

Abstract: After demonstrating that rainbow colors are still commonly used in scientific publications, we comparatively evaluate the rainbow and sequential color schemes on choropleth and isarithmic maps in an empirical user study with 544 participants to examine if a) people intuitively associate order for the colors in these schemes, b) they can successfully conduct perceptual and semantic map reading and recall tasks with quantitative data where order may have implicit or explicit importance. We find that there is little to no agreement in ordering of rainbow colors while sequential colors are indeed intuitively ordered by the participants with a strong dark is more bias. Sequential colors facilitate most quantitative map reading tasks better than the rainbow colors, whereas rainbow colors competitively facilitate extracting specific values from a map, and may support hue recall better than sequential. We thus contribute to dark- vs. light is more bias debate, and demonstrate why and when rainbow colors may impair performance, and add further nuance to our understanding of this highly popular, yet highly criticized color scheme.

Visualization of Eye Tracking Data: A Taxonomy and Survey

Abstract: This survey provides an introduction into eye tracking visualization with an overview of existing techniques. Eye tracking is important for evaluating user behaviour. Analysing eye tracking data is typically done quantitatively, applying statistical methods. However, in recent years, researchers have been increasingly using qualitative and exploratory analysis methods based on visualization techniques. For this state-of-the-art report, we investigated about 110 research papers presenting visualization techniques for eye tracking data. We classified these visualization techniques and identified two main categories: point-based methods and methods based on areas of interest. Additionally, we conducted an expert review asking leading eye tracking experts how they apply visualization techniques in their analysis of eye tracking data. Based on the experts' feedback, we identified challenges that have to be tackled in the future so that visualizations will become even more widely applied in eye tracking research.

Eye tracking for spatial research: Cognition, computation, challenges

Abstract: Spatial information acquisition happens in large part through the visual sense. Studying visual attention and its connection to cognitive processes has been the interest of many research efforts in...