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Item Time-oriented Cartographic Treemaps for Visualization of Public Healthcare Data(The Eurographics Association, 2017) Tong, Chao; McNabb, Liam; Laramee, Robert S.; Lyons, Jane; Walters, Angharad; Berridge, Damon; Thayer, Daniel; Tao Ruan Wan and Franck VidalCartographic treemaps offer a way to explore and present hierarchical multi-variate data that combines the space-efficient advantages of treemaps for the display of hierarchical data together with relative geo-spatial location from maps in the form of a modified cartogram. They offer users a space-efficient overview of the complex, multi-variate data coupled with the relative geo-spatial location to enable and facilitate exploration, analysis, and comparison. In this paper, we introduce time as an additional variate, in order to develop time-oriented cartographic treemaps. We design, implement and compare a range of visual layout options highlighting advantages and disadvantage of each. We apply the method to the study of UK-centric electronic health records data as a case study. We use the results to explore the trends of a range of health diagnoses in each UK healthcare region over multiple years exploiting both static and animated visual designs. We provide several examples and user options to evaluate the performance in exploration, analysis, and comparison. We also report the reaction of domain experts from health science.Item When Size Matters: Towards Evaluating Perceivability of Choropleths(The Eurographics Association, 2018) McNabb, Liam; Laramee, Robert S.; Wilson, Max; {Tam, Gary K. L. and Vidal, FranckChoropleth maps are an invaluable visualization type for mapping geo-spatial data. One advantage to a choropleth map over other geospatial visualizations such as cartograms is the familiarity of a non-distorted landmass. However, this causes challenges when an area becomes too small in order to accurately perceive the underlying color. When does size matter in a choropleth map? We conduct an experiment to verify the relationship between choropleth maps, their underlying color map, and a user's perceivability. We do this by testing a user's perception of color relative to an administrative area's size within a choropleth map, as well as user-preference of fixed-locale maps with enforced minimum areas. Based on this initial experiment we can make the first recommendations with respect to a unit area's minimum size in order to be perceivably useful.Item Cartograms with Topological Features(The Eurographics Association, 2018) Tong, Chao; McNabb, Liam; Laramee, Robert S.; {Tam, Gary K. L. and Vidal, FranckCartograms are a popular and useful technique for depicting geo-spatial data. Dorling style and rectangular cartograms are very good for facilitating comparisons between unit areas. Each unit area is represented by the same shape such as a circle or rectangle, and the uniformity in shapes facilitates comparative judgment. However, the layout of these more abstract shapes may also simultaneously reduce the map's legibility and increase error. When we integrate univariate data into a cartogram, the recognizability of cartogram may be reduced. There is a trade-off between information recognition and geo-information accuracy. This is the inspiration behind the work we present. We attempt to increase the map's recognizability and reduce error by introducing topological features into the cartographic map. Our goal is to include topological features such as a river in a Dorling-style or rectangular cartogram to make the visual layout more recognizable, increase map cognition and reduce geospatial error. We believe that compared to the standard Dorling and rectangular style cartogram, adding topological features provides familiar geo-spatial cues and flexibility to enhance the recognizability of a cartogram.Item Spectrum: A C++ Header Library for Colour Map Management(The Eurographics Association, 2018) Roberts, Richard C.; McNabb, Liam; AlHarbi, Naif; Laramee, Robert S.; {Tam, Gary K. L. and Vidal, FranckThe use of colour mapping is fundamental to visualisation research. It acts as an additional layer beyond rendering in the spatial dimensions and provides a link between values in any dataset. When designing and building visualisation research software, the process of creating and managing a colour mapping system can be time-consuming and complex. Existing alternatives offer niche features and require complex dependencies or installations. We present Spectrum; an open source colour map management library that is developer friendly with no installation required, and that offers a wide variety of features for the majority of use cases. We demonstrate the utility of the library through simple snippets of code and a number of examples which illustrate its ease of use and functionality, as well as a video demonstrating the installation and use of the library in under two minutes. It is a very valuable jump-start tool for developers and researchers who need to focus on other tasks.