2023, Müller, Gianna, Hollenstein, Daria, Cöltekin, Arzu, Bleisch, Susanne

Glyphs have long been used to approach the challenge of visualising multidimensional data with geospatial reference. Depending on the glyph design, data-dense visualizations of several concurrent data dimensions can be created. The square-glyph is a compound glyph to represent up to four data dimensions, e.g. walkability indices, with reference to a gridded geographic space (Bleisch and Hollenstein 2018 [Exploring multivariate representations of indices along linear geographic features. Proceedings of the 2017 International Cartographic Conference, Washington D.C. (pp. 1–5)]). In this paper, we present a user study to evaluate the readability and interpretability of the square-glyphs. We compare user performance with square-glyph plots containing two and four simultaneously mapped data dimensions under different value compositions. Our results show that the user performance with square-glyphs does not decrease as the number of data dimensions represented increases from two to four. The study results indicate no significant differences in efficiency and effectiveness between the four-dimensional square-glyphs and the two-dimensional square-glyphs. The average values of five adjacent glyphs can be estimated with a mean error of eight percentage points. The results suggest that equal value distances between the displayed dimensions are more accurately perceived in a lower-value composition than in higher-value arrangements.

2021, Hollenstein, Daria, Bleisch, Susanne

Gaining an overview of large spatial data sets presents a challenge common to various domains. 'Overviewing' spatial data involves viewing different areas of focus and context at different scales and requires access to detail from zoomed-out views. Standard pan and zoom interfaces provide limited support with this. Motivated by the application scenario of flood risk monitoring, we extend pan and zoom affordances with a combination of focus+context techniques and multiple maps to support 'overviewing' spatial data with a graph-like information structure. A combination of transient overlays to preview context-on-demand as well as detail-on-demand with the option to decouple additional maps enables fast navigation through the graph-like information space. User-created and -positioned, resizable multiple maps allow for simultaneous exploration of distant regions at flexible scales. The seamless integration of these concepts and the versatility of its components allow for continuously adaptable, user-defined layouts that support various analysis situations. We present a prototype implementation of this interaction model and illustrate its working in application to a hydrometric network, but we believe the model could be transferred to graph-like data in other domains.