Square-glyphs: assessing the readability of multidimensional spatial data visualized as square-glyphs

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 …

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Abstract

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 squareglyph 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.

Figures

(a) Square-glyphs of four data categories along a gridded road network of a city (Bleisch & Hollenstein, 2018, p. 5) (b) Classed square-glyph visualization of four data categories across the gridded settlement area of Florida (Strode et al., 2020).

(a) Different color hues distinguish the data categories (b) the area of the squares represents the data values (e.g. normalised index values). In (b) green = largest value, pink = smallest value (c) the glyphs are placed in a grid and represent the values of up to four data categories in relation to each grid cell.

Representations of square-glyphs with two (a), three (b) and four (c) data categories (adapted from: Bleisch & Hollenstein, 2018).

Example square-glyph generation from luminance value diagrams (pink and blue: continuous data, green and orange: discrete data). (a) four data sets along roads are represented as luminance values (b) the four data sets of (a) are gridded and represented as colored square-glyphs.

Example of data and layout conditions as used in the study. The three network variations (rows) with different data value, the two focus area frames A and B, and the representation as 2D and 4D square-glyphs (columns).

T1 results of ranking homologous glyph components in corresponding 2D and 4D conditions.

Results of T1 (average value estimation) mean and standard deviations of absolute errors.

Results of T2 location comparison.

BibTeX

@article{muller_squareglyphs_2023,
 abstract = {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 squareglyph 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.},
 author = {Müller, Gianna Daniela and Hollenstein, Daria and Çöltekin, Arzu and Bleisch, Susanne},
 doi = {10.1080/23729333.2023.2235492},
 journal = {International Journal of Cartography},
 number = {3},
 pages = {449--465},
 title = {Square-glyphs: assessing the readability of multidimensional spatial data visualized as square-glyphs},
 url = {https://www.tandfonline.com/doi/full/10.1080/23729333.2023.2235492},
 volume = {9},
 year = {2023}
}