## 5 Developing a Detailed Design Vocabulary for Visualisation Design Prompt Engineering
### Aesthetics: Visualisation Appearance  
With visualisation appearance, we look at how visualisations can be arranged. [PERSON] [75] describes this process as implantation, which refers to the placement or positioning of graphical elements within a visual display. It involves making deliberate decisions about the arrangement: the location, size, orientation, and alignment of graphical elements within the visualisation. For example, we can delineate circular, linear, and hierarchical arrangements, as well as other patterns, such as the F-pattern, zigzag, and so forth. Design visualisations also can consider wider layout designs, such as trees, dashboards, or multiple views and define the design vocabulary such as the shape, pattern, messiness, and markers such as a point, line, and shape (from [PERSON] [75]), as well as visual quantities such as those used in side-by-side and multiple view layouts or the colourmaps used (e.g., rainbow, sequential, and diverging). We collate words from V7 and VC to create a suite of suitable words, see Table 3.  
\begin{table}
\begin{tabular}{l l r r r r r r r r r r r r r r} \hline \hline \multicolumn{1}{c}{**Subject: Types**} & & & & & & & & & & & & & & & & & & & \\ \hline \multicolumn{1}{c}{**Term**} & \multicolumn{1}{c}{V7 \(f\).} & \multicolumn{1}{c}{**Term**} & \multicolumn{1}{c}{V7 \(f\).} & \multicolumn{1}{c}{**Term**} & \multicolumn{1}{c}{V7 \(f\).} & \multicolumn{1}{c}{**Term**} & \multicolumn{1}{c}{V7 \(f\).} \\ \hline
1. & map (noun) & 6609 & 11. & boxplot & 524 & 21. & Reeb graph & 125 & 31. & bubble chart & 59 \\
2. & scatterplot & 3058 & 12. & line chart & 517 & 22 & area chart & 106 & 32. & stack graph & 59 \\
3. & diagram & 2881 & 13. & scatterplot matrix & 428 & 23. & tag cloud & 104 & 33. & world map & 47 \\
4. & histogram & 2015 & 14. & word cloud & 364 & 24. & star glyph & 98 & 34. & tensor glyph & 45 \\
5. & PCP & 1685 & 15. & network visualisation & 298 & 25. & matrix visualisation & 97 & 35. & mosaic plot & 36 \\
6. & timeline & 1342 & 16. & pie chart & 238 & 26. & radar chart & 97 & 36. & star plot & 31 \\
7. & bar chart & 1320 & 17. & matrix view & 235 & 27. & sunburst & 77 & 37. & reorderable matrix & 31 \\
8. & isosurface & 158 & 18. & choropleth map & 148 & 28. & Gantt chart & 75 & 38. & trellis & 29 \\
9. & heatmap & 1034 & 19. & line graph & 138 & 29. & violin plot & 74 & 39. & donut chart & 19 \\
10. & treemap & 901 & 20. & icicle & 127 & 30. & bar graph & 62 & 40. & contour plot & 17 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Visualisation types ordered by frequency (\(f\).) from V7 corpus (6-million-word corpus of all IEEE visualisation publications from 2012 to 2017). Map, scatterplot, diagram histogram, parallel coordinate plot (PCP) timeline, and bar chart are all extremely popular.  
\begin{table}
\begin{tabular}{l l l l l l l l l l l l l l l l l l l l} \hline \hline \multicolumn{1}{c}{**Aesthetic Visualisation Appearance**}  
We include results where zeros appear, as shown in Table 3, because we consider these terms to be important and influential in generative AI visualisation design. Descriptive phrases like \"gritty texture\", \"fisheye\", or \"inset view\" hold significant value within this context and contribute positively to the design process. Terms around colourmaps are more visualisation-specific (cf. work by [PERSON] et al. (2018)) and are included in this category, such as the following: sequential, diverging, qualitative, sequential single-hue, sequential multi-hue, diverging two-hue, diverging three-hue, qualitative arbitrary, and qualitative miscellaneous colourmaps.