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Graphia: A platform for the graph-based visualisation and analysis of high dimensional data

Fig 2

Different graph visualisation options.

(A) 3D perspective view, smooth shading (the default), with visualisation of node categorical attribute (MCL cluster). (B) 3D orthographic view, flat shading (no perception of distance—all nodes same size, unless sized by attribute value). (C) 3D perspective view, smooth shading. (D) 2D view, smooth shading. (E) 2D view, flat shading. (F) compressed 2D layout, flat shading, showing node overlap view. Visualisation of (G) Betweeness centrality values, (H) Eccentricity values, (I) PageRank values. G-I are continuous (numerical) attributes, so a colour spectrum and size gradient is used for node display (2D, smooth shading). Betweenness and eccentricity are calculated for both nodes and edges, therefore visual encoding is applied to both.

Fig 2