Information-rich visualisation of dense geographical networks

Network information on geographical entities such as cities is frequently analysed numerically, but seldom visualised in an appealing form. Reasons for this include the absence of powerful software that is capable of handling large-scale networks and the layout of this information without extensive visual clutter. In addition, classic network drawing algorithms (e.g. Fruchterman-Reingold) are not optimised for the representation of geographically fixed nodes, and the standard repertoire of cartography is not suited to mapping complex network information. To tackle these issues, a method-mediating circular layout is presented that (1) roughly preserves the geographical information, (2) allows for the drawing of less cluttered relations between the geographical entities, and (3) offers the possibility of including more information on the underlying node and edge attributes when compared to conventional two-dimensional layouts. The data used to show the capacity of the circular layout were devised by the Globalisation and World City (GaWC) research network of 2010, and represents the office networks of globalised advanced producer services firms.