This three-year project is supported by a Leverhulme Trust Research Grant. The research relates to methods of visual representation of social and spatial inequalities among neighbourhood communities living at the peripheries of major urban centres in the UK and Colombia. The challenge is combine social, spatial and semantic networks into an intelligible visual model, which will be tested through community participation workshops at each site. 

Communities in urban contexts may be represented by combining the spatial, social and semantic networks upon which they are based. The inequalities among communities may also be represented by weighting these networks, which may, for example, signify maters of effort and cost in the urban landscape. This novel method of combination offers a powerful tool for urban modellers, yet also poses a set of theoretical and technical challenges. Not least, the multi-layered complexity of such as network combination must be rendered intelligible for professional and citizen engagement. This paper outlines some of the key opportunities and challenges for this graph theoretical approach to the visualisation of community inequalities, and provides concrete examples of graph data structures based on a recent public engagement in planning initiative.

My new book Shaping Knowledge includes a number of original case studies relating to major urban changes, and outlines modelling methods based on knowledge representations, network formation and economic pay-offs. Organisations depend on knowledge, but must adapt to ever-changing environments, their survival dependent on effective thinking and agile actions. Knowledge is social, spatial and provides the means by which we shape our socio-spatial environments, just as our environments shape the way we come to think and act. Any organization¹s knowledge is its prime asset, based on its resources of data and documentation. However, its true value requires the activations of structure, query, search and decision.