The world is becoming increasingly urbanized, complex and connected.

These changes are driving a demand for better information that can be used to make effective decisions about the organisation, flows and connectivity of people, processes and place. While decennial census have in the past been appropriate to monitor these changes, the rate and scale of current population change is making these large surveys increasingly redundant. Through better integration of a range of data sources it is proposed that new horizons can be opened up for analysing the different characteristics of populations and their behaviours. Key to making effective choices across a range of spatial problems is the ability of decision support tools to present areal data from a range of attributes in an understandable format. For example, one may be interested in a local measure which represents school attainment, deprivation and GP referrals for obesity. The dimensions in this example could all be measured independently from national coverage datasets, however, there are a series of challenges related to their amalgamation into a single measure including considerations of scale differences, data normalisation, weighting, method to reduce dimensions and presentation/ visualisation. The core challenge of this research agenda is how a range of attributes across multiple scales can be easily manipulated, interpreted, and displayed as online maps, graphs and descriptions by end users with limited statistical ability. This raises a range of technical computational challenges relating to the integration of large and possibly disparate spatial databases, data normalisation and optimisation for fast transactions related to on-the-fly computation of bespoke classification or measures, and the presentation of these data using GIS Map Servers.