Towards a new digital data infrastructure for urban analysis and modelling

Abstract

Formal models of urban systems have the potential to reveal a lot about the form and functioning of urban settlements, yet much of this potential has still to be realised. In this paper we focus on the extent to which this has reflected the dearth of digital data that are rich, relevant, and disaggregate. Geodemographic classifications have made important and enduring contributions to small-area analysis. Yet, on the one hand, reliance upon census data makes them outdated and irrelevant and, on the other, fragmentation and diversification of social areas in cities has made the 'mosaic metaphor' of small-area analysis untenable. As part of the quest for a new perspective on data modelling, we investigate in this paper the potential of 'lifestyles' data sets for creating richer, more relevant digital models of human activity patterns in cities.