About

Project Background

Cities around the world are being rocked by an explosion in urban data. Real-time information linked to urban energy use, travel flow, personal location and movement, consumption, and criminal activity is bursting forth in the Global North and South. Local governments, along with corporate and academic partners, are enthusiastically working to leverage this ‘big data’ in order to improve the sustainability of cities and enhance the quality of urban life. This so-called data- driven urbanism uses high-powered computers and data analytics to generate objective knowledge about urban conditions, patterns and impacts that is used to inform urban policy and planning practices.

The purpose of this project is to explore the contents of the ‘black-box’ of data-driven urbanism: the complex assemblages of people, spaces, discourses and technologies that must be secured to produce urban data in the first place.

Research Question

What types of practices and relations do we find when we open the ‘black-box’ of urban data in Canada and what role do these practices and relations play in data-driven urbanism?

Research Objectives

This project seeks to deepen understandings of data-driven urbanism and develop new insights into the spatiality of urban politics by unpacking the ‘black-box’ of urban data in terms of its constitutive practices and spatial relations. To do so, the project will:

  1. Critically examine urban data initiatives in one Canadian city (Edmonton, Alberta) and compare, contrast and assess their approaches to data production, management and sharing.
  2. Unpack the socio-materialities constituting these various approaches and chronicle the socio-spatial relations they engender (e.g. inclusion, accessibility and transparency).
  3. Examine the relationship between these socio-materialities, socio-spatial relations and the spread and influence of data-driven urbanism more generally.

Research supported by Social Sciences and Humanities Research Council Insight Grant. SSHRC Reference#: 435-2019-1137