A mixed data grid approach for systemic city questions

Abstract

As many cities do, Eindhoven collects a significant amount of data, such as information on the city's geography, demography, citizen surveys, and up to real-time traffic or air quality measurements. Much of this information is available to the public and presented online in various interactive visualizations. However, this data is not being fully used to address important city questions, provide citizens with insights about their city, or inform policy decisions. In particular, there is a lack of visualizations and analyses that incorporate multiple variables representing various perspectives on the city, like people, environment, infrastructure, and economy. Although city digital twinning is a promising approach towards bringing these perspectives together, the high data volumes and level of detail make city statistics analysis difficult. To address this gap, we assembled a geospatial grid dataset that maps 34 representative city-data variables onto a grid of 0.001 degrees latitude by 0.001 degrees longitude. This creates a common ground where a lightweight systemic view of the city can emerge. We also show two examples of how using this dataset for multivariate analysis of city data can lead to new and more nuanced insights than by analysing one or two variables at a time.