“What is the safest neighbourhood in the city?”, or “How are rent prices changing in the area where I live?” Most people living in urban environments have probably asked themselves common questions like these at some point in their life as citizens.

A usual way to find answers to these questions would be to look at publicly available urban data. But of course, every citizen would also be able to answer those questions according to their unique, personal experience of urban life.

So what if their own answers to this kind of questions, portraying their perception of urban issues, could be recorded, analyzed and shared to foster a dialogue between people, institutions and the whole urban community?

This thesis project explores how (urban) data visualization can be used to investigate the gap between people’s perception of concrete phenomena and actual data about them.

Research on cognitive bias suggests that visually revealing such a gap can help in generating a deeper and more engaging understanding of information. I decided to investigate how this practice could be used to better inform citizens, raise awareness on urgent urban issues, and possibly challenge  widespread misconceptions within urban communities.

I also wanted to research how recording and analyzing the gap between what citizens think and what data says can help public institutions to better inform their decisions, and to uncover problems and opportunities that might not necessarily be evident by merely analyzing the data at their disposal.

How? By asking questions to citizens! I took inspiration from the methodology in NYT’s groundbreaking series You Draw It to design an interactive survey in which citizens are asked to manipulate visualizations in order to answer a series of questions about urban issues. Only after having shared their personal guess, users are presented with visualizations of data on the same topics (sourced from publicly available datasets), and of answers from other users, within the same visual model. 

After a first research and design phase, in which I investigated the application of this methodology to different visual models and different kinds of questions (image above), I developed a working prototype of the mobile application which I used to conduct user testing with citizens from the Toronto Metropolitan Area. These one-on-one sessions were designed to gather a variety of feedback about the project, and were carried out as a mix of interviews and hands-on testing of the prototype. The contribution from participants was invaluable to improve every aspect of the project, from the wording and scope of questions, to the visualization methods.