Urban data collection tools can take many forms, from clickers & click boards to AI-enabled sensing devices. Each of these options present trade-offs between efficiency, accessibility, and privacy. Citi Map offers an open source, privacy-preserving digital tool for personal data collection that can be used while moving about a city. The goal of the project is to facilitate collecting real-time or time sensitive urban data that can be shared with other NYC residents.
Users choose their urban objects or behaviors of interest to customize the web app for their purposes. As an example, Mask Map is a Citi Map created to collect mask behavior data in NYC. Depending on what they observe around them, users click the emoji representing “mask”, “half-masked”, or “no mask”. This open dataset can be used to visualize how mask behavior has changed over time and across the NYC – https://maskmap.us/.
After an introduction to the project and Github repo, workshop participants will have the opportunity to adapt Citi Map for their own projects, through an interactive coding session. Potential projects include: tracking different kinds of trash on the street, blooming cherry blossom trees, or public bench locations. Please log your item of interest ahead of the workshop here – https://github.com/dingaaling/citi-map/issues/5.
The event will be lead by Citi Map & Mask Map co-developers Jennifer Ding (Research Application Manager @ The Alan Turing Institute | @jen_gineered) and Marco Berlot (Software Engineer @ IBM | @MarcoBerlot).