That’s the idea behind its new app, CommonSpace, which it announced March 29. The app, which Sidewalk Labs open-sourced by publishing its code on GitHub, is meant to make it easier for people — namely those interested in the subject matter, like city and county officials — to collect, analyze and use data about people in public spaces.
And it’s deliberately shunning the Internet of Things and other newfangled technologies that might be able to do that work automatically. The app is built for humans to use when making their own personal observations, not to deal with data sent in from sensors or cameras.
“While we explored many different ideas (including more ‘high-tech’ or automated solutions, such as cameras and computer vision), we learned that in-person approaches can be preferable because they lead to stronger studies: When community members participate, they not only add important local context but subsequently tend to become more active participants in the planning process (an outcome important to the long-term success of any public space),” wrote Ananta Pandey, a senior software engineer for Sidewalks Labs, in a blog post.
The app is also built around the Public Life Data Protocol, a standard the Gehl Institute developed to allow for standardized data collection around people in public spaces. A parks and recreation employee, for example, might record that they saw a person who looked like a middle-aged woman walking through a park.
Using that data, surveyors can develop an idea of what goes on in a park or other common space: Who does what, where and when. That data can, in turn, help set the foundation for making decisions about what kinds of programming should happen in a certain space or what kind of investments a space might need.
“Of course, we hope this tool helps cities and community organizations everywhere to create vibrant, people-centered public spaces — and stronger urban communities,” Pandey wrote.
