SCC-PG Improving Community and Neighborhood Safety through Open Data Collection


The goal of this project is to study how community-contributed data, like cell phone pictures or videos, can be used to improve aspects of neighborhoods and communities, like public safety and well-being, without unduly infringing on personal rights, like privacy. To date, these types of crowdsourcing efforts have largely been driven by private companies, which raises significant questions about control over surveillance data, trust about how it is used, and personal privacy. Once data is given to a private company, it is often unclear how long the data is stored, how the data is used, and who can access the data.
Our project is different. It’s based on the idea that the communities generating data should also control that data. This model differs significantly from the traditional model driven by private companies, in which voluntarily contributed data, like pictures and videos, is privately maintained. In contrast to this private model, our project studies how data that is contributed voluntarily by individuals in a community and maintained by the community can improve safety and well-being. For example, individuals might choose to capture the license plate identifiers of the automobiles that drive through their streets, but only for certain purposes, such as checking captured images against a hotlist of stolen vehicles (but not, for instance, against vehicle registration lists).

The transparency in this arrangement provides a unique opportunity to build a framework that not only offers real-world benefits, but also adheres to the social and privacy expectations of the communities in which it operates.
We’re studying these topics from both technical and social perspectives and taking privacy, historical, legal, and safety considerations into account. We’ve done surveys, run focus groups, given presentations to neighborhood associations and local government groups, and had numerous conversations with individuals to try to understand the core issues surrounding the use of technology and data in communities.

Our goal is to provide not only guidelines and recommendations that communities can use as a blueprint of best-practices for deploying data-driven technologies, but to also design and deploy a prototype technical and social framework that offers the best of both public and private systems: highly available, fine-grained data combined with automated analyses, with data-usage and retention policies enacted and controlled by individual communities.

Award Number
Lead PI
Daniel Balasubramanian
Sarah Igo