Big Data for Small Places is a quantitative study of the qualities that define our neighborhoods and our collective role in the production of local places over time. We are translating the potentials of big data from the scale of the city to the scale of the urban block, the scale at which we physically experience urban space, to gain a better understanding of the local patterns and social spaces that aggregate to form metropolitan identity. We hope that this study will improve our collective understanding of the urban environments we shape and the stories they generate, that it will allow us to more sensitively test and implement real change in our shared public realm and support the invisible narratives it generates.