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Reviewed by:
  • The Urban Commons: How Data and Technology Can Rebuild Our Communities by Daniel T. O'Brien
  • Sarah Shugars (bio)
A Review of Daniel T. O'Brien, The Urban Commons: How Data and Technology Can Rebuild Our Communities (Cambridge, MA: Harvard University Press, 2018)

In The Urban Commons, Daniel O'Brien leverages the growing quantity of available data in order to reimagine the modern commons. The book serves simultaneously as a practical and theoretical guide to the nascent field of urban informatics. Through case studies reflecting the hands-on practicalities of his ideas, O'Brien situates this growing field within the broader commons literature. Specifically, O'Brien develops the concept of custodianship, and develops a division of labor model in which a range of civic actors play distinct roles in the ongoing maintenance of a commons. Integrating the theoretical and practical is a daunting task, but O'Brien manages to seamlessly these perspectives together throughout his book.

Practically, The Urban Commons can be read as a how-to guide for city administrators, community organizations, or academics looking to leverage the ubiquity of large-scale urban data. O'Brien co-directs the Boston Area Research Initiative (BARI), and in many respects, the book acts as a case study of a successful academic and community partnership. Through a particular focus on the City of Boston's 311 system, which citizens can use to report potholes, streetlamp outages, or to otherwise connect with nonemergency city services, O'Brien outlines the steps and constituents needed to turn such observational data into information that can meaningfully shape policy. [End Page 64]

While this practical dimension is valuable, the book's more significant contributions lie in its theoretical treatments of urban and civic studies. O'Brien argues that the modern availability of big data and computational methods opens new pathways not only for studying the "commons" in the traditional sense of shared resources, but in fundamentally reimagining what the commons are and why they are deserving of scholarly interest. This argument reflects the broad vision of computational social science (Lazer et al., 2009), which urges scholars to go beyond merely applying big data or new methods to traditional scholarly problems, and to instead use new tools and data to re-evaluate what questions we are able to ask.

In other words, "urban informatics" should not be understood as merely the application of data or computational techniques to urban problems. While novel data and sensor technologies form the basis of the field, urban informatics can be more fully understood as a rich civic data infrastructure that enables both scientific pursuit and technocratic innovation around the physical and digital commons. O'Brien develops this argument in four parts over the course of his book. In the first two chapters, he discusses in detail how to think about and appropriately use administrative and other types of big data in an urban context. Second, he demonstrates how these techniques can be used to re-examine questions of the commons. Third, O'Brien delves into the role civic tech can play in partnerships and coproduction. Finally, he concludes with a thoughtful analysis of digital divides and inequity. It is a sweeping and bold vision, which lays important groundwork for reimaging commons research in the modern age.

Chapter 1 introduces the field of urban informatics and lays the groundwork for considering the "introspective city." Just as we might imagine ideal citizens as thoughtful, introspective individuals who continually learn and improve, O'Brien argues that we ought to aim for cities that go beyond being "smart" or "data-driven." Rather, the collection and use of urban data should characterize a continual process of discovery and improvement; of introspection.

In chapter 2, O'Brien grapples with the methodological challenges of such introspection. While there is an increasing amount of raw data available, these data are typically remnants of pre-established socio-technical processes. As Matthew Salganik (2017) would say, borrowing the language of the art world, these data are "readymade." While the custom-made data of surveys or designed experiments allow researchers to pinpoint the exact constructs of interest, repurposing readymade data requires a thoughtful interrogation of the data-generating process. Understanding the...


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pp. 64-69
Launched on MUSE
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