Data Governance in Smart Cities: Personal Data as Private Asset, Commons, and/or Public Good?

Data is increasingly framed as an integral part of municipal governance as city administrations seek to deliver public services online and employ insights from data analytics. Real-time data collection in city spaces and the digital transformation of urban infrastructure are turning cities into “smart cities” according to many commentators. Since these digital technologies often rely on commercial algorithms implemented in public facilities, smart city initiatives are often governed by public-private partnerships. Predictably, smart cities pose new governance challenges in which data access, collection, use, and commercialization often come into conflict with the interests of individual and collective privacy, equality, and democratic participation. The aim of this dissertation is to explore the political economy of this new data governance regime as it marks a transition from mass data collection online to mass data collection in city spaces.

This study draws on the concept of assetization, which has emerged in science and technology studies (STS) over the last few years. Assetization theory explores emerging socio-economic arrangements by analyzing the complex processes of co-construction between contemporary capitalism, technology, and society. In the empirical chapters of this thesis, I examine different forms of asset governance as they relate to digital personal data in two smart city initiatives: Sidewalk Toronto/Quayside and the City of Barcelona’s DECODE. These forms of asset governance include private, public, and commons forms of asset governance, which have very different implications for how municipalities manage the collection, use, and commercialization of personal data.

My dissertation includes three key findings. First, data governance in smart city initiatives can be usefully theorized as a form of asset governance in light of the specific political economic logics that underpinned the proposals for Sidewalk Toronto and DECODE. Second, both smart city initiatives aimed to generate monetary value from digital personal data but failed to balance the interests of business with public and collective interests. Third, the policymakers and citizens engaged with these smart city initiatives displayed a variety of non-economic expectations and attitudes toward data, a phenomenon I conceptualize in the dissertation as “affective data governance.”