Datafication is a predominant condition of capitalist urban production today, where data increasingly inform individual and collective urban decision-making and mediate urban interactions. This relationship is not ‘new’ in that non-digital forms of information have long mediated urban production (Mattern 2017); nevertheless, contemporary research focuses on how new data-driven technologies articulate novel forms of urban interaction and grapples with the logics of datafication in urban material and political environments. Datafication of the urban is largely enacted through two types of data extraction apparatuses: the networked Internet of Things (IoT) and the digital platform.
Smart city research of the last decade follows the development of the IoT, a network of smart devices--cameras, transponders, actuators, and sensors--that produce large volumes of data (Kitchin 2014). According to smart city logic, data are analyzed to “improve city services and create new services, engage citizens, foster sustainability and resilience, solve urban issues, and stimulate innovation and grow the local economy” (Kitchin et al. 2016, p. 93–4). However, the “actually existing” smart city is a manifestation of political and technological orders, deeply embedded in existing urban systems and politics (Shelton et al. 2015). In these articulations, big data mediate, modulate, and augment existing power structures even as these same powers dictate the capture of big data via control over sensing technologies. While ‘data-driven’ projects seek to de-politicize planning decisions, existing literature describes how these processes can (re)produce inequities in urban built environment (Safransky 2020). Not only does data alter planning outcomes, they reconfigure the urban subject through novel systems of control, enrolling them into the production of urban data through distinctive modes of ‘participation’ (Gabrys 2014; Vanolo 2014). Data integration into urban processes yields substantive material and social impact.
Platform urbanism has been described as a “mode of urbanization that is deeply shaped by the conditions and affordances of platforms” (Barns 2019, p. 3). The convergence of platform products and urban spatial infrastructures and practices pitches the economic relations of the proprietary digital platform into urban life (Barns 2020). Barns describes how datafication in platform urbanism is a kind of “steering tactic,” borrowed from the logics of the platform-as-business, to generate greater usership and “expand the range and remit of the platform ecosystem” (p. 116). The platform utilizes data and “many to many” web architectures to facilitate complex material interactions through digital interfaces. Consider Deliveroo, which coordinates three users (restaurants, delivery professionals, and consumers) via its platform interface. Consumers transact with the restaurants through Deliveroo’s digital interface, initiating as cascade of data-driven logistics, coordinated across several actors, resulting in the food delivery. The platform is not merely a neutral space where different actors and objects meet, but a coordinating regime powered by data; thus, the platform proffers a “reorganization of urban operations” by the “novel technologies of coordination that can reterritorialize those already existing” (Richardson 2020, p. 460). Though platform technologies emerged from an open, participatory Internet culture, these technologies are increasingly developed and enclosed by private firms (Barns 2020; Srnicek 2017). Therefore, private firms deploy data to catalyze the logistical organization of people and materials in extensive and emergent spatial-temporal arrangements towards profitable ends.
Datafication does not simply mediate modes of urbanization, but is (re)produced in the same urban contexts that it informs. In other words, datafication alters urban landscapes by fueling platforms in the orchestration of “flexible spatial arrangements” of objects and people (Richardson 2020), but those same arrangements serve as the sites for the ongoing extraction of datasets. In digital platform ecosystems, data production and consumption are remarkably recursive. The issue here is not so much that the thickness of data production in urban areas somehow skews big data’s representation towards ‘the urban,’ but that data production is conditioned by the very urban built environments that it informs.
The design logics of proprietary digital platforms are meaningful in shaping circular data production. Platform etymology suggests an open and collaborative sensibility (Gillespie 2010); however, the proprietary platform logic is “open, yet closed,” welcoming productive uses, but guarding the data outputs of those uses (Barns 2020, p. 139). Proprietary platforms enact a “recombinatory urban governance” where data capture is decentralized and incentivized while data capture and capitalization is centralized and proprietary (ibid., p. 131). While data are often deployed towards defining urban problems, in platform urbanism, more datafication is often the solution, where platform data outputs are re-integrated into the platform code. Not only does the platform firm make its outputs “necessary” by using them as inputs in the ongoing function of the platform, it profits from the use of these data.
Data production is deeply informed by the urban spaces and social interactions that urban data represent. Consideration of how data are ‘urbanized,’ reflects how data production is dependent on the social and material relations produced within particular forms of land use. What is important here is that the same places influenced by data serve as the site of data production itself, a feedback loop that draws attention to the ways that data production both mediates and is mediated by material contexts. As such, data production is deeply imbricated in the physical and social interactions made possible by particular forms of platform urbanization in the material world.