The Emergence of Data Cities

Alison Romaine - Writer

Cities, with their density of diverse population, infrastructure, ideas, identities, culture and commerce, form magnets of innovation- from the first Industrial city of Manchester to Barcelona graduating as a ‘Smart City’. Often framed as systems or ‘organisms’ where ‘things’ happen, where future trends are generated (the smart city, the sustainable city, the garden city, transport networks, experimental society laboratories) and where power is produced and starved. It is to note that the dynamism and microcosmic nature of these clusters forces me to be selective on a burgeoning topic which involves more than what this post can cover with fear of being simplistic, generalist and reductive. Thus, with the increasing affinity of technology and cities- from the urban design stage, remote sensing, big data to ‘digital twinning’, mapping and surveillance, I thought to join and highlight the discussion on how technology (and its agency) is shaping and perhaps inscripting everyday life in the city - what does it mean for the people on the ground who play out daily activity since we derive ‘city’ from the latinate cīvitās and cīvis; meaning citizen - so who is the city now for?

The model of ‘smart cities’ is becoming an aspiration for how future developments are planned- using networked data to promote efficiency, governance and participation, it seems like an exciting idea but as Shelton and Clark (2016), are conscience to note, it raises more sinister  ‘questions about technocentrism in the reproduction of inequality and socio-spatial fragmentation’. Meanwhile, Rob Kitchin (2014) outlines points that need more attention: the inherent politics of ostensibly ‘neutral’ data, corporatization and lock-in to proprietary technologies, potential of hackable systems we may become dependent of and intrusions on citizen’s privacy. As the rapidity of interactions and change in cities intensify, will urban governance and planning consider equality in community participation in the design, development and deployment of smart technologies or instead privilege efficiency?

In fact, the paradigm of earth observation science, remote sensing and top-down information gathering now reaches the realm of urban design (a domain that is rooted on the streets) as Davina Jackson (2019) discusses how satellite data (there are 650 sats currently operating beyond the atmosphere)- is now part of shaping city planning and control as the environment becomes peppered with squillions of semiconductor devices that pulse electromagnetic waves - meaning that our built environment will become increasingly responsive to electronic evidence revealing real time situations and challenges at various resolutions and scales. Networked sensors range from air quality devices, traffic flow detectors to bee hive monitors (serious business actually - bees in cities), crowd-sourced noise pollution maps and Twitter usage in the city - all this information or ‘big data’ is being encouraged to be used by city leaders to create ‘smarter’ policies. Jackson notes some innovations in sat-imaging e.g. the patterns of street lighting that reliably map different cities at night and infrared imaging of the surface temperatures and energy losses of buildings - which can extend of course into movements of people depicted via algorithms with machine learning developing and becoming predictive of patterns - but how do we humanise this? Data does not always provide the qualitative ‘why’ - why is that zone avoided, why is this community segregated - perhaps a less corporate use of information.

Such removed data collection and governance may be why projects like ‘urban rooms’ where communities are invited to have a say in the (re)design of their cities, are becoming popular - but is this just creating an illusion of participation - creating interior private spaces of thinking when cities and their citizens are in reality just outside and active in environments beyond the room (which often has exclusive connotations) which has viewing platforms overlooking spectacular skyscrapers wrapped up in a simulated ‘real’ experience - where are the networks of data, surveillance etc. On the other hand, it is a place according to Dixon and Farrelly (2019) where people can go to ‘understand, debate and get involved with the past, present and future of the place where they live, work and play’. Models are a very useful tool to help visualise public spaces and visions as well as increasing ‘civic engagement’ but perhaps should not supersede the value of involving the city’s population outside the room.

Moreover, there are suggestions of an agent-based modelling as noted by Malleson & Heppenstall, 2019- a computer which models the behaviour of individual people as they move around and interact inside a virtual world. Contrary to satellites, ABM, examines from the bottom-up - ‘seeking to understand how unexpected large-scale phenomena emerge from individual-level interactions’- each of whom have their own characteristics and rules which have been programmed by researchers based on theories and (a lot of) data on how people behave (from electronic travel cards, twitter messages, density of phones indicating crowds, loyalty consumer behaviour, participatory mapping) - hence a set of interactions drives the next. Combining this with urban datasets from sensors, scientists can detect the phenomena they want to study e.g. traffic jams or social segregation and begin to resolve such issues- although this is still removed from the very people of the city, these virtual city simulations are ‘driven by people - and not just the data they produce’ as citizen’s thoughts and behaviours are considered- avoiding generalisation and homengenisations of individuals. Somewhat worrisome, the example given of a benefit of ABM, is modelling activities of individuals who might commit a crime - seeing how altering an urban environment or road layout may influence how people move around a city. Controlling and surveilling the cities of the future.

Patterns of behaviour and thus the behaviour which is modelled and predicted come from those connected to a sensor e.g. a phone. Therefore, the digital divide and class divide separating those who do and don’t produce digital content may exclude certain groups from being planned into this data driven development of cities - perhaps they are the lucky ones as their activities go undetected although consent for sharing data is becoming higher on the agenda.

Malleson & Heppenstall comment that ‘we are getting closer to being able to simulate the richness of the fabric that weaves together to shape our cities. If we can do this, then we will be able to provide useful input on how best to shape cities in the future - perhaps even down to the last street light, bus and block of flats’. This positive framing is received eerily by other academics and digital geographers as a reliance on simulation - although a useful device in large scale planning - still seems quite an asymmetric relationship in data accumulation and power. Engagement on the ground through participatory GIS may be a more empowering alternative and reach a wider demographic.


Dixon, T. and Farrelly, L. (2019). Urban rooms: where people get to design their city's future. [online] The Conversation. Available at:  [Accessed 8 Feb. 2019].
Heppenstall, A. and Malleson, N. (2019). How big data and The Sims are helping us to build the cities of the future. [online] The Conversation. Available at:  [Accessed 7 Feb. 2019].
Jackson, Davina. (2019) “Digital earth: The paradigm now shaping our worlds data cities”. [online] Available at: [Accessed 7 Feb. 2019]
Kitchin, Rob. 2014. “The Real-Time City? Big Data and Smart Urbanism”, GeoJournal, vol. 79, no. 1, pp. 1–14.
Shelton, Taylor & Clark, Jennifer. (2016). “Technocratic Values and Uneven Development in the “Smart City” [online] Metropolitics. Available at:
[Accessed 07/02/2019]


Popular posts from this blog

The Brutal Bashing of the Brummie Accent

Sustainable solutions to Human-Elephant conflict: a coproductionist approach

The Human Cost of Modern Architectural Megaprojects