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IM919 Urban Data- Theory and Methodology

Urban Data Banner

15/20/30 CATs - (7.5/10/15 ECTS)


Cities have traditionally adapted to the raise of new technologies, like cars or telephones, for instance. Nowadays, digital technologies and data in particular are transforming the material, cultural, social and political spheres of the urban realm.

These transformations require new theories and research methods to understand the spaces, scales, and agents involved in the relationships between data and the urban. This module offers an insight into some of these current theories and methodologies, to question the notion of data itself, to challenge controversial notions like the smart city, and to expand the realms of inquiry of urban data. We will look at the modes and implications of producing, gathering, distributing and visualizing data in urban spaces, including sensors, datacenters, urban utopias or crowdsourcing maps. The module is open to students from all disciplines; no specific prior knowledge is required.

Module Convenors - Dr Nerea Calvillo and Dr Maria Puig de la Bellacasa

Indicative Syllabus

Week 1 (3hr lecture): Introduction to Urban Science-Cities and their relationship with technology and Smart cities?

How the three technological revolutions have restructured cities: industrial revolution, skyscrapers, proliferation of automobiles, and ubiquitous digital society. Genealogy of smart cities: Top-down vs. Grass-Roots (Townsend 2013); Case studies from global cities: London, New York, Amsterdam, Rio De Janeiro, Barcelona; Experiments of Masdar City, UAE and Songdo, South Korea; Critical approaches to smart cities in geography, new media and art.

Week 2 (2hr lecture & 1hr seminar): More-than-human interdependencies

Cities have been designed for humans, where environmental elements are considered resources. Environmental concerns such as biodiversity loss and species extinctions underpin the urgency to improve human relations with non-humans. In this context, ecological thinking emphasises human interdependence with non-humans. We will explore how relational thinking and posthuman ethics respond to this concern and challenge anthropocentrism. If the environment is human, who’s data is air pollution data, for instance? What are the theory and politics surrounding urban ecologies data?

Week 3 (2hr lecture & 1hr seminar): Against the ubiquitous city and data materialities

The material infrastructures of urban data; From sensors to datacenters; Digital infrastructures and their transformation of territory; Impact of digital infrastructures in urban design and urban imaginaries.

Week 4 (2hr lecture & 1hr seminar): Data gathering, urban sensing

Theory, practices and examples of urban sensing; Why and how do we collect urban data?; From satelites to DIY devices; Institutional vs citizen science data.

Week 5 (2hr lecture & 1hr seminar): What is Data?

This lecture will explore a variety of concepts in order to develop a critical and informed view of data. Is our data what we think it is? Would we get the same measurement if we collected that data again? We will discuss uncertainty and the implications of imposing hypotheses on data, and how metadata and analysis can help us to understand these errors.

Week 6 Reading week

Week 7 (2hr lecture & 1hr seminar): The Anatomy of Urban Visualisations

What is a visualisation, what isn’t a visualisation? This lecture will examine the anatomy of visualisations from a variety of perspectives – as an image, code, data and affordances – as viewed from a variety of disciplines; such as design, computing, psychology, architectures, the arts and sciences. We will explore some of the functions, promises and myths of visualisation, in terms of a wide variety of examples, in order to construct a pragmatic overview of urban visualisation.

Week 8-10 (3hr workshop): Ethnography of data. Group work

Analysis, critical and alternative visions of an existing urban cartography whose data is available. Search, analyse and propose changes in the type of data, how it has been gathered, which other data it interacts, the material infrastructures that support the data, the agents involved, and the visualization.

Learning Outcomes

  • By the end of this module, students should be able to:
  • Demonstrate an understanding of how cities are shaped and transformed through technological developments;
  • Explain the basic propositions of smart cities, including their advantages, challenges and feasibility through examples;
  • Reflect on the implications of information and communication technologies and big data for contemporary cities and smart cities;
  • Develop an appreciation of the methodological and epistemological challenges involved in conducting inter-disciplinary research on cities using big and open data;
  • Demonstrate an understanding of the ways in which urban data is transforming traditional social research practices and processes;
  • Practice design research, group work;
  • Practice individual, collective, physical and online ethnography;
  • Extend general and current knowledge in urban data to specific thematic context of urban challenges.


Group presentation (summative; week 10)
2500 word report (summative; week 10)
1500 word essay (summative; at the end of the module)


Group presentation (summative; week 10)
2500 word report (summative; week 10)
3000 word essay (summative; at the end of the module)

Group presentation (summative; week 10)
2500 word report (summative; week 10)
4000 word essay (summative; at the end of the module)

Important Registration Information:

CIM Students

  • Please first discuss your optional module choices with you personal tutor during the personal tutor meetings and get their approval
  • Then complete and submit the optional module choice webform available in the CIM welcome page
  • If there are any queries, please get in touch with Clare (PG Coordinator) via 

External Students

  • Computer Science – Details for signing up for this module will be provided at your induction.
  • All other external students - Please contact the CIM PG Coordinator (Clare) via email ( to request your optional module choice by Week 1.


  • Please be advised that you may be expected to have access to a laptop for some of these courses due to software requirements; the Centre is unable to provide a laptop for external students.
  • Please be advised that some modules may have restricted numbers and places are allocated according to availability.
  • Please note that a request does NOT guarantee a place on the module and is subject to availability.
  • Gaining permission of a member of CIM teaching staff or a member of staff from your home department or filling in the eVision Module Registration (eMR) system with the desired module does NOT guarantee a place on that module.
  • Requests after the specified deadline will not be considered.
  • The CIM PG Coordinator will get back confirming your place in the module by Friday 1st October (For CIM students).
  • For external students - Only after confirmation of a place from CIM PG Coordinator can students’ or their home departments confirm their registration on eVision/MRM. Registrations by students who have not received confirmation of a place from CIM will be rejected via the system.

NOTE – The above-mentioned registration deadline also applies to the CIM optional modules running in Term 2. We will consider registrations again in the first week of Term 2, but only in relation to modules where there is availability.

We are normally unable to allow students (registered or auditing) to join/leave the module after the second week of it commencing.