Solving Urban Problems Through Big Data

Big data’ is a recent term to refer to the collection and use of large data sets. Given their size, these data sets cannot be processed using traditional database management tools, and require new forms of computing applications. Big data is being used in a multiplicity of fields, such as science and research, marketing and security. The social and political implications of the use of big data are multiple and often contradictory. On one hand, big data is hailed as a new type of ‘economic and knowledge asset’, providing opportunities to optimise systems, reduce costs and find solutions to health, education, crime and a multiplicity of other problems. On the other, the use of big data raises fears around privacy, profiling and limited respect for key citizen rights.

Urban authorities and partnerships, as part of their efforts to embrace narratives around ‘smart’, are now starting to develop ‘big data’ initiatives. Examples of this are Amsterdam’s Open Data programme, iCity London and Open Data Brighton and Hove. These projects aim to standardise forms of data collection in the city and make such data available to the ‘public’ for their use. They are also linked to smart city initiatives, both under public and private leadership. However, the implications of the use of big data in the city have not yet been a focus for research. Whilst the implications of big data at the nation state level are starting to be a prominent topic of research (e.g. Amoore 2013), the urban scale is a gap within a critical analysis of big data.

The objective of this apprenticeship is to support a student in their involvement in a project that, in the short term, seeks to understand the pressures and drivers for, and the local initiatives and responses to, big data in the city. The apprenticeship is design to work over the course of 6 weeks during the summer of 2014, although alternative arrangements can be sought. The student will gather background primary material, and, with the support of the academic staff involved in the project, they will develop and implement a methodology for further enquiry through the use of interviews. Whilst some of the interviews can be carried out over the phone, the research might also require visits to different cities for the purpose of conducting interviews.

Tasks for the student

Development of interview schedules and identification of interviewees: Together with the academic staff involved in the project, the student will develop an interview schedule and identify appropriate contacts for one to one interviews. 1 week
Interviews: Interviews with key stakeholders involved in the development of each big data initiative will be carried out. This task will be carried out jointly between the student and the research associate (RA) working in the project, and they are likely to involve travel to at least three of the selected cities. 2 weeks
Big data and cities database: Based on web-based desktop research, construct a database of big data projects in cities around the world. The template to be used for the collection of the information will be discussed in advance between the student and the staff members working in the project. 1 week
Big data case studies: Five cities will be selected for further research, in order to develop a 5 page case study of each according to an agreed proforma and protocol. 2 weeks

Outcomes expected from the student

Interview schedule and list of relevant contacts for each of the selected cities
Undertake interviews (jointly with the RA) and recorded them in audio (mp3) format for three UK cities
Excel spreadsheet with the Big data and cities database
Five case studies, developed via web-based desktop research

Expected learning benefits for the student

Understanding of the key initial steps involved in research formulation and project development
Development of analytical skills
Development of research methodology skills within the social sciences, with an emphasis on the use of web-based data collection and interviews