Spatial/Mapping - 5th June 2019

Speakers

Alison Heppenstall, University of Leeds

Title: Bringing the social city to the smart city

Abstract: Technological developments, such as the rise in GPS enabled devices and Web 2.0 technologies have created social transformations in how we connect and share information through the mass uptake of smart phones and social media platforms. This new generation of mobile technologies work as individual sensors capturing data on a wide range of human behaviours that have been previously unavailable. These include data on individual movement, preferences and opinions. Understanding these behaviours is crucial if we are to create a holistic approach to simulating how cities breathe and grow. However, considerable work is required in adapting and developing new technologies from machine learning to extract behaviours which can be embedded into cutting-edge modelling techniques. Creating this bridge between ‘big’ data representing the ‘real’ world, and simulations producing alternative versions of reality is of value to both academics and policymakers looking to develop new solutions to many of the challenges that today’s cities face. To do this we need to understand how factors within the “Social City” (the impact of individual movements and decisions) play out every day in the “Smart City” (data collected from fixed sensors on for example, traffic counts or air pollution).

This presentation will give an overview of work that is being undertaken through an ESRC-Alan Turing Fellowship to address the challenges of bringing the social city to the smart city.

Nik Lomax, University of Leeds

Title: Using novel data to provide local insights

Abstract: There is currently much discussion and hype around the use of big data to provide insight in to a range of phenomena, from consumer behaviour to travel patterns. In this talk, I move away from discussion of big and emerging data to focus on recent work using what I loosely term ‘novel’ data. These are novel in the sense that they are data which are not routinely used in academia but which can provide insight in to local level phenomena and spatial patterns. I provide two substantive examples. The first dataset comes from a commercial provider and reports the characteristics of properties in the sales and rentals market. I use these data to assess local variation in house prices and in rent/price ratios. The second dataset is provided by the UK Government’s e-petitions website. I use these data to estimate the Brexit referendum vote share for Westminster Parliamentary Constituencies and to create a classification of Constituencies based on the types of petitions constituents sign. In both examples I utilise techniques often used on big datasets alongside more conventional techniques. Maps are used as a key tool for interpreting local level variations in both cases. The overall aim of this talk is to highlight that there are a wide range of data available which can provide insight in to spatial patterns which are not routinely used in research. Once we stop worrying about finding big datasets to solve problems, we can focus on applying useful techniques to the range of novel datasets available to us.

Location: Seminar Room 2 (8.11 Garstang, University of Leeds) Time: 3-5pm (coffees from 2:30pm)