Event to launch Royal Society Open Science’s City Analytics Special Collection
Date: 21 February 2017
Time: 14:00 – 16:00
City life generates vast amounts of data: from social media, telecommunications, geolocation, crime, health, transport, to air quality, energy, utilities, weather, CCTV, wi-fi usage, retail footfall, and satellite imaging.
These new data streams are driving a demand for cutting-edge models, algorithms and tools in data science to be tested, customized, deployed, and, where necessary, for new techniques to be developed.
In this event to mark the publication of the Royal Society’s Open Science journal special issue dedicated to city analytics, co-authors of four of the papers will present their work, and discuss the exciting advances in this emerging, interdisciplinary field, and the variety of new, public domain, data sets that are now available to researchers.
The Alan Turing Institute is delighted to work with the Royal Society Open Science to launch this special issue on City Analytics. ‘Smart Cities’ was identified as one of the Institute’s key strategic priorities in its first year of operations, and several Turing Fellows have contributed to the issue.
The papers are freely accessible, and we encourage readers to view the collection of articles.
Elsa Arcaute, UCL, will discuss how the urban hierarchies observed in Britain at different geographical scales, can be understood in terms of a percolation process on the street network. Expected regional divisions and natural barriers can be observed at the larger scales, and surprisingly, these also bear information on socio-economic polarisations.
Luca Aiello, Bell Labs, Cambridge, will discuss his “Chatty Maps” project, where Flickr uploads geotagged for Barcelona and London are compared with a specially compiled urban sound dictionary. Such sound maps on a city scale complement the traditional street plan with a novel and useful layer of information, by adding value to existing social media data.
Mirco Musolesi, UCL, will describe work that builds on the concept of network centrality and on the definition of novel metrics for studying the robustness of spatio-temporal systems. The specific focus is on network vulnerability to disruptions and attacks: his work has been applied to several real-life networks, including examples derived using data from the metro systems of London, Paris and New York, and from flight schedules in the USA.
Peter Grindrod, University of Oxford, will discuss the use of ideas from network science to understand city structures. This work uses geolocated reciprocated Twitter mentions to build up a picture of the pairwise social interactions between inhabitants of ten UK cities. Peter will present a novel technique for understanding and comparing communities within cities, and will consider its possible implications for the use of social media campaigns and behavioural interventions.
Please click here to register your place.
This event has being co-organised by Professor Des J. Higham, guest editor of the Royal Society Open Science City Analytics Collection and Chanuki Illushka Seresinhe, doctoral researcher at The Alan Turing Institute.