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Applicable Urban Infomatics

Urban Informatics is a MacArthur Foundation funded research project examining the translation of new digital tools and technologies for practical applications in cities.

 

Applicable Urban Infomatics London Image

Urban Informatics is a MacArthur Foundation funded research project examining the translation of new digital tools and technologies for practical applications in cities. We propose to explore the impact of new technologies which we collectively call Urban Informatics on planning and management as these activities relate to cities.

The project also aims to assemble, study and interpret a variety of case studies in large cities where new digital technologies are being developed and implemented. This will involve expertise about science in public policy and organisational change in largely public but some private organisations who have a mission to develop smart technologies.

Urban Informatics is a very wide domain and therefore our scope is restricted to two major areas:

1. ‘Big data’ and its use for new applications in cities: ranging from transportation through urban sensing, new data from social media and networks, energy sensing, the control of routine emergency services, and a range of municipal services from housing to welfare. The focus would be on how the tools that define these domains are being adapted to real practice and the political and organisational dilemmas involved in their application. The experiences of scientists and policy makers would be discussed and interpreted with a focus on prescribing best practice.

2. New tools and models for forecasting based on new technologies: focussing on the ways in which those same technologies based on computation are being embedded into the urban environment. New theories and models of the urban system are being developed to deal with automated applications in cities. There is overlap with the first area in that new models are being based on big data. 

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Professor Michael Batty
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Dr Elsa Arcaute
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Big data Cities Public policy Data models