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A City in Common: A Framework to Orchestrate Large-scale Citizen Engagement around Urban Issues

Rogers, Y; Balestrini, M; Hassan, C; Creus, J; King, M; Marshall, PE; (2017) A City in Common: A Framework to Orchestrate Large-scale Citizen Engagement around Urban Issues. In: Mark, G and Fussell, S and Lampe, C and Schrafel, MC and Hourcade, JP and Appert, C and Wigdor, D, (eds.) CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. (pp. pp. 2282-2294). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

Citizen sensing is an approach that develops and uses lightweight technologies with local communities to collect, share and act upon data. In doing so it enables them to become more aware of how they can tackle local issues. We report here on the development and uptake of the 'City- Commons Framework for Citizen Sensing', a conceptual model that builds on Participatory Action Research with the aim of playing an integrating role: outlining the processes and mechanisms for ensuring sensing technologies are co-designed by citizens to address their concerns. At the heart of the framework is the idea of a city commons: a pool of community-managed resources. We discuss how the framework was used by communities in Bristol to measure and monitor the problem of damp housing.

Type: Proceedings paper
Title: A City in Common: A Framework to Orchestrate Large-scale Citizen Engagement around Urban Issues
Event: 2017 CHI Conference on Human Factors in Computing Systems (CHI '17)
Location: Denver, USA
Dates: 07 May 2017 - 11 May 2017
ISBN-13: 9781450346559
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3025453.3025915
Publisher version: http://dx.doi.org/10.1145/3025453.3025915
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Smart cities; commons; citizen engagement; publics; citizen sensing; open data; framework; methods
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > UCL Interaction Centre
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1545216
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