Home // HUSO 2016, The Second International Conference on Human and Social Analytics // View article

The Lightweight Smart City and Biases in Repurposed Big Data

Authors:
Christian Voigt
Jonathan Bright

Keywords: Smart City; Big Data; Interpretation Biases

Abstract:
This paper addresses the implications of 'big data' on the smart city paradigm. In addition to grids of sensors to track traffic flows or monitor service delivery, urban governments around the world are starting to experiment with repurposing stores of data collected by third parties: using mobile phone data to track movement or social media to identify failing services. The use of this type of data has considerable potential to both augment the existing smart city vision and to spread it out to small and medium sized cities that are unable to afford investment in sensor grids, creating what we call a “lightweight” version of the smart city. However, it also implies a number of problems which previously smart cities were less prone to. After defining the lightweight smart city this paper reviews these challenges, mainly in the area of interpretation biases, before offering pointers to potential remedies and solutions.

Pages: 61 to 66

Copyright: Copyright (c) IARIA, 2016

Publication date: November 13, 2016

Published in: conference

ISSN: 2519-8351

ISBN: 978-1-61208-519-7

Location: Barcelona, Spain

Dates: from November 13, 2016 to November 17, 2016