Newing, A orcid.org/0000-0002-3222-6640, Anderson, B, Bahaj, A et al. (1 more author) (2016) The role of digital trace data in supporting the collection of population statistics – the case for smart metered electricity consumption data. Population, Space and Place, 22 (8). pp. 849-863. ISSN 1544-8444
Abstract
Debates over the future of the United Kingdom’s traditional decadal census have led to the exploration of supplementary data sources which could support the provision of timely and enhanced statistics on population and housing in small areas. This paper reviews the potential value of a number of commercial datasets before focusing on high temporal resolution household electricity load data collected via smart metering. We suggest that such data could provide indicators of household characteristics that could then be aggregated at the census output area level to generate more frequent official small area statistics. These could directly supplement existing census indicators or even enable development of novel small area indicators. The paper explores this potential through preliminary analysis of a ‘smart meter-like’ dataset and, when set alongside the limited literature to date, the results suggest that aggregated household load profiles may reveal key household and householder characteristics of interest to census users and national statistical organisations. The paper concludes that complete coverage, quasi-real time reporting and household level detail of electricity consumption data in particular could support the delivery of population statistics and area based social indicators and we outline a research programme to address these opportunities.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 The Authors. Population, Space and Place published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited |
Keywords: | Census, energy monitoring, small area statistics, digital trace data, big data |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Jun 2015 12:16 |
Last Modified: | 24 Apr 2017 05:40 |
Published Version: | https://doi.org/10.1002/psp.1972 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1002/psp.1972 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:86667 |