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Creating a synthetic spatial microdataset for zone design experiments

Creating a synthetic spatial microdataset for zone design experiments
Creating a synthetic spatial microdataset for zone design experiments
New forms of administrative and linked data containing high levels of attribute and spatial detail present increased risks of information disclosure about individuals, potentially enabling identification. Evaluation of disclosure risk using real data is not feasible, as disclosive record-level data are understandably not accessible for such research. This paper details development of a synthetic microdataset for England and Wales with a realistic distribution of household locations and individual characteristics. Data for the study comes from the England and Wales 2011 Census and are combined from multiple tables and sources to arrive at the final dataset. Our motivation for this work is exploit the synthetic dataset for assessment of alternative automated zone design solutions, with the eventual aim of improving researcher access to the most useful data while minimising disclosure risk. However, the synthetic microdataset, and the methodological approach used to produce it, potentially have wider utility than our automated zone design research. This working paper documents the generation of our synthetic dataset in a way intended to benefit others needing to conduct experiments on a non-disclosive population microdataset.
Spatial microsimulation, Geographical Information System (GIS), Confidentiality and Anonymity
5
National Centre for Research Methods, School of Social Sciences, University of Southampton
Robards, James
4c79fa72-e722-4a2a-a289-1d2bad2c2343
Gale, Christopher G.
5e6578ce-b9cf-4173-aad8-4c5cbd6c3696
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f
Robards, James
4c79fa72-e722-4a2a-a289-1d2bad2c2343
Gale, Christopher G.
5e6578ce-b9cf-4173-aad8-4c5cbd6c3696
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f

Robards, James, Gale, Christopher G. and Martin, David (2017) Creating a synthetic spatial microdataset for zone design experiments (National Centre for Research Methods Working Papers, 5, 17) Southampton, UK. National Centre for Research Methods, School of Social Sciences, University of Southampton 40pp.

Record type: Monograph (Working Paper)

Abstract

New forms of administrative and linked data containing high levels of attribute and spatial detail present increased risks of information disclosure about individuals, potentially enabling identification. Evaluation of disclosure risk using real data is not feasible, as disclosive record-level data are understandably not accessible for such research. This paper details development of a synthetic microdataset for England and Wales with a realistic distribution of household locations and individual characteristics. Data for the study comes from the England and Wales 2011 Census and are combined from multiple tables and sources to arrive at the final dataset. Our motivation for this work is exploit the synthetic dataset for assessment of alternative automated zone design solutions, with the eventual aim of improving researcher access to the most useful data while minimising disclosure risk. However, the synthetic microdataset, and the methodological approach used to produce it, potentially have wider utility than our automated zone design research. This working paper documents the generation of our synthetic dataset in a way intended to benefit others needing to conduct experiments on a non-disclosive population microdataset.

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More information

Published date: 31 July 2017
Keywords: Spatial microsimulation, Geographical Information System (GIS), Confidentiality and Anonymity

Identifiers

Local EPrints ID: 414151
URI: http://eprints.soton.ac.uk/id/eprint/414151
PURE UUID: fd6c2575-8268-42be-813e-f98d13592eb2
ORCID for James Robards: ORCID iD orcid.org/0000-0003-4784-5679
ORCID for David Martin: ORCID iD orcid.org/0000-0003-0397-0769

Catalogue record

Date deposited: 15 Sep 2017 16:30
Last modified: 12 Dec 2021 02:46

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Contributors

Author: James Robards ORCID iD
Author: Christopher G. Gale
Author: David Martin ORCID iD

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