Creating a synthetic spatial microdataset for zone design experiments using 2011 Census and linked administrative data
Creating a synthetic spatial microdataset for zone design experiments using 2011 Census and linked administrative data
New forms of administrative and linked data with high attribute and spatial detail present increased risk 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. We here exploit the synthetic dataset for assessment of alternative automated zone design solutions, with the eventual aim of improving researcher access to maximally useful data while minimising disclosure risk.
Robards, James
4c79fa72-e722-4a2a-a289-1d2bad2c2343
Gale, Chris
5e6578ce-b9cf-4173-aad8-4c5cbd6c3696
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f
April 2017
Robards, James
4c79fa72-e722-4a2a-a289-1d2bad2c2343
Gale, Chris
5e6578ce-b9cf-4173-aad8-4c5cbd6c3696
Martin, David
e5c52473-e9f0-4f09-b64c-fa32194b162f
Robards, James, Gale, Chris and Martin, David
(2017)
Creating a synthetic spatial microdataset for zone design experiments using 2011 Census and linked administrative data.
GIS Research UK Conference, University of Manchester, Manchester, United Kingdom.
19 - 21 Apr 2017.
6 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
New forms of administrative and linked data with high attribute and spatial detail present increased risk 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. We here exploit the synthetic dataset for assessment of alternative automated zone design solutions, with the eventual aim of improving researcher access to maximally useful data while minimising disclosure risk.
Text
GISRUK 2017 Robards Gale Martin - April 2017
- Accepted Manuscript
More information
Submitted date: 13 January 2017
Accepted/In Press date: 3 March 2017
Published date: April 2017
Venue - Dates:
GIS Research UK Conference, University of Manchester, Manchester, United Kingdom, 2017-04-19 - 2017-04-21
Organisations:
Social Statistics & Demography, Population, Health & Wellbeing (PHeW)
Identifiers
Local EPrints ID: 410678
URI: http://eprints.soton.ac.uk/id/eprint/410678
PURE UUID: a7fc9984-30f4-4eba-8d60-b2a3fb7a26ae
Catalogue record
Date deposited: 09 Jun 2017 09:20
Last modified: 16 Mar 2024 02:44
Export record
Contributors
Author:
James Robards
Author:
Chris Gale
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics