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The role of administrative data in the big data revolution in social science research

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Connelly, Roxanne, Playford, Chris J., Gayle, Vernon and Dibben, Chris (2016) The role of administrative data in the big data revolution in social science research. Social Science Research, 59 . pp. 1-12. doi:10.1016/j.ssresearch.2016.04.015 ISSN 0049-089X.

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Official URL: http://dx.doi.org/10.1016/j.ssresearch.2016.04.015

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Abstract

The term big data is currently a buzzword in social science, however its precise meaning is ambiguous. In this paper we focus on administrative data which is a distinctive form of big data. Exciting new opportunities for social science research will be afforded by new administrative data resources, but these are currently under appreciated by the research community. The central aim of this paper is to discuss the challenges associated with administrative data. We emphasise that it is critical for researchers to carefully consider how administrative data has been produced. We conclude that administrative datasets have the potential to contribute to the development of high-quality and impactful social science research, and should not be overlooked in the emerging field of big data.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Social Sciences > Sociology
Library of Congress Subject Headings (LCSH): Big data, Register-based statistics, Database management, Databases -- Access control
Journal or Publication Title: Social Science Research
Publisher: Academic Press
ISSN: 0049-089X
Official Date: September 2016
Dates:
DateEvent
September 2016Published
14 April 2016Available
13 April 2016Accepted
8 July 2015Submitted
Volume: 59
Page Range: pp. 1-12
DOI: 10.1016/j.ssresearch.2016.04.015
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 14 April 2016
Date of first compliant Open Access: 11 August 2016
Funder: Economic and Social Research Council (Great Britain) (ESRC)
Grant number: ES/L007487/1 (ESRC)
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