
The Library
Administrative social science data : the challenge of reproducible research
Tools
Playford, Christopher J., Gayle, Vernon, Connelly, Roxanne and Gray, Alasdair J. G. (2016) Administrative social science data : the challenge of reproducible research. Big Data and Society, 3 (2). doi:10.1177/2053951716684143 ISSN 2053-9517 .
|
PDF
WRAP-administrative-social-data-challenge-Connelly-2016.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution. Download (521Kb) | Preview |
|
![]() |
PDF
WRAP-bds_admin_data_reproducible_research_wrao_20161123.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (315Kb) |
Official URL: https://doi.org/10.1177/2053951716684143
Abstract
Powerful new social science data resources are emerging. One particularly important source is administrative data, which were originally collected for organisational purposes but often contain information that is suitable for social science research. In this paper we outline the concept of reproducible research in relation to micro-level administrative social science data. Our central claim is that a planned and organised workflow is essential for high quality research using micro-level administrative social science data.
We argue that it is essential for researchers to share research code, because code sharing enables the elements of reproducible research. First, it enables results to be duplicated and therefore allows the accuracy and validity of analyses to be evaluated. Second, it facilitates further tests of the robustness of the original piece of research. Drawing on insights from computer science and other disciplines that have been engaged in e-Research we discuss and advocate the use of Git repositories to provide a useable and effective solution to research code sharing and rendering social science research using micro-level administrative data reproducible.
Item Type: | Journal Article | ||||||||
---|---|---|---|---|---|---|---|---|---|
Alternative Title: | |||||||||
Subjects: | H Social Sciences > H Social Sciences (General) Q Science > Q Science (General) |
||||||||
Divisions: | Faculty of Social Sciences > Sociology | ||||||||
Library of Congress Subject Headings (LCSH): | Reproducible research, Social sciences -- Research -- Methodology, Big data | ||||||||
Journal or Publication Title: | Big Data and Society | ||||||||
Publisher: | Sage Publications Ltd. | ||||||||
ISSN: | 2053-9517 | ||||||||
Official Date: | 1 November 2016 | ||||||||
Dates: |
|
||||||||
Volume: | 3 | ||||||||
Number: | 2 | ||||||||
Number of Pages: | 13 | ||||||||
DOI: | 10.1177/2053951716684143 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 23 November 2016 | ||||||||
Date of first compliant Open Access: | 14 June 2017 | ||||||||
Funder: | Economic and Social Research Council (Great Britain) (ESRC) | ||||||||
Grant number: | ES/L007487/1 (ESRC) |
Request changes or add full text files to a record
Repository staff actions (login required)
![]() |
View Item |
Downloads
Downloads per month over past year