Quantitative data anonymisation: practical guidance for anonymising sensitive social science data

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Ressource 1Download: Kleiner&Heers2024.pdf (362.86 [Ko])
State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_13CC50576B31
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Quantitative data anonymisation: practical guidance for anonymising sensitive social science data
Journal
FORS Guides
Author(s)
Kleiner Brian, Heers Marieke
Publication state
Published
Issued date
18/03/2024
Peer-reviewed
Oui
Volume
23
Language
english
Abstract
In the social sciences, requirements from funders and journals to make data available often present difficulties for researchers because of data protection issues. Anonymisation is a good solution for addressing the challenges of personal and sensitive data. This FORS Guide provides some practical guidance on how to select and apply techniques for anonymising quantitative data within a larger strategic framework for sharing.
Create date
21/03/2024 18:15
Last modification date
22/03/2024 9:26
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