Challenging the robustness of OGD de-identification rules through a hackathon

Details

Ressource 1Request a copy Under indefinite embargo.
UNIL restricted access
State: Public
Version: Author's accepted manuscript
License: CC BY 4.0
Secondary document(s)
Download: 20190911_FinalPaper.pdf (458.10 [Ko])
State: Public
Version: Final published version
License: Not specified
Serval ID
serval:BIB_4C247B062A56
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Challenging the robustness of OGD de-identification rules through a hackathon
Title of the conference
Proceedings of Ongoing Research, Practitioners, Posters, Workshops, and Projects of the International Conference EGOV-CeDEM-ePart 2019
Author(s)
Marmier Auriane, Mettler Tobias
Organization
IFIP WG8.5 on ICT and Public Administration
Address
San Benedetto Del Tronto, Italy
Publication state
Published
Issued date
02/09/2019
Peer-reviewed
Oui
Pages
81-89
Language
english
Abstract
With the emergence of the notion of “open innovation”, public organisations are currently undergoing a transformation process. Particularly driven by the idea of open government, the release of data that has been produced and financed by public funds has increased and with it, the risk associated to the publication of sensitive or personal information about citizens. Although the diffusion of open government data (OGD) might be beneficial for the private sector, the disclosure of such data might engender several risks, which could affect an individual’s privacy. In order to avoid this issue, governments worldwide have started to protect the privacy of individuals by applying de-identification rules. However, de-identification is not risk-free. If the de-identified data does not provide sufficient robustness, re-identification (or re-construction) of personal information is possible. In this paper, we describe a practical approach to examine OGD de-identification rules.
Keywords
De-identification, Open Government Data, Action Design Research, Hackathon
Open Access
Yes
Create date
21/05/2019 8:39
Last modification date
12/09/2019 13:05
Usage data