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An interaction model for de-identification of human data held by external custodians

conference contribution
posted on 01.01.2018, 00:00 authored by Andrew Simmons, Anju Kissoon CurumsingAnju Kissoon Curumsing, Rajesh VasaRajesh Vasa
Reuse of pre-existing industry datasets for research purposes requires a multi-stakeholder solution that balances the researcher's analysis objectives with the need to engage the industry data custodian, whilst respecting the privacy rights of human data subjects. Current methods place the burden on the data custodian, whom may not be sufficiently trained to fully appreciate the nuances of data de-identification. Through modelling of functional, quality, and emotional goals, we propose a de-identification in the cloud approach whereby the researcher proposes analyses along with the extraction and de-identification operations, while engaging the industry data custodian with secure control over authorising the proposed analyses. We demonstrate our approach through implementation of a de-identification portal for sports club data.

History

Event

Association for Computing Machinery. Conference (30th : 2018 : Melbourne, Vic.)

Series

Association for Computing Machinery Conference

Pagination

23 - 26

Publisher

Association for Computing Machinery

Location

Melbourne, Vic.

Place of publication

New York, N.Y.

Start date

04/12/2018

End date

07/12/2018

ISBN-13

9781450361880

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2018, owner/author(s)

Editor/Contributor(s)

G Buchanan, D Stevenson

Title of proceedings

OzCHI '18 : Proceedings of the 30th Australian Conference on Computer-Human Interaction 2018