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Data protection for the common good : developing a framework for a data protection-focused data commons

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2020_07_dfp.pdf (451.9Kb)
Date
15/09/2020
Author
Wong, Janis
Henderson, Tristan
Ball, Kirstie
Keywords
Data protection
Privacy
Personal data
Commons
Interviews
QA75 Electronic computers. Computer science
T-NDAS
NIS
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Abstract
In our data-driven society, personal data are increasingly being collected and processed by sizeable and international companies. While data protection laws and privacy technologies attempt to limit the impact of data breaches and privacy scandals, they rely on individuals having a detailed understanding of the available recourse, resulting in the responsibilisation of data protection. To better protect individual autonomy over personal data, we posit that a data protection-focused data commons framework can be developed to encourage co-creating data protection solutions, rebalancing power between data subjects and controllers. Conducting interviews with commons experts, we aim to better understand how data protection were considered in existing commons and how privacy principles can be better applied. Incorporating trust, multidisciplinary knowledge, and public participation, a data protection-focused data commons can represent a community network of norms and values, enabling the protection of personal data by considering data protection for the common good.
Citation
Wong , J , Henderson , T & Ball , K 2020 , Data protection for the common good : developing a framework for a data protection-focused data commons . in Data for Policy Conference 2020 . Data for Policy . https://doi.org/10.5281/zenodo.3965670
Publication
Data for Policy Conference 2020
DOI
https://doi.org/10.5281/zenodo.3965670
Type
Conference item
Rights
Copyright © 2020 Wong et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.
Collections
  • University of St Andrews Research
URL
https://dataforpolicy.org/data-for-policy-2020/
URI
http://hdl.handle.net/10023/21723

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