Pandit, Harshvardan J., Fernandez Garcia, Javier David, Debruyne, Christophe, Polleres, Axel. 2019. Towards Cataloguing Potential Derivations of Personal Data. In The Semantic Web: ESWC 2019 Satellite Events. ESWC 2019. Lecture Notes in Computer Science, Hrsg. Hitzler P. et al. 147-151. Cham: Springer.
BibTeX
Abstract
The General Data Protection Regulation (GDPR) has established transparency and accountability in the context of personal data usage and collection. While its obligations clearly apply to data explicitly obtained from data subjects, the situation is less clear for data derived from existing personal data. In this paper, we address this issue with an approach for identifying potential data derivations using a rule-based formalisation of examples documented in the literature using Semantic Web standards. Our approach is useful for identifying risks of potential data derivations from given data and provides a starting point towards an open catalogue to document known derivations for the privacy community, but also for data controllers, in order to raise awareness in which sense their data collections could become problematic.
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| Status of publication | Published |
|---|---|
| Affiliation | WU |
| Type of publication | Contribution to conference proceedings |
| Language | English |
| Title | Towards Cataloguing Potential Derivations of Personal Data |
| Title of whole publication | The Semantic Web: ESWC 2019 Satellite Events. ESWC 2019. Lecture Notes in Computer Science |
| Editor | Hitzler P. et al. |
| Page from | 147 |
| Page to | 151 |
| Location | Cham |
| Publisher | Springer |
| Year | 2019 |
| ISBN | 978-3-030-32326-4 |
| URL | https://link.springer.com/chapter/10.1007%2F978-3-030-32327-1_29 |
| Open Access | N |
Associations
- People
- Fernandez Garcia, Javier David (Former researcher)
- Polleres, Axel (Details)
- External
- Debruyne, Christophe (ADAPT Centre, Trinity College Dublin, Ireland)
- Pandit, Harshvardan J. (ADAPT Centre, Trinity College Dublin, Ireland)
- Organization
- Institute for Data, Process and Knowledge Management (AE Polleres) (Details)
- Institute for Data, Process and Knowledge Management IN (Details)
- Research areas (ÖSTAT Classification 'Statistik Austria')
- 1100 Mathematics, information technology (Details)
- 1109 Information and data processing (Details)
- 1122 Artificial intelligence (Details)
- 5367 Management information systems (Details)
- 5937 Information systems (Details)