@inproceedings{kamocki-siegert-2022-pseudonymisation,
title = "Pseudonymisation of Speech Data as an Alternative Approach to {GDPR} Compliance",
author = "Kamocki, Pawel and
Siegert, Ingo",
editor = "Siegert, Ingo and
Rigault, Mickael and
Arranz, Victoria",
booktitle = "Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.legal-1.4",
pages = "17--21",
abstract = "The debate on the use of personal data in language resources usually focuses {---} and rightfully so {---} on anonymisation. However, this very same debate usually ends quickly with the conclusion that proper anonymisation would necessarily cause loss of linguistically valuable information. This paper discusses an alternative approach {---} pseudonymisation. While pseudonymisation does not solve all the problems (inasmuch as pseudonymised data are still to be regarded as personal data and therefore their processing should still comply with the GDPR principles), it does provide a significant relief, especially {---} but not only {---} for those who process personal data for research purposes. This paper describes pseudonymisation as a measure to safeguard rights and interests of data subjects under the GDPR (with a special focus on the right to be informed). It also provides a concrete example of pseudonymisation carried out within a research project at the Institute of Information Technology and Communications of the Otto von Guericke University Magdeburg.",
}
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%0 Conference Proceedings
%T Pseudonymisation of Speech Data as an Alternative Approach to GDPR Compliance
%A Kamocki, Pawel
%A Siegert, Ingo
%Y Siegert, Ingo
%Y Rigault, Mickael
%Y Arranz, Victoria
%S Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F kamocki-siegert-2022-pseudonymisation
%X The debate on the use of personal data in language resources usually focuses — and rightfully so — on anonymisation. However, this very same debate usually ends quickly with the conclusion that proper anonymisation would necessarily cause loss of linguistically valuable information. This paper discusses an alternative approach — pseudonymisation. While pseudonymisation does not solve all the problems (inasmuch as pseudonymised data are still to be regarded as personal data and therefore their processing should still comply with the GDPR principles), it does provide a significant relief, especially — but not only — for those who process personal data for research purposes. This paper describes pseudonymisation as a measure to safeguard rights and interests of data subjects under the GDPR (with a special focus on the right to be informed). It also provides a concrete example of pseudonymisation carried out within a research project at the Institute of Information Technology and Communications of the Otto von Guericke University Magdeburg.
%U https://aclanthology.org/2022.legal-1.4
%P 17-21
Markdown (Informal)
[Pseudonymisation of Speech Data as an Alternative Approach to GDPR Compliance](https://aclanthology.org/2022.legal-1.4) (Kamocki & Siegert, LEGAL 2022)
ACL
- Pawel Kamocki and Ingo Siegert. 2022. Pseudonymisation of Speech Data as an Alternative Approach to GDPR Compliance. In Proceedings of the Workshop on Ethical and Legal Issues in Human Language Technologies and Multilingual De-Identification of Sensitive Data In Language Resources within the 13th Language Resources and Evaluation Conference, pages 17–21, Marseille, France. European Language Resources Association.