| Title: | Automated text similarities approach : GDPR and privacy by design principles |
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| Authors: | ID Brumen, Boštjan (Author) |
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| Files: |  FAIA-333-FAIA200831.pdf (771,38 KB)
MD5: 0F2604909A7C49BEB0934810B360EA7C
 https://ebooks.iospress.nl/volumearticle/56446
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.16 - Independent Scientific Component Part or a Chapter in a Monograph |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
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| Abstract: | Respect for privacy is not a modern phenomenon as it has been around for centuries. Recent advances in technologies led to the rise of awareness of the importance of privacy, and to the development of principles for privacy protection to guide the engineering of information systems on one side, and on using the principles to draft legal texts protecting privacy on the other side. In this paper, we analyze how respect for privacy has been implemented in GDPR by automated comparison of the similarity of GDPR's articles and the text of seven principles of Privacy by Design. We have compared the specific text of GDPR's first 50 core privacy-protecting articles and the GDPR's remaining provisions to establish independent supervisory authorities. The first half is observing the privacy by design principles, each of them considerably more than the second half. Our findings show that automated similarity comparison can highlight portions of legal texts where principles were observed. The results can support drafting legal texts to check whether important legal (or other) principles were adequately addressed. |
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| Keywords: | privacy, information system, GDPR, privaci by design, similarity, semantics |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 01.01.2021 |
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| Publisher: | IOS Press |
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| Year of publishing: | 2021 |
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| Number of pages: | Str. 213-226 |
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| PID: | 20.500.12556/DKUM-96590  |
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| UDC: | 004.6 |
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| COBISS.SI-ID: | 46237187 |
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| DOI: | 10.3233/FAIA200831 |
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| Copyright: | © 2021 The authors and IOS Press
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| Publication date in DKUM: | 20.01.2026 |
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| Views: | 190 |
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| Downloads: | 5 |
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| Metadata: |    |
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| Categories: | Misc.
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