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2019 | OriginalPaper | Buchkapitel

GDPR Transparency Requirements and Data Privacy Vocabularies

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Abstract

This tutorial introduced participants to the transparency requirements of the General Data Protection Regulation (GDPR) [35]. Therein, it was explored together with the attendees whether technical specifications can be valuable to support transparency in favour of a data subject whose personal information is being processed. In the context of the discussions, past and present international efforts were examined that focus on data privacy vocabularies and taxonomies as basis work to enable effective enforcement of data handling policies. One example of a current undertaking in this area is the W3C Data Privacy Vocabularies and Controls Community Group (DPVCG) which aims at developing a taxonomy of privacy terms aligned to the GDPR, which encompasses personal data categories, processing purposes, events of disclosures, consent, and processing operations. During the tutorial session, the potential of such efforts was discussed among the participants, allowing for conclusions about the need to re-align and update past research in this area to the General Data Protection Regulation.

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Fußnoten
1
Cf. with regard not only to the GDPR, but also to the review of the ePrivacy Directive, see [12]:pages 3, 7, 10, and 11 as well as in [11], pages 4 f. The results of the public consultation and the Eurobarometer survey outcomes strongly indicate a lack of citizen’s confidence of being able to control and protect own personal data online.
 
2
With an exemplary list of transparency-enhancing technical and organizational measures referenced in the handbook of the Standard Data Protection Model recommended for use in Germany.
 
3
Meis et al. constructed a set of requirements for a transparency focused ontology on the basis of the ISO/IEC 29100:2011standard, OECD principles, and the US fair information practices (FIPs), and which already entails some of these aspects.
 
4
OTT (Over The Top Services) are communication systems over data networks, e.g. skype.
 
5
Electronic Communication Services.
 
6
Microsoft had considerable market power on the Web in 2002.
 
10
RDF uses IRIs to identify objects.
 
11
The privacy dashboard was a Firefox extension that stored all data from the HTTP chatter into a local database and was able to show the tracking to the user. See http://​primelife.​ercim.​eu/​results/​opensource/​76-dashboard.
 
13
See https://​www.​w3.​org/​2013/​share-psi/​ for more information and pointers.
 
15
Scalable and policy-aware linked data architecture for privacy, transparency and compliance (SPECIAL), https://​www.​specialprivacy.​eu.
 
Literatur
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Zurück zum Zitat Kodagoda, N.: Using machine learning to infer reasoning provenance from user interaction log data: based on the data/frame theory of sensemaking. JCEDM Spec. Issue 11(1), 23–47 (2017) Kodagoda, N.: Using machine learning to infer reasoning provenance from user interaction log data: based on the data/frame theory of sensemaking. JCEDM Spec. Issue 11(1), 23–47 (2017)
23.
Zurück zum Zitat Koops, B.-J.: On Decision Transparency, or How to Enhance Data Protection after the Computational Turn, pp. 196–220 (2013) Koops, B.-J.: On Decision Transparency, or How to Enhance Data Protection after the Computational Turn, pp. 196–220 (2013)
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Zurück zum Zitat Pandit, H., O’Sullivan, D., Lewis, D.: Queryable provenance metadata for GDPR compliance. Procedia Comput. Sci. 137, 262–268 (2018)CrossRef Pandit, H., O’Sullivan, D., Lewis, D.: Queryable provenance metadata for GDPR compliance. Procedia Comput. Sci. 137, 262–268 (2018)CrossRef
35.
Zurück zum Zitat European Union: Regulation (EU) 2016/679 of the European parliament and of the council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing directive 95/46/ec (general data protection regulation), May 2016 European Union: Regulation (EU) 2016/679 of the European parliament and of the council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing directive 95/46/ec (general data protection regulation), May 2016
36.
Zurück zum Zitat W3C: A P3P preference exchange language 1.0 (APPEL1.0) (2002) W3C: A P3P preference exchange language 1.0 (APPEL1.0) (2002)
37.
Zurück zum Zitat W3C: The platform for privacy preferences 1.1 (P3P1.1) specification (2006) W3C: The platform for privacy preferences 1.1 (P3P1.1) specification (2006)
Metadaten
Titel
GDPR Transparency Requirements and Data Privacy Vocabularies
verfasst von
Eva Schlehahn
Rigo Wenning
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-16744-8_7