@inproceedings{cc2c46be1f9b4b039765a4aca1ac05bc,
title = "From prescription to description: Mapping the GDPR to a privacy policy corpus annotation scheme",
abstract = "The European Union's General Data Protection Regulation (GDPR) has compelled businesses and other organizations to update their privacy policies to state specific information about their data practices. Simultaneously, researchers in natural language processing (NLP) have developed corpora and annotation schemes for extracting salient information from privacy policies, often independently of specific laws. To connect existing NLP research on privacy policies with the GDPR, we introduce a mapping from GDPR provisions to the OPP-115 annotation scheme, which serves as the basis for a growing number of projects to automatically classify privacy policy text. We show that assumptions made in the annotation scheme about the essential topics for a privacy policy reflect many of the same topics that the GDPR requires in these documents. This suggests that OPP-115 continues to be representative of the anatomy of a legally compliant privacy policy, and that the legal assumptions behind it represent the elements of data processing that ought to be disclosed within a policy for transparency. The correspondences we show between OPP-115 and the GDPR suggest the feasibility of bridging existing computational and legal research on privacy policies, benefiting both areas.",
author = "Ellen Poplavska and Norton, {Thomas B.} and Shomir Wilson and Norman Sadeh",
note = "Publisher Copyright: {\textcopyright} 2020 The Authors, Faculty of Law, Masaryk University and IOS Press.; 33rd International Conference on Legal Knowledge and Information Systems, JURIX 2020 ; Conference date: 09-12-2020 Through 11-12-2020",
year = "2020",
month = dec,
day = "1",
doi = "10.3233/FAIA200874",
language = "English (US)",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "243--246",
editor = "Serena Villata and Jakub Harasta and Petr Kremen",
booktitle = "Legal Knowledge and Information Systems - JURIX 2020",
}