An Anonymization Tool for Open Data Publication of Legal Documents

Arttu Oksanen; Eero Hyvönen; Minna Tamper; Jouni Tuominen; Henna Ylimaa; Katja Löytynoja; Matti Kokkonen; Aki Hietanen

An Anonymization Tool for Open Data Publication of Legal Documents

Arttu Oksanen, Eero Hyvönen, Minna Tamper, Jouni Tuominen, Henna Ylimaa, Katja Löytynoja, Matti Kokkonen, Aki Hietanen

Research output: Contribution to journal › Conference article › Scientific › peer-review

1 Citation (Scopus)

87 Downloads (Pure)

Abstract

The EU General Data Protection Regulation (GDPR) requires anonymization of documents containing personal data, such as court decisions, for public use. Doing this manually is costly and time-consuming but can be automated by applying Natural Language Processing (NLP) methods. This paper introduces the ANOPPI tool developed for (semi-)automatic anonymization of Finnish texts. The tool can be used both as a web application and programmatically through a REST API. Evaluation shows that ANOPPI performs well with different types of documents, however, further improving the performance of the named entity recognition and disambiguation methods would enhance the usefulness of the software. The tool is being published as open source for public use by the Ministry of Justice in Finland. A use case of ANOPPI is to publish court decisions on the Web in the LawSampo semantic portal for human close reading and as Linked Open Data for data analysis in legal informatics.

Original language	English
Pages (from-to)	12-21
Number of pages	10
Journal	CEUR Workshop Proceedings
Volume	3257
Publication status	Published - 2022
MoE publication type	A4 Conference publication
Event	3rd International Workshop on Artificial Intelligence Technologies for Legal Documents and the 1st International Workshop on Knowledge Graph Summarization - Virtual, Online, Hangzhou, China Duration: 23 Oct 2022 → 24 Oct 2022

Keywords

anonymization
case law
named entity recognition
pseudonymization

Access to Document

An Anonymization Tool for Open Data Publication of Legal DocumentsFinal published version, 1.88 MBLicence: CC BY

Cite this

@article{2bc500da1a94449c8bdaa14383318033,

title = "An Anonymization Tool for Open Data Publication of Legal Documents",

abstract = "The EU General Data Protection Regulation (GDPR) requires anonymization of documents containing personal data, such as court decisions, for public use. Doing this manually is costly and time-consuming but can be automated by applying Natural Language Processing (NLP) methods. This paper introduces the ANOPPI tool developed for (semi-)automatic anonymization of Finnish texts. The tool can be used both as a web application and programmatically through a REST API. Evaluation shows that ANOPPI performs well with different types of documents, however, further improving the performance of the named entity recognition and disambiguation methods would enhance the usefulness of the software. The tool is being published as open source for public use by the Ministry of Justice in Finland. A use case of ANOPPI is to publish court decisions on the Web in the LawSampo semantic portal for human close reading and as Linked Open Data for data analysis in legal informatics.",

keywords = "anonymization, case law, named entity recognition, pseudonymization",

author = "Arttu Oksanen and Eero Hyv{\"o}nen and Minna Tamper and Jouni Tuominen and Henna Ylimaa and Katja L{\"o}ytynoja and Matti Kokkonen and Aki Hietanen",

note = "Publisher Copyright: {\textcopyright} 2022 Copyright for this paper by its authors.; 3rd International Workshop on Artificial Intelligence Technologies for Legal Documents and the 1st International Workshop on Knowledge Graph Summarization, AI4LEGAL-KGSUM ; Conference date: 23-10-2022 Through 24-10-2022",

year = "2022",

language = "English",

volume = "3257",

pages = "12--21",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "RWTH Aachen University",

}

TY - JOUR

T1 - An Anonymization Tool for Open Data Publication of Legal Documents

AU - Oksanen, Arttu

AU - Hyvönen, Eero

AU - Tamper, Minna

AU - Tuominen, Jouni

AU - Ylimaa, Henna

AU - Löytynoja, Katja

AU - Kokkonen, Matti

AU - Hietanen, Aki

PY - 2022

Y1 - 2022

N2 - The EU General Data Protection Regulation (GDPR) requires anonymization of documents containing personal data, such as court decisions, for public use. Doing this manually is costly and time-consuming but can be automated by applying Natural Language Processing (NLP) methods. This paper introduces the ANOPPI tool developed for (semi-)automatic anonymization of Finnish texts. The tool can be used both as a web application and programmatically through a REST API. Evaluation shows that ANOPPI performs well with different types of documents, however, further improving the performance of the named entity recognition and disambiguation methods would enhance the usefulness of the software. The tool is being published as open source for public use by the Ministry of Justice in Finland. A use case of ANOPPI is to publish court decisions on the Web in the LawSampo semantic portal for human close reading and as Linked Open Data for data analysis in legal informatics.

AB - The EU General Data Protection Regulation (GDPR) requires anonymization of documents containing personal data, such as court decisions, for public use. Doing this manually is costly and time-consuming but can be automated by applying Natural Language Processing (NLP) methods. This paper introduces the ANOPPI tool developed for (semi-)automatic anonymization of Finnish texts. The tool can be used both as a web application and programmatically through a REST API. Evaluation shows that ANOPPI performs well with different types of documents, however, further improving the performance of the named entity recognition and disambiguation methods would enhance the usefulness of the software. The tool is being published as open source for public use by the Ministry of Justice in Finland. A use case of ANOPPI is to publish court decisions on the Web in the LawSampo semantic portal for human close reading and as Linked Open Data for data analysis in legal informatics.

KW - anonymization

KW - case law

KW - named entity recognition

KW - pseudonymization

UR - http://www.scopus.com/inward/record.url?scp=85142520225&partnerID=8YFLogxK

UR - https://ceur-ws.org/Vol-3257/

M3 - Conference article

AN - SCOPUS:85142520225

SN - 1613-0073

VL - 3257

SP - 12

EP - 21

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 3rd International Workshop on Artificial Intelligence Technologies for Legal Documents and the 1st International Workshop on Knowledge Graph Summarization

Y2 - 23 October 2022 through 24 October 2022

ER -

An Anonymization Tool for Open Data Publication of Legal Documents

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this