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在欧洲法律框架背景下重新审视与匿名化相关的概念及“识别”一词

Reconsidering Anonymization-Related Concepts and the Term "Identification" Against the Backdrop of the European Legal Framework.

作者信息

Sariyar Murat, Schlünder Irene

机构信息

1 Institute of Pathology, Charité-University Medicine Berlin , Berlin, Germany .

2 TMF (Technologie- und Methodenplattform e.V.) , Berlin, Germany .

出版信息

Biopreserv Biobank. 2016 Oct;14(5):367-374. doi: 10.1089/bio.2015.0100. Epub 2016 Apr 22.

Abstract

Sharing data in biomedical contexts has become increasingly relevant, but privacy concerns set constraints for free sharing of individual-level data. Data protection law protects only data relating to an identifiable individual, whereas "anonymous" data are free to be used by everybody. Usage of many terms related to anonymization is often not consistent among different domains such as statistics and law. The crucial term "identification" seems especially hard to define, since its definition presupposes the existence of identifying characteristics, leading to some circularity. In this article, we present a discussion of important terms based on a legal perspective that it is outlined before we present issues related to the usage of terms such as unique "identifiers," "quasi-identifiers," and "sensitive attributes." Based on these terms, we have tried to circumvent a circular definition for the term "identification" by making two decisions: first, deciding which (natural) identifier should stand for the individual; second, deciding how to recognize the individual. In addition, we provide an overview of anonymization techniques/methods for preventing re-identification. The discussion of basic notions related to anonymization shows that there is some work to be done in order to achieve a mutual understanding between legal and technical experts concerning some of these notions. Using a dialectical definition process in order to merge technical and legal perspectives on terms seems important for enhancing mutual understanding.

摘要

在生物医学领域共享数据变得越来越重要,但隐私问题对个人层面数据的自由共享设置了限制。数据保护法仅保护与可识别个人相关的数据,而“匿名”数据则可由所有人自由使用。在统计和法律等不同领域,许多与匿名化相关的术语用法往往不一致。关键术语“识别”似乎特别难以定义,因为其定义预设了识别特征的存在,从而导致某种循环。在本文中,我们基于法律视角对重要术语进行了讨论,在阐述与“唯一标识符”“准标识符”和“敏感属性”等术语的使用相关问题之前,先对该法律视角进行了概述。基于这些术语,我们试图通过做出两个决定来规避“识别”一词的循环定义:第一,决定哪个(自然)标识符应代表个人;第二,决定如何识别个人。此外,我们还概述了防止重新识别的匿名化技术/方法。对与匿名化相关的基本概念的讨论表明,为了使法律专家和技术专家就其中一些概念达成相互理解,仍有一些工作要做。使用辩证定义过程来融合术语的技术和法律视角,对于增进相互理解似乎很重要。

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本文引用的文献

1
Anonymising and sharing individual patient data.
BMJ. 2015 Mar 20;350:h1139. doi: 10.1136/bmj.h1139.
2
Publishing data from electronic health records while preserving privacy: a survey of algorithms.
J Biomed Inform. 2014 Aug;50:4-19. doi: 10.1016/j.jbi.2014.06.002. Epub 2014 Jun 14.
3
Disassociation for electronic health record privacy.
J Biomed Inform. 2014 Aug;50:46-61. doi: 10.1016/j.jbi.2014.05.009. Epub 2014 May 28.
4
Routes for breaching and protecting genetic privacy.
Nat Rev Genet. 2014 Jun;15(6):409-21. doi: 10.1038/nrg3723. Epub 2014 May 8.
5
Identifying genetic relatives without compromising privacy.
Genome Res. 2014 Apr;24(4):664-72. doi: 10.1101/gr.153346.112. Epub 2014 Mar 10.
6
Are clinical trial data shared sufficiently today? Yes.
BMJ. 2013 Jul 9;347:f1881. doi: 10.1136/bmj.f1881.
7
Biomedical data privacy: problems, perspectives, and recent advances.
J Am Med Inform Assoc. 2013 Jan 1;20(1):2-6. doi: 10.1136/amiajnl-2012-001509. Epub 2012 Dec 6.
8
Estimating the re-identification risk of clinical data sets.
BMC Med Inform Decis Mak. 2012 Jul 9;12:66. doi: 10.1186/1472-6947-12-66.
9
Improvements on a privacy-protection algorithm for DNA sequences with generalization lattices.
Comput Methods Programs Biomed. 2012 Oct;108(1):1-9. doi: 10.1016/j.cmpb.2011.02.013. Epub 2011 Mar 22.
10
Protecting privacy using k-anonymity.
J Am Med Inform Assoc. 2008 Sep-Oct;15(5):627-37. doi: 10.1197/jamia.M2716. Epub 2008 Jun 25.

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