Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19

Abstract The Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) is a European registry for studying the epidemiology and clinical course of COVID-19. To support evidence-generation at the rapid pace required in a pandemic, LEOSS follows an Open Science approach, making data available...

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Autores principales:	Carolin E. M. Jakob, Florian Kohlmayer, Thierry Meurers, Jörg Janne Vehreschild, Fabian Prasser
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/75301dc6967641f282d7b5b64817d09f
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spelling	oai:doaj.org-article:75301dc6967641f282d7b5b64817d09f2021-12-02T11:43:44ZDesign and evaluation of a data anonymization pipeline to promote Open Science on COVID-1910.1038/s41597-020-00773-y2052-4463https://doaj.org/article/75301dc6967641f282d7b5b64817d09f2020-12-01T00:00:00Zhttps://doi.org/10.1038/s41597-020-00773-yhttps://doaj.org/toc/2052-4463Abstract The Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) is a European registry for studying the epidemiology and clinical course of COVID-19. To support evidence-generation at the rapid pace required in a pandemic, LEOSS follows an Open Science approach, making data available to the public in real-time. To protect patient privacy, quantitative anonymization procedures are used to protect the continuously published data stream consisting of 16 variables on the course and therapy of COVID-19 from singling out, inference and linkage attacks. We investigated the bias introduced by this process and found that it has very little impact on the quality of output data. Current laws do not specify requirements for the application of formal anonymization methods, there is a lack of guidelines with clear recommendations and few real-world applications of quantitative anonymization procedures have been described in the literature. We therefore believe that our work can help others with developing urgently needed anonymization pipelines for their projects.Carolin E. M. JakobFlorian KohlmayerThierry MeurersJörg Janne VehreschildFabian PrasserNature PortfolioarticleScienceQENScientific Data, Vol 7, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Carolin E. M. Jakob Florian Kohlmayer Thierry Meurers Jörg Janne Vehreschild Fabian Prasser Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
description	Abstract The Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) is a European registry for studying the epidemiology and clinical course of COVID-19. To support evidence-generation at the rapid pace required in a pandemic, LEOSS follows an Open Science approach, making data available to the public in real-time. To protect patient privacy, quantitative anonymization procedures are used to protect the continuously published data stream consisting of 16 variables on the course and therapy of COVID-19 from singling out, inference and linkage attacks. We investigated the bias introduced by this process and found that it has very little impact on the quality of output data. Current laws do not specify requirements for the application of formal anonymization methods, there is a lack of guidelines with clear recommendations and few real-world applications of quantitative anonymization procedures have been described in the literature. We therefore believe that our work can help others with developing urgently needed anonymization pipelines for their projects.
format	article
author	Carolin E. M. Jakob Florian Kohlmayer Thierry Meurers Jörg Janne Vehreschild Fabian Prasser
author_facet	Carolin E. M. Jakob Florian Kohlmayer Thierry Meurers Jörg Janne Vehreschild Fabian Prasser
author_sort	Carolin E. M. Jakob
title	Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
title_short	Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
title_full	Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
title_fullStr	Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
title_full_unstemmed	Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
title_sort	design and evaluation of a data anonymization pipeline to promote open science on covid-19
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/75301dc6967641f282d7b5b64817d09f
work_keys_str_mv	AT carolinemjakob designandevaluationofadataanonymizationpipelinetopromoteopenscienceoncovid19 AT floriankohlmayer designandevaluationofadataanonymizationpipelinetopromoteopenscienceoncovid19 AT thierrymeurers designandevaluationofadataanonymizationpipelinetopromoteopenscienceoncovid19 AT jorgjannevehreschild designandevaluationofadataanonymizationpipelinetopromoteopenscienceoncovid19 AT fabianprasser designandevaluationofadataanonymizationpipelinetopromoteopenscienceoncovid19
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Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19

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