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Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19.
Jakob, Carolin E M; Kohlmayer, Florian; Meurers, Thierry; Vehreschild, Jörg Janne; Prasser, Fabian.
  • Jakob CEM; University Hospital Cologne, Cologne, Germany.
  • Kohlmayer F; School of Medicine, Technical University of Munich, Munich, Germany.
  • Meurers T; Berlin Institute of Health (BIH), Berlin, Germany.
  • Vehreschild JJ; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
  • Prasser F; University Hospital Cologne, Cologne, Germany.
Sci Data ; 7(1): 435, 2020 12 10.
Article in English | MEDLINE | ID: covidwho-972239
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Registries / Pandemics / Data Anonymization / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: English Journal: Sci Data Year: 2020 Document Type: Article Affiliation country: S41597-020-00773-y

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Registries / Pandemics / Data Anonymization / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: English Journal: Sci Data Year: 2020 Document Type: Article Affiliation country: S41597-020-00773-y