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Lookup NU author(s): Hugh Garner, Dr Stuart Wheater, Emeritus Professor Paul BurtonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2025. Published by Oxford University Press.Motivation: The validity of epidemiologic findings can be increased using triangulation, i.e. comparison of findings across contexts, and by having sufficiently large amounts of relevant data to analyse. However, access to data is often constrained by practical considerations and by ethico-legal and data governance restrictions. Gaining access to such data can be time-consuming due to the governance requirements associated with data access requests to institutions in different jurisdictions. Results: DataSHIELD is a software solution that enables remote analysis without the need for data transfer (federated analysis). DataSHIELD is a scientifically mature, open-source data access and analysis platform aligned with the 'Five Safes' framework, the international framework governing safe research access to data. It allows real-time analysis while mitigating disclosure risk through an active multi-layer system of disclosure-preventing mechanisms. This combination of real-time remote statistical analysis, disclosure prevention mechanisms, and federation capabilities makes DataSHIELD a solution for addressing many of the technical and regulatory challenges in performing the large-scale statistical analysis of health and biomedical data. This paper describes the key components that comprise the disclosure protection system of DataSHIELD. These broadly fall into three classes: (i) system protection elements, (ii) analysis protection elements, and (iii) governance protection elements.
Author(s): Avraam D, Wilson RC, Aguirre Chan N, Banerjee S, Bishop TRP, Butters O, Cadman T, Cederkvist L, Duijts L, Escriba Montagut X, Garner H, Goncalves G, Gonzalez JR, Haakma S, Hartlev M, Hasenauer J, Huth M, Hyde E, Jaddoe VWV, Marcon Y, Mayrhofer MT, Molnar-Gabor F, Morgan AS, Murtagh M, Nestor M, Nybo Andersen A-M, Parker S, Pinot De Moira A, Schwarz F, Strandberg-Larsen K, Swertz MA, Welten M, Wheater S, Burton P
Publication type: Article
Publication status: Published
Journal: Bioinformatics Advances
Year: 2025
Volume: 5
Issue: 1
Online publication date: 10/03/2025
Acceptance date: 05/03/2025
Date deposited: 23/04/2025
ISSN (electronic): 2635-0041
Publisher: Oxford University Press
URL: https://doi.org/10.1093/bioadv/vbaf046
DOI: 10.1093/bioadv/vbaf046
Data Access Statement: Not applicable
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