%0 Journal Article
%@ 2291-9694
%I JMIR Publications
%V 6
%N 4
%P e47
%T Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
%A Rumbold,John
%A Pierscionek,Barbara
%+ School of Science and Technology, Nottingham Trent University, 50 Shakespeare Street, Nottingham, NG1 4FP, United Kingdom, 44 1158483738, John.Rumbold@NTU.ac.uk
%K anonymization matrix
%K big data
%K data protection
%K privacy
%K research ethics
%D 2018
%7 22.11.2018
%9 Proposal
%J JMIR Med Inform
%G English
%X Background: The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. Objective: We propose a matrix for setting different standards, which is responsive to context and public expectations. Methods: The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix. Results: The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved. Conclusions: The matrix offers a tool with context-specific standards for anonymization in data research. 
%M 30467101
%R 10.2196/medinform.7096
%U http://medinform.jmir.org/2018/4/e47/
%U https://doi.org/10.2196/medinform.7096
%U http://www.ncbi.nlm.nih.gov/pubmed/30467101