TY  - JOUR
AU  - Rumbold, John
AU  - Pierscionek, Barbara
PY  - 2018
DA  - 2018/11/22
TI  - Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
JO  - JMIR Med Inform
SP  - e47
VL  - 6
IS  - 4
KW  - anonymization matrix
KW  - big data
KW  - data protection
KW  - privacy
KW  - research ethics
AB  - 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. 
SN  - 2291-9694
UR  - http://medinform.jmir.org/2018/4/e47/
UR  - https://doi.org/10.2196/medinform.7096
UR  - http://www.ncbi.nlm.nih.gov/pubmed/30467101
DO  - 10.2196/medinform.7096
ID  - info:doi/10.2196/medinform.7096
ER  -