Research Data Management
Data Anonymization
What is data anonymization?
Anonymization involves permanently removing personal identifiers so that data cannot be attributed to an identifiable individual.
Pseudonymization or deidentification involves replacing personal identifiers with alternate identifiers so that data cannot readily be attributed to an identifiable individual, but where the ability to re-identify the data is maintained.
Data Anonymization Software
- ARX Open Source Data AnonymizationARX is a comprehensive open source software for anonymizing sensitive personal data. It supports a wide variety of (1) privacy and risk models, (2) methods for transforming data and (3) methods for analyzing the usefulness of output data.
- AmnesiaAmnesia is a web based application that uses a Java backend to implement the data anonymization algorithm. It runs both in Windows and Linux and requires Java version 8 or greater.
- AnonimatronA free, extendable, open source data anonymization tool.
Anonymization Webinars and Training
Webinars
- Reducing Risk: An Introduction to Survey Data AnonymizationPresented by Kristi Thompson, Research Data Management Librarian at Western University
- RDM Data Anonymization WebinarPresented by: Kristi Thompson, University of Windsor and Manolis Terrovitis, Institute for the Management of Information Systems, Greece
Resources
- BMJ's Preparing raw clinical data for publication: guidance for journal editors, authors, and peer reviewers (2010)Includes a list of 28 direct identifiers, based on information aggregated from policy documents and research guidance from major UK and US funding agencies, governmental health departments and statutes, and three internationally recognised publication ethics resources for editors of biomedical journals.
- Portage Network's Deidentification GuidancePrepared by the Portage Network, COVID-19 Working Groupon behalf of the Canadian Association of Research Libraries (CARL)
Copyright