Anonymity

Last updated on Nov 3, 2021

Definition: Anonymising data refers to removing, generalising, aggregating or distorting any information which may potentially identify participants, peer-reviewers, and authors, among others. Data should be anonymised so that participants are not personally identifiable. The most basic level of anonymisation is to replace participants’ names with pseudonyms (fake names) and remove references to specific places. Anonymity is particularly important for open data and data may not be made open for anonymity concerns. Anonymity and open data has been discussed within qualitative research which often focuses on personal experiences and opinions, and in quantitative research that includes participants from clinical populations.

Related terms: Anonymising, Clinical populations, Confidentiality, Research ethics, Research participants, Vulnerable population

Reference: Braun and Clarke (2013)

Drafted and Reviewed by: Claire Melia, Tsvetomira Dumbalska, Bethan Iley, Tamara Kalandadze, Bettina M.J. Kern, Sam Parsons, Charlotte R. Pennington, FlĂĄvio Azevedo, Madeleine Pownall, Birgit Schmidt

We are currently working to link the references directly. For now, the complete reference list can be viewed here.