From Guidance to Practice: Exploring Research Data Anonymization and Pseudonymization Techniques

AS 22.A.272 - Classroom 10

Based on a published Research Data Pseudonymization and Anonymization: A Practical Guide | Zenodo, this workshop will introduce two approaches to research data de-identification: anonymization and pseudonymization and discuss how these practices can support responsible data sharing and contribute to Open Science.   Through practical examples involving different types of research data, such as textual, numerical, audio-visual, and geospatial research data, participants will be introduced to key steps in the data de-identification process, including understanding the data, identifying privacy risks, applying appropriate anonymization and pseudonymization techniques, assessing re-identification risks, and implementing measures to manage these risks before data sharing.   

By engaging with these practices, participants will gain practical insights into balancing privacy protection with data usability before sharing and making data available for reuse.     We would like to share the following four key messages:   Privacy protection should enable, not prevent, Open Science;  Re-identification risk assessment is a continuous process, not a one-time activity;   Data de-identification involves balancing privacy protection with data usability.

Increase participants' awareness and practical skills in responsible personal data handling, enabling them to apply anonymization and pseudonymization techniques in support of GDPR compliance and FAIR data-sharing practices   Disseminate the anonymization and pseudonymization guide to researchers and research support staff, promoting its adoption by the open science community  Generate insights into community needs and priorities for extending the guide to additional data types and research contexts.