Lecture, Presentation, Training materials

HemaFAIR Lecture 16 - Privacy-Preserving Record Linkage – Use Cases, Approaches, and Implementation Scenarios in Rare Diseases

This HELIOS and HemaFAIR webinar provides an introduction to Privacy-Preserving Record Linkage (PPRL) and its application in rare disease and biomedical research.

Delivered by Dr. Dieter Hayn, the session explores the principles and practical approaches for securely linking sensitive health data across institutions without exposing personally identifiable information. It covers key privacy-preserving techniques, including cryptographic methods, hashing, and secure multi-party computation, as well as challenges related to interoperability, governance, and regulatory compliance.

The webinar is aimed at researchers, clinicians, data scientists, and data stewards interested in secure health data integration, collaborative research, and privacy-preserving approaches for rare disease and clinical research.

DOI: https://doi.org/10.5281/zenodo.20391927

Licence: Creative Commons Attribution 4.0 International

Contact: Dr Sotiroula Chatzimatthaiou at [email protected]

Keywords: FAIR principles, HemaFAIR, HELIOS, Open Science, Healthcare, Hemoglobinopathies, Rare Diseases, Privacy-Preserving, Record Linkage, Registries

Competency level: • Beginner

Target audience: Researchers, Data Scientist, Data stewards, Data managers, Students, Clinicians

Resource type: Lecture, Presentation, Training materials

Version: 1

Status: Active

Prerequisites:

No prerequisites. This material is intended as a first introduction to the Biomedical Ontologies

Learning objectives:

-Define Privacy-Preserving Record Linkage (PPRL) and its role in biomedical research.
-Compare different methods for privacy-preserving data linkage.
-Understand the challenges of linking sensitive health data while maintaining privacy and regulatory compliance.
-Identify opportunities for implementing PPRL in rare disease and clinical research settings.
-Appreciate the role of secure data integration in enabling collaborative and federated research initiatives.

Date created: 2026-03-30

Date published: 2026-05-26

Authors: Dieter Hayan

Contributors: Petros Kountouris, Sotiroula Chatzimatthaiou

Scientific topics: Data protection, Data mining, Open science, FAIR data, Rare diseases


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