Data Harmonisation Workshop

Course Overview: The ultimate goal of CINECA's vision of a federated cloud-enabled infrastructure making population-scale genomic and biomolecular data accessible across international borders is to enable large-scale federated data analysis responsibly and securely. This will require integrating and harmonizing diverse, large human cohort data using community standards. Data harmonization within and across cohorts adds value to the data for downstream analysis and interpretation and facilitates cross-cohort meta-analysis.
This workshop aims to discuss ways to address common challenges in cohort data harmonization, work towards practical steps to address them, and share best practices. We welcome any cohort with plans for prospective or retrospective data harmonization, enthusiastic about sharing their experience and learning from others' perspectives in cohort data discovery and analysis.
Topics to be covered:
● Data cleaning and curation
● ELSI considerations in merging data
● Data collection standards, ontology terminology and interoperability standards, metadata
● Data storage standards
● Data harmonization
● Sharing cohort summary data

Nicky Mulder; Katherine Johnston; Ayton Meintjes; Isuru Liyanage; Mamana Mbiyavanga; Melanie Goisauf; Carles Garcia; Mamana Mbiyavanga; Alexa Heekes; Lyndon Zass; Sarah Bauermeister; Leslie Lange
Event Theme/Subject Category: 
Data handling
Coordinator's name: 
Nicola Mulder; Mamana Mbiyavanga
Coordinator's email address :;
Name of Venue, Institute: 
City of Venue: 
Country of Venue: 
South Africa
Organisers/Organizing Body: 
CINECA and H3ABioNet
Dates of Event: 
Wednesday, May 18, 2022 - 14:00 to Thursday, May 19, 2022 - 18:00
Eligibility & Application Instructions: 
Intended Audience: Members of cohort projects who are working on data curation and management. Data managers, curators, bioinformaticians, data scientists. Prerequisites: None, but should be involved in cohort data management or analysis. Applicants are
Extra information: 
Link to application form:
Targeted Learning Outcomes: 
Objectives: After this workshop, participants should be able to: ● Do basic data cleaning ● Understand what data standards & ontologies exist for clinical data ● Map their cohort metadata to a data model ● Understand existing approaches to and algorithms for data harmonization ● Prepare summary data from their cohorts
SickleInAfrica Project/PI/Working Group: 
H3ABioNet: A Sustainable African Bioinformatics Network for H3Africa