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Federated data analysis Training school & Hackathon
Federated Data Training to Real-World FAIR Hackathon: Practical Applications of FAIR Principles

Date: 11 - 14 May 2026
Timezone: Athens
Duration: 4 days
Language of instruction: English
We invite you to express your interest in taking part in the Federated Analysis Hackathon, held from 11 to 14 May 2026 in Cyprus, jointly organised by the HELIOS and HemaFAIR projects.
This hands-on training and hackathon will bring together participants and leading international experts in federated analysis to explore innovative approaches for privacy-preserving data analysis and federated learning across distributed datasets.
There is no registration fee for this event. Registration link: https://0lyz0gsa.forms.app/federated-analysis-fair-training-school
HELIOS members will receive reimbursement in accordance with COST rules, while non-HELIOS participants are welcome to join but will need to cover their own travel and accommodation expenses. [Join HELIOS here: https://e-services.cost.eu/action/CA22119/working-groups/apply]
Please note that completing this Expression of Interest form does not guarantee selection for participation in the event. Confirmed invitations to attend the training school will be sent out in the first week of March 2026.
Contact: For any clarifications, please contact Dr Sotiroula Chatzimatthaiou (sotiroulac@cing.ac.cy)
Keywords: Data Analysis, FAIR Data, Federated Analysis, Federated data analysis, Learning, Hands-on, Research Data Management
City: Ayia Napa
Country: Cyprus
Prerequisites:
-Basic hands-on experience in data analysis (e.g. working with datasets in Python or R)
-Familiarity with common data formats (such as CSV or other tabular data)
-A general understanding of FAIR data principles is beneficial but not mandatory
While prior experience with federated analysis frameworks or federated learning is not required, participants are expected to be comfortable following technical instructions and working with data analysis tools. Introductory concepts and guided hands-on support will be provided during the event.
Learning objectives:
-Gain an introductory understanding of federated analysis, federated learning, and related frameworks
-Learn how FAIR data principles and data standardisation support federated and privacy-preserving analysis
-Develop practical skills in working with a common data model across distributed datasets, including basic federated querying
-Become familiar with ethical, legal, and governance aspects of federated analysis, with a focus on privacy and responsible data use
-Collaborate effectively in multidisciplinary teams to explore real-world federated analysis challenges
Host institutions: The Cyprus Institute of Neurology & Genetics, HELIOS COST Action, HemaFAIR
Target audience: Scientists, Researchers, Data Scientists, Data managers
Capacity: 20
Event types:
- Workshops and courses
Tech requirements:
-A laptop running Windows (preferred); macOS or Linux are also accepted
-A modern web browser (e.g. Chrome or Firefox)
-Basic familiarity with data analysis workflows; prior exposure to FAIR data principles is an advantage but not required
-Ability to follow simple setup instructions before the event
Credit / Recognition: Certification of attendance
Cost basis: Free to all
Sponsors: COST Association, Funded by the European Union
Scientific topics: FAIR data, Data management, Data acquisition, Data identity and mapping, Data curation and archival, Data governance, Data protection
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