Development and Design of FLKit: A Structured Onboarding Toolkit for Federated Learning in Health and Life Sciences

2026-06-22

AI Summary

This work addresses the lack of structured guidance faced by health and life sciences teams when initiating federated learning (FL) projects, often hindered by fragmented frameworks, complex governance, and diverse stakeholder roles. To bridge this gap, the authors propose FLKit—an open, community-maintained onboarding toolkit that innovatively incorporates role-aware entry points tailored to clinicians, legal experts, governance officers, and technical staff. Grounded in ELIXIR’s research data management principles, FLKit integrates an interdisciplinary glossary, a curated tool catalog, and a full-cycle workflow methodology. It supports project planning and documentation through four lifecycle phases and FAIR-aligned FL Story templates. By December 2024, FLKit comprised 39 pages across eight chapters, featuring seven real-world case studies spanning multiple sclerosis, inflammatory bowel disease, and genomics.

Abstract

Federated learning lets institutions train shared models without moving their data, which makes it a natural fit for health and life sciences research under strict privacy regulation. The methods are maturing fast, but the practical barrier now comes earlier: a team starting a federated project meets a scattered mix of frameworks, governance obligations, and unfamiliar roles, with no structured place to begin that fits its own background. FLKit closes that gap. It is an open, community-maintained onboarding toolkit that takes a multidisciplinary team through the full federated learning lifecycle and gives every contributor, clinical, legal, governance, or technical, a role-aware entry point instead of assuming fluency across all four. We modeled it on the ELIXIR Research Data Management Kit and built it with a multidisciplinary core team, a wider consortium supplying milestone reviews and roadmap direction, and external practitioners interviewed to keep the content grounded in real practice. FLKit sits on four lifecycle stages, Governance, Infrastructure, Wrangling, and Analysis, and connects them through 11 role-specific entry points, a cross-disciplinary glossary, a reusable FAIR-aligned FL Story template for planning and documenting projects, and a curated directory of tools, frameworks, and communities. Since the December 2024 demo it has grown to 39 pages across eight sections, with seven FL Stories documenting completed and ongoing projects in multiple sclerosis disability prediction, inflammatory bowel disease, genomics, and brain-computer interfaces. It is openly available at https://uhasselt-biomedicaldatasciences.github.io/federated-learning-toolkit/ and welcomes contributions from across the life sciences.

Problem

• federated learning
• onboarding
• health and life sciences
• governance
• multidisciplinary collaboration

Innovation

• Federated Learning
• Onboarding Toolkit
• Multidisciplinary Collaboration
• FAIR Principles
• Role-aware Design