Introduction
The Federated Learning Kit (FLkit) is created to guide life scientists and data professionals who want to explore the potential of federated learning in health and life sciences. As research increasingly relies on sensitive, distributed data, federated learning provides a way to collaborate responsibly without moving or exposing raw data. FLkit brings clarity to this complex landscape by connecting newcomers and experienced teams alike with trusted tools, proven practices, and real-world examples.
Who is FLkit for?
FLkit is especially designed for those at the start of their federated learning journey. Whether you are a researcher or data scientist in your first months, part of a health data network setting up distributed pipelines, a technical team building secure infrastructure, or a method developer focused on privacy-preserving solutions, FLkit offers you a structured entry point. It combines legal, clinical, technical, and governance perspectives so that all roles in a federated project can find relevant guidance.
Why FLkit?
For newcomers, federated learning can feel overwhelming. Tools, projects, and communities are multiplying fast, making it hard to know where to start. At the same time, technical and clinical teams face different challenges: technical experts may overlook the ethical dimensions of health data, while clinical teams are often hesitant to share data at all.
FLkit provides a clear entry point. It helps users orient themselves, navigate best practices, and build confidence. By combining trusted resources with practical guidance, it bridges perspectives and lowers the barrier to responsible, federated collaboration.
Why Federated Learning?
Federated learning enables collaboration across institutions without centralizing sensitive data. Each partner retains control, while shared models and analytics provide joint insights. This protects privacy, supports compliance with regulations like GDPR, and builds trust between partners. In practice, it allows teams to generate deeper insights from larger, more diverse datasets — all while respecting ethical and legal responsibilities.
What does FLkit aim to achieve?
The mission of FLkit is to empower newcomers in federated health data initiatives by offering a structured, ethical, and practical guide. Our vision is to become the go-to onboarding resource for federated workflows in health:
- Supporting researchers and data professionals at their first steps
- Promoting best practices for privacy, interoperability, and reproducibility
- Embedding ethics and responsible data use through shared insights and lessons
- Facilitating scalable collaboration across institutions and domains
A community-driven resource
FLkit started as a proof-of-concept, inspired by the success of RDMkit, and has since grown through input from interviews and hands-on projects. It is still evolving, with the aim to release a robust, community-led version by the end of 2025. We invite contributors from all disciplines—scientists, clinicians, IT specialists, legal experts, and more—to help shape its future. Together we can make federated learning more accessible, trustworthy, and impactful for the life sciences.
Funding acknowledgement
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How to cite the FLkit
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The ELIXIR Research Data Management Kit makes all of their materials publicly available under Open Source Initiative licenses. The process documents and data are made available under a CC-BY license. Software are made available under an MIT license. For full details on licensing, please visit our License document.