Research Data Management toolkit for Life Sciences

The Research Data Management Kit (RDMkit) is an online guide that provides good research data management practices for life science projects from planning through to long‑term data reuse. Developed within the ELIXIR Europe network under the Horizon 2020 ELIXIR‑CONVERGE project, it offers practical, FAIR‑aligned guidance written by data stewards and researchers working with life science data. The site helps users make data findable, accessible, interoperable and reusable through structured advice, examples and links to tools and resources.

The website is organised around multiple entry points to support different ways of working. Each section consists of short guidance pages with explanations, recommended practices and links to tools, databases and external resources. From the landing page, users can navigate by:

• data life cycle (planning, collecting, processing, analysing, preserving, sharing and reusing data)
• roles (for example researchers, data stewards, policy makers)
• domain pages (discipline‑specific guidance)
• tool assemblies (curated combinations of tools for particular tasks)
• national resources (country‑specific information and services linked to ELIXIR Nodes)
• a searchable catalogue listing all tools and resources referenced across the site
• training resources

RDMkit covers core research data management topics such as FAIR data, data management plans, data lifecycle stages, data sharing, data archiving and preservation, and metadata for life sciences. It provides guidance on planning research data management, documenting and structuring data, choosing appropriate repositories and aligning with community standards and policies. Dedicated pages address domain‑specific issues, enabling users working with particular data types or methods to find tailored advice and relevant tools.

The content is an open community project, licensed under permissive software and content licences, and is updated regularly through a documented editorial and contribution process. A practical way to start is to use the “Data life cycle” entry point for an overview of tasks at each phase, then consult relevant domain pages and tool assemblies for concrete solutions and tools.
For investigators setting up an academic-sponsored trial, the Research Data Management Toolkit for Life Sciences serves as a strong foundation for designing a robust data management strategy. While it does not replace clinical trial–specific guidance, it complements GCP and regulatory requirements by promoting structured planning, high-quality documentation, secure data handling, standardised workflows, and FAIR data practices. Used alongside clinical trial standards and institutional procedures, it can improve data quality, facilitate collaboration, support compliance, and enhance the long-term value and reproducibility of trial data