RDMkit: A research data management toolkit for life sciences - Alper, Pinar; D'Anna, Flora; Droesbeke, Bert; Andrabi, Munazah; Andrade Buono, Rafael; Bianchini, Federico; Bösl, Korbinian; Chandramouliswaran, Ishwar; Cook, Martin; Faria, Daniel; Fatima, Nazeefa; Hooft, Rob; et al. (Patterns (New York, N.Y.), 2025)
The rise of data-driven scientific investigations has made research data management (RDM) essential for good scientific practice. Implementing RDM is a complex challenge for research communities, infrastructures, and host organizations. Generic RDM guidelines often do not address practical questions, and disciplinary best practices can be overwhelming without proper context. Once guidelines are established, expanding their reach and keeping them up to date is challenging. The RDMkit is an open community-led resource designed as a gateway to reach the wealth of RDM knowledge, tools, training, and resources in life sciences. The RDMkit provides best-practice guidelines on common RDM tasks expected of data stewards and researchers, specific data management challenges and solutions from life science domains, and tool assemblies showcasing holistic solutions to support the research data life cycle. Built on a reusable open infrastructure, the RDMkit allows organizations to create their own guidelines using it as a blueprint.
Keywords: FAIR; data lifecycle; RDM community; guidelines; tool assemblies