SUMMARY In modern reproducible, hypothesis-driven plant research, scientists are increasingly relying on research data management (RDM) services and infrastructures to streamline the processes of collecting, processing, sharing, and archiving research data. FAIR (i.e., findable, accessible, interoperable, and reusable) research data play a pivotal role in enabling the integration of interdisciplinary knowledge and facilitating the comparison and synthesis of a wide range of analytical findings. The PLANTdataHUB offers a solution that realizes RDM of scientific (meta)data as evolving collections of files in a directory – yielding FAIR digital objects called ARCs – with tools that enable scientists to plan, communicate, collaborate, publish, and reuse data on the same platform while gaining continuous quality control insights. The centralized platform is scalable from personal use to global communities and provides advanced federation capabilities for institutions that prefer to host their own satellite instances. This approach borrows many concepts from software development and adapts them to fit the challenges of the field of modern plant science undergoing digital transformation. The PLANTdataHUB supports researchers in each stage of a scientific project with adaptable continuous quality control insights, from the early planning phase to data publication. The central live instance of PLANTdataHUB is accessible at (https://git.nfdi4plants.org), and it will continue to evolve as a community-driven and dynamic resource that serves the needs of contemporary plant science.

The technological advancements in bio-science research are resulting in the generation of vast amounts of complex and heterogeneous data sets from individual studies. Efficient Research Data Management solutions based on FAIR principles can guide the research groups toward standardizing and packaging the study-specific research results into uniquely identifiable digital objects that are easily traceable and identifiable, leading to knowledge discovery, collaboration, and innovation. However, to explore the inter-dependencies among data sets originating from different study disciplines, it is crucial to deploy a generic data-centric RDM solution that overcomes inherent challenges and helps manage complex data sets. This solution should respect participating groups’ data and security policies while providing an integrated data view. In this paper, we introduce ARC Registry, a cloud-native search and exploration application that integrates experimental metadata from individual research groups that have deployed PLANTdataHUB (FAIR-RDM) solution. The focus is on the parts of PLANTdataHUB and ARC Registry that facilitate near-real-time integration of experimental metadata from standardized digital objects (Annotated Research Contexts) across participating research groups.