With the ever-increasing amount of research data that is produced within short periods of time, the demand for easy-to-use tools that allow for the collection, annotation, processing, exchange and storage of this data is growing. To support scientists with the challenging task of Research Data Management (RDM) of plant sciences data, the National Research Data Infrastructure (NFDI) consortium DataPLANT is working on the development of a tool and service landscape that enables an all-in-one solution.

The central concept of DataPLANT is the standardized folder structure called the Annotated Research Context (ARC) that packages research data with all associated information into a FAIR digital object. In combination with a variety of provided tools the ARC allows for easy, efficient and FAIR RDM.

Key objectives of DataPLANT are:

Metadata and Ontology Integration:

A core priority of DataPLANT is the development and adoption of common metadata standards and semantic frameworks like ontologies. These enhanced descriptions ensure that datasets are consistently annotated, interpretable, and discoverable, enabling more meaningful comparisons, integrative analyses, and efficient data reuse across various studies and disciplines.

Community-Driven Development:

DataPLANT actively engages the plant research community—including biologists, ecologists, breeders, data scientists, and computational biologists—to co-develop its tools, guidelines, and services. This participatory approach ensures that solutions align with researchers’ real-world needs and that the resulting infrastructure is both user-friendly and future-proof.

Integrated Tools and Services:

The project provides a suite of interoperable tools and services for data management, including automated annotation pipelines, version control frameworks, scalable computing resources, and user-friendly interfaces. These integrated solutions lower the entry barriers for researchers, allowing them to focus on scientific discovery rather than technical overhead.

Sustainable Data Stewardship and Education:

Beyond building an infrastructure, DataPLANT promotes sustainable data stewardship practices through training materials, workshops, and community forums. By cultivating expertise in RDM, DataPLANT helps ensure that researchers and institutions are well-equipped to handle the ever-growing volume and complexity of plant science data.

Please find more information on the project’s homepage: