DataPLANT aims to support fundamental plant researchers in data management in various ways. Planning is a crucial component especially in the grant application and setup period of projects. Plant sciences present specific RDM needs, with unique data types and challenges. For this purpose the TA1 team developed a specialized tool: DataPLAN. It addresses challenges in Research Data Management (RDM) specific to plant sciences. DataPLAN, an open-source tool, incorporates prewritten Data Management Plan (DMP) content to facilitate the creation of multiple DMPs. Compatible with Horizon 2020, Horizon Europe, and DFG-funded projects, DataPLAN aims to standardize RDM practices, reduce workload, and enhance collaboration by offering customizable templates.
A Data Management Plan (DMP) outlines procedures for handling research data throughout a project's lifecycle, contributing to efficient RDM. DMPs ensure the findability, accessibility, interoperability, and reusability (FAIR-ness) of data, addressing requirements set by major funding bodies such as Horizon Europe, DFG, NIH, NSF, and SNSF. DMPs involve challenges due to diverse requirements from funding bodies, leading to the development of multiple tools. These tools assist in creating comprehensive DMPs but vary in their support for specific funding bodies, domain-specific RDM approaches, and relevant regulations. Built on the maDMP standard, which facilitates information exchange among these tools, DataPLAN merges the reusable content across various funding contexts and different projects. By linking to minimum information standards and DataPLANT tools such as PlantDataHub, Swate, ARCcommander and ARCitect, DataPLAN enables the accommodation of plant-specific aspects, such as organ-specific growth parameters, high-throughput phenotyping, and plant taxonomy. As DataPLAN provides comprehensive and tailored DMPs in plant sciences, the workload of the users can be reduced by using DataPLAN.