Speaker
Description
Sustainable development projects often rely on a multitude of data sets from multiple sources given their trans-disciplinary profile. The EU-funded CLEVER (Creating Leverage to Enhance Biodiversity Outcome of Global Biomass) research project crosscuts several disciplines by aiming to quantifying biodiversity and other impacts of trade in major raw and processed non-food biomass value chains. The project involves 12 partners, which are divided in 8 working-packages, where they must work together, sharing data and results. Because of that, the funders requires a Data Management Plan (DMP), with clear guidelines for implementing the FAIR principles on both re-used and newly generated data via empirical field research. The objective of this poster is to provide an empirical example of DMP usage in a project with multiple partners. The DMP defines the handling of research data along the research data life cycle, documenting the context in which research data is collected, created and processed within the project. Some key topics addressed by the plan are utility, re-usage, storage, ethics, and access protocol to the data. In addition, data analyses and the publication of research data are planned ahead to ensure the interpretability and reproducibility of the research results generated during the project period and beyond. As examples of applicability of the DMP, the project commits to use Zenodo as repository, to publish open-access and to assign a globally unique persistent identifier (PI), i.e., a digital object identifier (DOI), for all metadata and generated and reused data. In this context, the long-term availability of the data and the archiving of the research data are also specified. Finally, all measures to ensure and maximize the reusability of the research data of the project are also defined. The EU requires an update on the DMP once an year, which means two times before the end of the project in three years.
