In a recent presentation titled “Continuity in data management plan: examples of the Horizon projects PoshBee and WildPosh”, WildPosh coordinator Denis Michez discussed how data is managed across multiple projects under the European Pollinator Initiative (EPI). The talk was part of the Living Data 2025 conference that took place in Bogotá, Colombia, in October.

Data management in WildPosh 

One of the objectives of the WildPosh project is to understand the relationship between pesticides and pollinator health. To achieve this, researchers study pesticide impacts at different levels - both in the laboratory and in the field - and combine data from the project with data from the literature and from other projects.

Several work packages within WildPosh focus on data. Work package 4 handles data curation and in-silico data collection and aims to build an open-source, curated database that will also include information generated within the project itself. Work package 5 uses available data to develop a risk assessment methodology. Work package 7 focuses on the effective communication, dissemination and exploitation of data. 

The project follows a Data Management Plan (DMP) that applies the FAIR principles - ensuring that data are Findable, Accessible, Interoperable, and Reusable. In practice, this means using a centralised, well-curated system for data management. However, Michez emphasised that it is necessary to think not only about how data is handled within WildPosh’s lifespan, but also about the project’s long-term legacy. Moreover, all data sets should be integrated with existing ones, including those from the PoshBee project.

Ensuring continuity in the data management plan

Since WildPosh operates within the European Pollinator Initiative, data management goes beyond the scope of a single project. Michez highlighted that several Horizon projects - including PoshBee and WildPosh - are meant to build upon each other. This continuity requires a shared framework so that datasets produced at different times or by different research teams can be reused effectively.

For this to be possible, the first step was choosing a repository system that could incorporate existing datasets and would be accessible to members of all other EU projects. The EU Pollinator Hub, developed by the BeeLife European Beekeeping Coordination and funded by the European Commission, was selected. This online platform supports open access and integrates and centralises standardised data on pollinators.

Michez outlined the strategy partners follow to ensure that datasets can be merged, used, and understood by members of different projects. The process starts with defining requirements for each research partner - including what (meta)data will be collected or required, what regulatory compliance is needed (GDPR, GLP, certification, etc.), and what terminology, infrastructure, timelines and quality expectations apply.

Standardisation is essential for this continuity. A glossary and vocabulary were developed at the beginning of the process to ensure that all projects use the same definitions and translations of terms. Metadata is also standardised and follows a unified format across partners.

Each project partner was asked to provide their own data templates -  similar templates were converged, and a shared format was established. Thanks to this standardisation, datasets are reusable and compatible, and can easily be uploaded to the Pollinator Hub. Users can request data from the system, and data owners retain control over whether to share it.

By following FAIR principles and using shared templates, metrics, methodologies and structures, researchers can merge datasets from multiple projects and timeframes, and preserve research well beyond the lifespan of individual projects.

Watch the full presentation (from 1:10:19 to 1:20:47): youtube.com/watch?v=0reDdr4gVtM