While Data Management Plans (DMPs) are often perceived by researchers as an administrative burden or an afterthought to research activities, it is increasingly recognised that best research practice requires data to be made available to others. Crucially, this must be done with sufficient information on research context and provenance to enable data reuse. This is commonly achieved by ensuring that data are Findable, Accessible, Interoperable and Reusable – the FAIR principles.

Although the concept of FAIR data is widely accepted, implementing it in practice remains challenging. Community standards and appropriate tools are not always available or fully developed. In response to this challenge, PARC’s FAIR Data group has spent the past three years mapping the existing landscape, adapting available tools for chemicals risk assessment, and developing bespoke solutions where significant gaps were identified.

As a result, PARC is now at a stage where datasets and their accompanying metadata – the information that explains why, how and by whom the data were generated – can be made FAIR in a consistent and meaningful way. The specific approach depends on the type of data involved. To date, PARC has focused on three key domains: Human Biomonitoring, Chemicals in the Environment, and Toxicology. Each domain has its own terminology, preferred data repositories (or, in some cases, a lack of agreed repositories), and community standards at different levels of formalisation.

The PARC Deliverable D7.3 – Data Infrastructure Tools and Services provides a comprehensive overview of these three core areas of the chemicals risk assessment domain, outlining the tools, standards and infrastructures required to support FAIR data implementation.

The quality and relevance of this work have been formally recognised by PARC’s external reviewers. During the latest periodic review meeting, the the report was described as “essential reading for all PARC members”. The written review further highlighted that the Plan is well structured, clearly explains FAIR principles, and effectively presents the processes and structures supporting data management within PARC.

This recognition underlines the importance of data management as a cornerstone of PARC’s scientific and regulatory ambitions. All partners are therefore strongly encouraged to consult the document, which serves as a practical guide to FAIR data implementation across the project. An updated version of the DMP will also be presented and discussed at the PARC Consortium Meeting in Dublin in June 2026.