From FAIR Data to FAIR Policy: Strengthening the Biodiversity Science-Policy Interface through Open Science

The transformation of biodiversity knowledge into policy-relevant evidence depends not only on what we know, but on how data are shared, curated, and made accessible across scientific and institutional boundaries. As the science-policy interface (SPI) evolves to support decision-making under complex institutional frameworks such as the EU Biodiversity Strategy for 2030 and the Global Biodiversity Framework, supported by the evidence provided by IPBES assessments. Within this context, the importance of establishing efficient mechanisms for biodiversity policy relies strongly on open biodiversity science and data. The principles of FAIR data - Findable, Accessible, Interoperable, and Reusable - have become essential to building trust, transparency, and usability of scientific knowledge in the field of biodiversity. This session will explore the role of FAIR biodiversity data infrastructures and open science practices in reinforcing the credibility, legitimacy, and salience of the evidence used in policymaking. It will examine how open-access academic publishing and initiatives for making biodiversity data FAIR advance the standards and tools that enable scientists, policymakers, and practitioners to interact within shared knowledge systems. Through practical examples stemming from various initiatives, including several EU-funded projects (e.g. BioAgora, SELINA, CO-OP4CBD or RESPIN), the session will provide a focus on the following topics: how the combination of FAIR data principles and open science approaches can enhance knowledge synthesis and policy relevance,how interoperable datasets facilitate cross-sectoral policy integration (e.g., linking biodiversity, climate, and land-use policies), andhow FAIR-based infrastructures support long-term sustainability of the SPI. Beyond technical solutions, discussions will focus on the institutional and social dimensions of FAIR science - governance, incentives, and collaboration models - that determine whether data are actually used to inform policy. This presentation aims to identify practical pathways for turning FAIR data into FAIR policy, supporting the co-creation of evidence-based actions for nature. Keywords: FAIR data, biodiversity informatics, science-policy interface, open science, data governance, evidence-based policymaking, interoperability