From Science-Policy to Data-Policy Interfaces: Unpacking Biodiversity Monitoring Data Practices

The integration of marine biodiversity monitoring data into policy and decision-making has remained limited despite numerous efforts to bridge the gap between science and policy. This may be because traditional approaches to science-policy interfaces often segment stakeholders into predefined groups, such as scientists, policymakers, and civil society and assume a bi- or tri-lateral bridging to occur. But this rigid classification often falls short of capturing the complexities of how different actors engage with marine biodiversity knowledge and data. At the same time a lack of understanding persists on the actual data practices of the individuals involved in the marine biodiversity monitoring knowledge value chain from local marine observation sites to universities and national or regional decision-making bodies, i.e. how do individuals engage with marine biodiversity data, what types of data do they use, for what purposes, what challenges do they encounter and what tools do they need.

This study explores these practices through the lens of a Community of Practice (CoP), in which individuals in the marine biodiversity monitoring domain share practices through common engagement with marine biodiversity data. Based on the results of a large online survey, this study applies a latent class analysis (LCA), to examine communities of shared data practices that transcend conventional actor boundaries. We identify three latent types of engaging with marine biodiversity monitoring data: scientific data producers, data managers and analysists, and policy-oriented data appliers and find that data literacy is a major barrier of preventing increased engagement with marine biodiversity data.

The findings contribute with a social scientific view, underscoring the significance of a person- and practice-oriented approach over an affiliation-oriented analysis by illustrating how certain practices extend across traditional actor boundaries, while also uncovering distinct patterns within these communities. This research advocates for a dynamic, community-driven model of science-policy-society interfaces that transcends conventional bi-or tri-lateral frameworks. By re-envisioning science-policy interfaces as inclusive data-policy interfaces, where individuals from various sectors collaboratively develop and share data practices, the study promotes a more integrated and action-oriented vision for environmental governance.

Additionally, the results highlight the pressing need for capacity building and training to enhance data literacy, empowering diverse stakeholders to engage meaningfully with marine biodiversity monitoring data. This inclusive, multi-faceted strategy supports the shift necessary to ensure that science reliably informs ocean decision-making, enabling proactive, data driven governance for sustainable and informed ocean action.