Analytical framework for marine socioecological data curation

The SURIMI project aims at developing an integrated framework for marine socio-ecological modelling, grounded in high-quality secondary data and FAIR (Findable, Accessible, Interoperable, Reusable) principles. The SURIMI project emphasizes the integration of socioeconomic, environmental, and ecological datasets into a cohesive framework to support decision-making processes and facilitate the European Digital Twin of the Ocean. A key element of this framework is the SURIMI Data Lake, which provides a single, harmonised access point for the datasets required across the project. The project prioritises the use of secondary data from external repositories through a systematic scoping exercise to identify relevant data sources and assess their quality and completeness. The Data Lake integrates fisheries landings, CPUE estimates, stock assessments, biological and ecological traits and socio-economic data sourced mainly from the EU Data Collection Framework (DCF) and complementary repositories. All acquired datasets are managed according to the SURIMI Data Management and Exploitation Plan (DMEP) and stored in a centralised SURIMI data lake for streamlined use in assessments, models and e-tools. Within Work Package 2 (WP2), the project focuses on data scoping, acquisition, harmonisation, and the development of socio-economic and ecological indicators to support modelling efforts in WP3, as well as the development of visualisation tools in WP4. Special attention is paid to ensuring coherence in spatial and temporal resolution, as well as to enabling the interoperability of socio-economic and environmental datasets and the reusability of the formulated protocol with other datasets. The integration of these datasets and methodologies within the SURIMI framework enables the project to advance marine ecosystem modelling by tackling long-standing interoperability challenges of combining datasets that differ in resolution and structure, from fine-grained biological and environmental observations to highly aggregated economic statistics. To reconcile these discrepancies, new disaggregation protocols are tested to realign data. The practical application of these methods is demonstrated through two contrasting case studies in the Western Mediterranean: one characterised by comprehensive data availability and another one where data gaps required model-based integration of AIS and DCF/AER information. The results include detailed maps of landings and values, port-level species price estimates, and temporal analyses of price variability by gear and vessel type. Overall, deliverable D2.1 establishes the methodological basis for the SURIMI modelling suite within the European Digital Twin of the Ocean, offering a scalable approach to data integration that strengthens the analytical capacity for sustainable and adaptive marine governance.