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ECOTWIN

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Emulating complex causal socio ecological models in digital twins of ocean

To fully realise the potential of the European Digital Twin Ocean (DTO) to empower citizens, entrepreneurs, scientists and policymakers with accessible knowledge about ocean and coastal domains, new models, tools and methods are n... ver más

31/08/2027

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3M€

Presupuesto del proyecto: 3M€

Líder del proyecto Líder desconocido

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-05-21

HORIZON-MISS-2021-OCEAN-04-01: Lighthouse in the Baltic and the No... ExpectedOutcome:Project results are expected to contribute to all of the following expected outcomes...

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THE PROVOST, FELLOWS, FOUNDA...

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Duración del proyecto: 39 meses Fecha Inicio: 2024-05-21
Fecha Fin: 2027-08-31

Líder del proyecto Líder desconocido

Presupuesto del proyecto 3M€

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Descripción del proyecto To fully realise the potential of the European Digital Twin Ocean (DTO) to empower citizens, entrepreneurs, scientists and policymakers with accessible knowledge about ocean and coastal domains, new models, tools and methods are needed to understand and assess the complex interactions of social, economic and ecological factors. ECOTWIN delivers innovative graph theoretic solutions, developed using a multi-actor approach with policy makers, local communities, marine and coastal industries and communities, to address the challenges of modelling marine socio-ecological systems and integrating these models into the emerging DTO framework. Innovations include four different classes of novel socio-ecological models based on concepts from mathematics (graph theory), control engineering (stability), computer science (generative AI), statistics (Bayesian theory) and information science (entropy), combined with dynamic participatory feedback from stakeholders, and methodological protocols enabling seamless integration with DTOs by accounting for the interoperability, accessibility, reliability and sustainability of transdisciplinary data. The models comprise: 1) quantitative causal graph theoretic models, 2) qualitative causal graph theoretic models, 3) network models with participatory feedback and 4) parallel generative AI models. Through validation in four use cases in the North Sea (Belgium, Germany), Celtic Sea (Ireland), Thracian Sea (Greece) and Waterford Harbour (Ireland), tools will be developed for assessing scenarios including the relationships between factors including ecosystem services and health, geopolitical factors, fishing job losses, tourism and marine renewables development. Results will enable what-if scenario analysis and impact assessments, exploring the interconnected impacts of environmental changes, human pressures and policy implementation to empower better decision-making to support ocean health social prosperity and a thriving blue economy.

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