MARINE INSTITUTE

TerraTwin project aims to develop a holistic DTE (Digital Twin of Ecosystem) tool, to better understand the complex interplay between climate change and marine and terrestrial biodiversity. This will be accomplished by leveraging existing multiparametric data from various sources, for marine, land, soil and atmospheric biodiversity, which will be used to feed and train the DTE, which in turn will offer innovative features, such as data analytics anomaly detection, predictive capabilities, feedback loops, policy recommendations and connection with other tools and databases. The following advanced solutions will be integrated to the DTE, to meet its goals: a) Advanced data harmonization to unify and standardize different types of collected biological and environmental data, b) Big data to handle diverse types of datasets, c) Blockchain technology to enhance the functionality, security, traceability and trustworthiness, d) Gathering and harmonizing of Historical and near real time data from existing data bases and on the field activities for climate and biodiversity, d) AI and machine learning, an “in-silico” approach will be enforced to recompile all available physiological information as maps for different key or iconic species, in order to match the different physiological scenarios with changing environmental conditions as mechanism to predict biodiversity changes, as predicted for the different areas by the International, panel for the Climate Change (IPCC), e) DTE integration GUI, f) Simulation for various climatic scenarios based on the selection of areas and environmental data, g) Socio-economic modelling integrating environmental data with human activity patterns, providing a holistic view of how climate and biodiversity changes impact communities and economies and h) Environment-species mapping modelling links species distribution with environmental conditions, enabling the identification of potential habitats and the assessment of biodiversity resilience.

EC contribution:

EUR 77k

Start:

2026-01-01

End:

2028-12-31

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-MISS-2024-CLIMA-01

View on CORDIS (DOI 10.3030/101214557)

iMagine provides a portfolio of free at the point of use image datasets, high-performance image analysis tools empowered with Artificial Intelligence (AI), and Best Practice documents for scientific image analysis. These services and materials enable better and more efficient processing and analysis of imaging data in marine and freshwater research, accelerating our scientific insights about processes and measures relevant for healthy oceans, seas, coastal and inland waters. By building on the computing platform of the European Open Science Cloud (EOSC) the project delivers a generic framework for AI model development, training, and deployment, which can be adopted by researchers for refining their AI-based applications for water pollution mitigation, biodiversity and ecosystem studies, climate change analysis and beach monitoring, but also for developing and optimising other AI-based applications in this field. The iMagine compute layer consists of providers from the pan-European EGI federation infrastructure, collectively offering over 132,000 GPU-hours, 6,000,000 CPU-hours and 1500 TB-month for image hosting and processing. The iMagine AI framework offers neural networks, parallel post-processing of very large data, and analysis of massive online data streams in distributed environments. 13 RIs will share over 9 million images and 8 AI-powered applications through the framework. Having representatives so many RIs and IT experts, developing a portfolio of eye-catching image processing services together will also give rise to Best Practices. The synergies between aquatic use cases will lead to common solutions in data management, quality control, performance, integration, provenance, and FAIRness, contributing to harmonisation across RIs and providing input for the iMagine Best Practice guidelines. The project results will be integrated into and will bring important contributions from RIs and e-infrastructures to EOSC and AI4EU.

EC contribution:

EUR 0

Start:

2022-09-01

End:

2025-08-31

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-INFRA-2021-SERV-01

View on CORDIS (DOI 10.3030/101058625)