Project description
AI-powered biodiversity data integration into the Digital Twin Ocean
The Horizon Europe Mission’s objective is to safeguard the ocean and its biodiversity by 2030. To achieve this goal, the EU plans to establish a digital knowledge system, including a Digital Twin of the Ocean (DTO), which relies on accurate data regarding marine life and environmental pressures. The collection of this data is vital to ensure that the DTO effectively informs evidence-based policies. The EU-funded DTO-BioFlow project is dedicated to facilitating access to previously unused marine biodiversity data. It also aims to support the sustainable integration of both existing and new data from various sources. The project encompasses the development of the biological aspects of the DTO, encompassing data flows, models and algorithms.
Objective
"The ocean and its biodiversity are essential to life on this planet. Comprehensive data on biodiversity, and related human and environmental pressures are crucial to understand its current state and how this may change. Protecting and restoring biodiversity is one of three objectives of the Horizon Europe Mission to restore our oceans and waters by 2030, enabling the EU to reach its Green Deal and Biodiversity 2030 targets. Identified as one of the Mission ""enablers"", the EU will build on “a digital knowledge system” to include a Digital Twin of the Ocean (DTO) allowing simulation of ‘what if’ scenarios, advancing ocean knowledge, informing evidence-based policy and offering a range of societal applications. To effectively replicate the ocean’s ecology, the DTO requires sustained flows of data on biodiversity and associated pressures. Despite myriad actors collecting biodiversity data, and the development of novel cost-effective monitoring technologies, much of these data are inaccessible or unusable for a variety of reasons, hampering the development of the DTO biological component and limiting its efficacy.
DTO-BioFlow will activate access to (""sleeping"") marine biodiversity data and enable the sustainable integration of existing and new Artificial Intelligence processed and automated data flows from various sources to EMODnet and into the EDITO infrastructure serving the EU DTO. Combining sustained data flows, models and new algorithms, DTO-BioFlow will develop and integrate the biological component of the DTO, including new digital tools and services. Policy-relevant use cases, will demonstrate the benefit for marine ecosystems of continuous data streams flowing through EMODnet and usable by the EU DTO infrastructures and ultimate end-users. Mobilising the marine biodiversity community towards increasing the availability of biodiversity monitoring data into 2030, DTO-BioFlow and its outputs will support the Mission’s actions to protect and restore biodiversity."
Fields of science
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencesbiological sciencesmarine biology
- natural sciencesphysical sciencesastronomyplanetary sciencesplanets
- natural sciencesbiological sciencesecologyecosystems
- natural sciencescomputer and information sciencesdata sciencedata exchange
Keywords
Programme(s)
Funding Scheme
HORIZON-IA - HORIZON Innovation ActionsCoordinator
8400 OOSTENDE
Belgium
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Participants (29)
75005 Paris
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41071 Sevilla
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1000 Bruxelles / Brussel
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
405 30 Goeteborg
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2800 Kongens Lyngby
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1553 Kobenhavn V
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70126 Bari
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02101 Espoo
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31400 Toulouse
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75007 Paris
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75006 Paris
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2595 DA Den Haag
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7034 Trondheim
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7052 Trondheim
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56124 Pisa
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
56124 Pisa
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
2333 CR Leiden
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4450 208 Matosinhos
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2632 BD Nootdorp
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
28006 Madrid
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24148 Kiel
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708 00 Ostrava Poruba
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8000 Aarhus C
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21502 Geesthacht
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69117 Heidelberg
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75794 Paris
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
59375 Dunkerque
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19013 Attikia Anavissos
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1000 Bruxelles / Brussel
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Partners (2)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
PL1 2PB Plymouth
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
KY16 9AJ St Andrews
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