{"authors":[{"id":null,"fullName":"Schaap, Dick","name":"Dick","surname":"Schaap","rank":1,"pid":{"id":{"scheme":"orcid_pending","value":"0000-0001-6562-068x"},"provenance":null}}],"openAccessColor":null,"publiclyFunded":false,"eoscIfGuidelines":null,"type":"publication","language":{"code":"eng","label":"English"},"countries":null,"subjects":[{"subject":{"scheme":"keyword","value":"Artificial intelligence"},"provenance":null},{"subject":{"scheme":"keyword","value":"aquatic science"},"provenance":null}],"mainTitle":"iMagine - an AI platform supporting aquatic science use cases","subTitle":null,"descriptions":["iMagine advances aquatic science by providing open access to AI-powered image analysis tools tailored to support data-driven marine research and innovation. Aligned with the European Green Deal and the Mission Restore Our Ocean and Waters by 2030, iMagine contributes to the development of Digital Twins of the Ocean (DTOs), aiming to enhance sustainable resource use, biodiversity preservation, and climate resilience.At its core, the iMagine AI Platform, built on the AI4OS framework and supported by the AI4EOSC project, offers significant computational resources via the EGI e-Infrastructure Federation. This platform enables an end-to-end AI workflow, including image annotation, deep learning model training, and inference, fostering collaboration between AI specialists and aquatic scientists and accelerating the integration of AI into marine science workflows.Key functionalities include:    A scalable computational platform for AI-based image analysis in aquatic research.  Development and deployment of AI-driven services addressing scientific and environmental challenges.  Provision of labelled FAIR datasets to support model training, validation, and retraining.  Knowledge sharing and capacity building on AI applications in aquatic science.   iMagine supports diverse use cases such as floating litter classification, plankton taxonomy, ecosystem  monitoring, oil spill prediction, vessel activity detection via underwater acoustics, and coral reef health assessment. These applications feed into and enhance thematic and local DTOs, contributing to better-informed marine policy and management decisions.The iMagine Competence Centre, comprising AI experts, scientists, and data providers, facilitates ongoing collaboration through regular meetings, training sessions, and feedback loops to improve model accuracy and usability.  To ensure data quality, transparency, and reproducibility, iMagine adopts best practices in data stewardship and model development. Publicly available datasets on Zenodo enable community engagement in model validation and improvement. Moreover, iMagine actively collaborates with initiatives like EOSC, AI4EU, and Blue-Cloud 2026 to advance the uptake of AI in marine and aquatic sciences.By delivering valuable AI services and tools, iMagine contributes to the broader ecosystem of Digital Twins of the Ocean, supporting sustainable ocean governance, conservation, and climate action."],"publicationDate":"2025-06-16","publisher":"Zenodo","embargoEndDate":"2025-06-16","sources":null,"formats":null,"contributors":null,"coverages":null,"bestAccessRight":{"code":"c_abf2","label":"OPEN","scheme":"http://vocabularies.coar-repositories.org/documentation/access_rights/"},"container":null,"documentationUrls":null,"codeRepositoryUrl":null,"programmingLanguage":null,"contactPeople":null,"contactGroups":null,"tools":null,"size":null,"version":null,"geoLocations":null,"id":"doi_dedup___::8b1af382b95b5fa8f7e0e2be8b08d30b","originalIds":["50|datacite____::8b1af382b95b5fa8f7e0e2be8b08d30b","10.5281/zenodo.15698470","oai:zenodo.org:15698470","50|od______2659::8b1af382b95b5fa8f7e0e2be8b08d30b","50|datacite____::a224d919570ef941ddc4502fc69bf022","10.5281/zenodo.15698469"],"pids":[{"scheme":"doi","value":"10.5281/zenodo.15698470"},{"scheme":"doi","value":"10.5281/zenodo.15698469"}],"dateOfCollection":null,"lastUpdateTimeStamp":null,"indicators":{"citationImpact":{"citationCount":0.0,"influence":2.2251732E-9,"popularity":2.342466E-9,"impulse":0.0,"citationClass":"C5","influenceClass":"C5","impulseClass":"C5","popularityClass":"C5"}},"projects":[{"id":"corda_____he::cee20577a3cf295391e596e40621449f","code":"101058625","acronym":"iMagine","title":"Imaging data and services for aquatic science","funder":"European Commission","pids":[{"scheme":"doi","value":"10.3030/101058625"}]}],"organizations":null,"communities":[{"code":"nbfc","label":"Italian National Biodiversity Future Center","provenance":null},{"code":"eu-conexus","label":"European University for Smart Urban Coastal Sustainability","provenance":null},{"code":"eosc","label":"EOSC","provenance":null},{"code":"egi","label":"EGI : advanced computing for research","provenance":null}],"collectedFrom":[{"key":"openaire____::9e3be59865b2c1c335d32dae2fe7b254","value":"Datacite"},{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"}],"instances":[{"pids":[{"scheme":"doi","value":"10.5281/zenodo.15698470"}],"license":"CC BY","type":"Presentation","urls":["https://dx.doi.org/10.5281/zenodo.15698470"],"publicationDate":"2025-06-16","refereed":"nonPeerReviewed","hostedBy":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"},"collectedFrom":{"key":"openaire____::9e3be59865b2c1c335d32dae2fe7b254","value":"Datacite"}},{"pids":[{"scheme":"doi","value":"10.5281/zenodo.15698470"}],"alternateIdentifiers":[{"scheme":"oai","value":"oai:zenodo.org:15698470"}],"license":"CC BY","accessRight":{"code":"c_abf2","label":"OPEN","scheme":"http://vocabularies.coar-repositories.org/documentation/access_rights/","openAccessRoute":null},"type":"Other literature type","urls":["http://dx.doi.org/10.5281/zenodo.15698470","https://zenodo.org/records/15698470"],"publicationDate":"2025-06-16","refereed":"nonPeerReviewed","hostedBy":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"},"collectedFrom":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"}},{"pids":[{"scheme":"doi","value":"10.5281/zenodo.15698469"}],"license":"CC BY","type":"Presentation","urls":["https://dx.doi.org/10.5281/zenodo.15698469"],"publicationDate":"2025-06-16","refereed":"nonPeerReviewed","hostedBy":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"},"collectedFrom":{"key":"openaire____::9e3be59865b2c1c335d32dae2fe7b254","value":"Datacite"}}],"links":[{"header":{"relationType":"resultProject","relationClass":"isProducedBy","relatedIdentifier":"corda_____he::cee20577a3cf295391e596e40621449f","relatedRecordType":"project","relationProvenance":"sysimport:crosswalk:repository","trust":"0.9"},"collectedfrom":[{"dsId":"openaire____::3f264f93cf3b0cfc4ede188a6300455c","dsName":"CORDA - COmmon Research DAta Warehouse - Horizon Europe"}],"projectTitle":"Imaging data and services for aquatic science","code":"101058625","funding":{"funder":{"id":"ec__________::EC","shortname":"EC","name":"European Commission","jurisdiction":{"code":"EU","label":"European Union"},"pid":null},"level0":{"id":"ec__________::EC::HE","description":"Horizon Europe Framework Programme","name":"HE"},"level1":{"id":"ec__________::EC::HE::HORIZON-RIA","description":"HORIZON  Research and Innovation Actions","name":"HORIZON-RIA"},"level2":{"id":null,"description":null,"name":null}},"startDate":"2022-09-01","endDate":"2025-08-31"}],"otherTitles":null,"inDiamondJournal":false,"green":true,"isGreen":true,"isInDiamondJournal":false}