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AI-driven solutions for the European Green Deal and data strategy
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Data taken from environmental observations of the Earth is vital for understanding and mitigating the challenges facing humanity and our planet. But this information must be readily available, and computers and digital systems should be able to fully exploit it and maximise the potential benefit of data. The challenges facing data sharing and reuse can be addressed by making data findable, accessible, interoperable and reusable (FAIR). These four principles promote openness and collaboration, thereby maximising the potential value of the data for use in scientific research and other fields. This new CORDIS Results Pack highlights research results funded under the EU Horizon Europe and Digital Europe Programmes that make use of AI, machine learning and high-performance computing to enhance the FAIRness of environmental observation data. It also outlines lessons learnt as well as detailed guiding principles and future visions for implementing FAIRness in environmental observation workflows. Project partners developed tools to convert existing environmental platforms into fully interoperable digital ecosystems for European data access, sharing and interoperability. The objective was to turn these data into open and accessible knowledge at the regional and local level across all European regions and beyond. The pack also illustrates the significance of the project results for the implementation of the European Green Deal and the European strategy for data in general.
- Published:
- Corporate author(s): CORDIS (Publications Office of the European Union)
- Themes: Environmental research , Information technology and telecommunications
- Subject: access to information , artificial intelligence , collaborative economy , data sharing , earth observation , EU strategy , green economy , high-performance computing , open data , research project , research results , right to reuse information , scientific research , systems interconnection
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| ISSN 2599-7890 | ISBN 978-92-78-44761-8 | DOI 10.2830/3948262 | Catalogue number OA-01-25-020-EN-Q |
- Released on EU publications website:
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