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FAIR2Adapt: Advancing Climate Change Adaptation Strategies through FAIR and open  data sharing and Research Infrastructures

Authors: Anne Fouilloux; Barbara Magagna;

FAIR2Adapt: Advancing Climate Change Adaptation Strategies through FAIR and open  data sharing and Research Infrastructures

Abstract

The FAIR2Adapt European-funded project (grant number: 101188256) aims to transform data into actionable knowledge to shape effective Climate Change Adaptation (CCA) strategies. By collaborating with the European Open Science Cloud (EOSC), we leverage its broad range of services and resources, aligning with the EOSC interoperability framework and the FAIR Implementation Framework Catalogue of Resources. This collaboration enhances the accessibility, interoperability, and usability of crucial environmental data, supporting the development of climate adaptation strategies across Europe.The project spans diverse case studies, such as investigating radionuclide dispersal in the Arctic, monitoring coastal water quality through the RiOMar project, and addressing urban climate-induced stressors in Hamburg. These case studies are built on a FAIR-by-design approach, utilizing technologies such as RO-Crate for implementing FAIR Digital Objects (FDOs), which ensure compliant data packaging and sharing, and nanopublications for representing research outputs in a reusable, formalized format. We also leverage I-ADOPT, a semantic bridging framework, and tailored FDO services to enhance collaboration and facilitate open data sharing.By fostering collaboration between private and public sectors, we emphasize integrating research data with practical adaptation measures, enabling the reuse of FAIRified data (including datasets, software, workflows, and machine learning models) to meet regulatory requirements, such as the EU taxonomy for sustainable activities. This approach supports cohesive climate risk assessments across multiple EU regions, demonstrating how FAIR and open data sharing can drive effective adaptation strategies. The project also aligns with the EU Mission’s objective of enhancing climate resilience in European regions and communities.Through transfer cases and collaboration with other initiatives, FAIR2Adapt aims to demonstrate its scalability and applicability beyond the project’s completion, extending its impact to a wide range of climate adaptation scenarios. Stakeholder engagement and capacity-building activities will be key in raising awareness and devising customized solutions, ensuring that the project’s outcomes are grounded in the practical needs of local communities and policymakers.In summary, FAIR2Adapt contributes to the EOSC mission by fostering data sharing and collaboration, and by building a scalable, extensible framework for data sharing that can be adapted to future climate adaptation challenges. Its impact will span scientific advancement, economic resilience, social-environmental well-being, and responsive policy development, promoting multidisciplinary cooperation, enhancing trust in science, and stimulating a climate-smart economy. Ultimately, FAIR2Adapt seeks to construct a more resilient, inclusive, and knowledge-based society capable of efficiently tackling the challenges of climate change.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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