FAIR2Adapt: FAIR to Adapt to Climate Change

FAIR2Adapt: FAIR to Adapt to Climate Change

Duration
2025-2027

Enhancing Climate Adaptation through Improved Data Sharing

The FAIR to Adapt to Climate Change project, or the FAIR2Adapt project, addresses the complex challenges of climate change adaptation (CCA) by tackling the fragmentation and inaccessibility of climate data and resources. Currently, there are many platforms and tools that provide CCA information, but their lack of interoperability and standardised metadata leads to knowledge silos and inefficiencies in tailoring strategies to specific contexts. 

About the project

FAIR2Adapt aims to overcome these issues by creating a collaborative framework that promotes the integration and sharing of FAIR (Findable, Accessible, Interoperable, Reusable) and open data across various CCA domains, building on the European Open Science Cloud (EOSC). 

The project will bridge gaps between scientific knowledge, practical application, and resource sharing to support better climate resilience strategies, particularly by coordinating cross-sectoral knowledge and improving data accessibility for diverse stakeholders. Through use cases linked to the EU Mission on Adaptation to climate change, FAIR2Adapt will demonstrate how to implement equitable, effective, and data-driven climate adaptation strategies at national, regional, and local levels. This includes not only climate-related data but also relevant socioeconomic and environmental information, such as insurance data and infrastructure assessments, which are essential for developing comprehensive strategies

Key innovations

A key innovation of FAIR2Adapt is the implementation of FAIR Digital Objects (FDOs), which enable seamless exchange and reuse of various data types across diverse platforms and tools. This initiative harnesses the capabilities of the EOSC to enhance machine-assisted discovery, selection, access, and use of relevant climate adaptation data, knowledge, and services. By facilitating efficient knowledge sharing and reuse, FAIR2Adapt empowers European regional and local authorities to build resilience against the impacts of climate change.

Collaborative framework

This project unites a consortium of 17 EU partners with Simula Research Laboratory as the project coordinator.

Key objectives include:

  1. Enhance Data Accessibility: Improve the availability and discoverability of diverse data related to climate adaptation, including climate, socioeconomic, and environmental information, leveraging the European Open Science Cloud (EOSC).
  2. Promote Data Interoperability: Develop standardized methods and tools to ensure seamless data sharing and integration across various platforms and sectors, supporting the objectives of the EU Mission on Adaptation to Climate Change.
  3. Implement FAIR Digital Objects (FDOs): Facilitate the exchange and reuse of data through FDOs, enabling stakeholders to access high-quality, machine-actionable information that contributes to effective climate adaptation strategies.

Project partners

  • SRL - Simula Research Laboratory, coordinator (Norway)
  • TIB - Technische Informationsbibliothek TIB (Germany)
  • UPM - Universidad Politécnica de Madrid,(Spain)
  • Institut Francais De Recherche Pour L’Exploration De La Mer IFREMER France
  • PSNC - Poznan Supercomputing and Networking Center (Poland)
  • ALPHA - ALPHA Consult (Italy)
  • Expert.ai - Expert System IBERIA SLU (Spain)
  • UHAM - University of Hamburg (Germany)
  • FCiências.ID – Associação para a Investigação e Desenvolvimento de Ciências FC.ID (Portugal)
  • SEI - SEI Oxford Office Ltd. (UK)
  • P4A - Plan4All (Czech Republic)
  • Lesprojekt, Affiliated Entity (Czech Republic)
  • NKUA - National and Kapodistrian University of Athens (Greece)
  • NERSC - Nansen Environmental and Remote Sensing Center (Norway)
  • GFF - GO FAIR Foundation (Netherlands)
  • FTC - Fresh Thoughts Consulting GmbH (Austria)
  • ADELPHI - adelphi research gemeinnützige GmbH (Germany)
  • DESCI - DeSci Labs, Associated Partner (Switzerland)

Funding source

This project is funded by the Horizon Europe programme under Call HORIZON-INFRA-2024-EOSC-01-01 (external link to the call).

It is a Research & Innovation Action (RIA), Project 101188256.

Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the Granting authority can be held responsible for them.