Result description
A second key result of the project will be the development of RO-Crate profiles tailored for climate change adaptation research communities, enabling the structured representation and exchange of complex research outputs within the FAIR2Adapt ecosystem.
RO-Crate is an open, community-driven specification for packaging research data together with rich metadata describing the resources involved in a research process. It uses JSON-LD and linked-data principles to represent datasets, workflows, software, instruments, publications, organisations, and people in a machine-actionable and human-readable format. As a standard for serialising and exchanging Research Objects, RO-Crate enables interoperable sharing of scientific investigations across infrastructures and platforms.
A key strength of RO-Crate is its extensibility through community-defined profiles, which allow specific domains to define recommended metadata structures, controlled vocabularies, and validation rules aligned with their research practices. Within FAIR2Adapt, dedicated RO-Crate profiles for climate change adaptation research will be designed to capture the types of resources commonly produced in this domain, including datasets, models, environmental observations, analytical workflows, and decision-support artefacts.
These profiles will provide clear guidance for researchers on how to structure and describe their research outputs in a consistent and FAIR-compliant way, facilitating interoperability, reproducibility, and reuse. The resulting profiles will be implemented and supported within ROHub, enabling communities to create and publish climate-adaptation Research Objects that can be easily shared, discovered, and reused across EOSC and related research infrastructures.
Problem addressed
A key problem addressed by this result is the lack of consistent, interoperable ways to describe and exchange complex research outputs in climate change adaptation research. Scientific investigations in this domain typically produce a wide variety of resources, including datasets, models, workflows, environmental observations, software, and policy-relevant reports. These outputs are often stored in different repositories and described using heterogeneous metadata practices, making them difficult to discover, interpret, reproduce, and reuse.
While FAIR principles encourage the use of structured and machine-readable metadata, many climate adaptation research outputs remain fragmented and insufficiently described, limiting their integration across infrastructures and their reuse in new analyses or decision-support systems. In particular, there is often no agreed way to capture the relationships between datasets, models, analytical workflows, and the contextual information required to understand how results were produced.
The development of RO-Crate profiles for climate change adaptation communities addresses this challenge by providing domain-specific guidance on how to structure and describe research outputs using a common, interoperable format. These profiles define recommended metadata elements, vocabularies, and relationships tailored to the needs of climate adaptation research.
By enabling consistent representation of research outputs as machine-actionable Research Objects, the result will improve interoperability, support reproducibility of scientific workflows, and facilitate the sharing and reuse of knowledge across projects, infrastructures such as EOSC, and climate adaptation stakeholders.