Climate Science Meets Data Spaces: FAIR Digital Objects as a Gateway to Interdisciplinary Science

In recent times, data spaces have emerged as an important concept—especially within industrial contexts—as a means of structuring and exchanging data across organizational, institutional, and disciplinary boundaries. Although the scientific community has not yet widely adopted the terminology, the concept holds significant promise for research applications. Data spaces create an organized framework that enables the integration of heterogeneous datasets from various fields, disciplines, and methodological backgrounds, thereby facilitating collaborative analysis. Climate and climate impact research, which inherently depends on data from diverse areas such as meteorology, hydrology, and socio-economic studies, stands to gain substantially from this approach.

In parallel, the movement toward open science is driving researchers to embrace tools and frameworks that ensure data transparency, accessibility, and reproducibility. FAIR Digital Objects (FDOs) play a key role in achieving these aims. As machine-actionable, interoperable, and standardized units, FDOs interlink data, metadata, and associated software components. This structure supports seamless data integration and promotes reuse across scientific disciplines, while also enabling connectivity between distinct data spaces.

To illustrate this, a use case from climate research is presented where climate model output from an institutional data space and quasi-observational data are brought together. By leveraging STAC (SpatioTemporal Asset Catalog) structures—implemented as FAIR Digital Objects and integrated with the European Open Science Cloud (EOSC) Data Type Registry—we tackle an interdisciplinary research problem. This example not only demonstrates the practical value of FDOs but also underscores their potential to serve as a foundation for addressing large-scale, complex scientific questions. They streamline research workflows and foster collaboration across disciplinary and institutional lines.