Advancing Climate Data (Re)usability through FAIR Digital Objects and Decentralized Technologies

Climate science relies heavily on the effective creation, management, sharing, and analysis of massive and diverse datasets. As the digital landscape evolves, there is a growing need to establish a framework that ensures FAIRness in handling climate science digital objects. Especially, the machine-to-machine actionability of digital objects will be a crucial step towards future AI assisted workflows. Motivated by a use case, this contribution proposes the adoption of the Fair Digital Object (FDO) concept to address the challenges associated with the emerging spread in interdisciplinary reuse scenarios of climate model simulation output, as well as observational data. FDOs are encapsulations of data and their metadata made accessible via persistent identifiers (PIDs) in a way that data and their context will remain a complete unit as FDO travels through cyberspace and time. They represent a paradigm shift in data management, emphasizing the machine-actionability principles of FAIRness and the requirements enabling cross-disciplinary research. The FDO concept can be applied to various digital objects, including data, documents and software within different research disciplines and industry areas. The aim of this work is to commit to an FDO standard in climate science that enables standardized and therefore automated data analysis workflows and facilitates the extraction and analysis of relevant weather and climate data by all stakeholders involved. The current work expands on the efforts made to enable broad reuse of CMIP6 climate model data and focuses on requirements identified to enable automated processing of climate simulation output and their possible implementation strategies. In doing so, we propose the following concrete avenues: (1) Enriching the PID profiles of climate model and observational data in accordance with the FDO concept while taking into account the needs of the climate science community will lead to improved findability of digital objects, especially for machines. (2) Adopting the FDO concept for existing data management solutions, such as intake-esm and Spatio Temporal Asset Catalogs (STAC), can lead to improved data handling in line with prevailing community practices. (3) Furthermore, combining the FDO concept with the Inter Planetary File System (IPFS) offers benefits, such as decentralized storage, improved data integrity and easier data sharing through content addressing of digital objects. Eventually, implementing an FDO standard will benefit climate science as well as related communities in several ways: The reusability of the data will facilitate the cost-effective use of existing economically expensive climate model and observational data. Also, these approaches will lead to higher transparency and will increase the reproducibility of research workflows and consolidate scientific results.