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

The growing complexity of digital research environments and the explosive increase in data volume demand robust, interoperable infrastructures to support sustainable Research Data Management (RDM). In this context, data spaces have emerged—especially in industry—as a powerful conceptual framework for organizing and sharing data across ecosystems, institutional boundaries, and disciplines. Although the term is not yet fully established in the research community, it maps naturally onto scientific practice, where the integration of heterogeneous datasets and cross-disciplinary collaboration are increasingly central. Aligned with the principles of open science, FAIR Digital Objects (FDOs) provide a promising infrastructure for structuring these emerging data spaces. FDOs are standardized, autonomous, and machine-actionable digital entities that encapsulate data, metadata, software, and semantic assertions. They enable both humans and machines to Find, Access, Interoperate, and Reuse (FAIR) digital resources efficiently. By abstracting from underlying technologies and embedding persistent, typed relations, FDOs allow for seamless data integration, provenance tracking, and rights management across domains. This structure promotes reproducibility, trust, and long-term sustainability in data sharing. The Digital Object Interface Protocol (DOIP) serves as a minimal unifying mechanism for interacting with FDOs, playing a foundational role in data interoperability similar to what TCP/IP achieved for the internet. The incremental introduction of FDOs does not require replacing existing repository systems but rather enhances them by providing a unifying abstraction layer. Their integration is already underway, with key specifications extended by the FDO Forum and standardization efforts actively pursued by the German Institute for Standardization (DIN). FDOs not only simplify technical implementation but also offer societal benefits: they support secure storage of legal documents, reinforce data sovereignty, and enable automation of workflows through associated procedures. Ultimately, FDO-based infrastructures provide the backbone for a globally integrated data space, where scientific and societal data can be reused and recombined at scale to generate new knowledge and insights. Using an example from climate research, we demonstrate how climate model data from an institutional data space, observational data from field campaigns, and satellite data (e.g., from the Destination Earth Data Lake) can be combined. By employing STAC (Spatio Temporal Asset Catalog) catalogs defined as FAIR Digital Objects facilitating the European Open Science Cloud (EOSC) Data Type Registry, we address a specific interdisciplinary research question. This approach not only illustrates the practical application of FDOs but also highlights how they can provide a robust framework for tackling larger and more complex scientific challenges by streamlining workflows and enabling collaboration across disciplinary and institutional boundaries.