Towards Standardization of the Earth Observation Data Product Supply Chain – Are OCI Artifacts the Key to Ubiquitous and Scalable EO Data Handling?

Abstract. The exponential growth of Earth Observation (EO) data generated by satellites demands scalable, efficient, and interoperable methods not only for storing and managing, but also for distributing data packages tailored to diverse use cases. The Open Container Initiative (OCI) registries, together with the OCI artifact specifications, present a promising framework for packaging, exchanging, and managing EO-derived and combined datasets. Originally developed for software containers, OCI registries offer key capabilities such as content-addressable storage, data integrity verification, cryptographic attestation, layered packaging, and version control. A notable advantage is their ability to act as access gateways—enforcing access control at the artifact level without requiring direct exposure of the underlying storage backends (e.g., S3, GCS, Azure Blob, NFS, Ceph, IPFS). The ubiquity of OCI registries—spanning public platforms, managed enterprise services, and open-source deployments—makes them a practical foundation for distributing EO data across heterogeneous environments without custom infrastructure. This paper investigates the applicability of today’s OCI registry ecosystem to EO data pipelines, evaluating both strengths and current limitations in handling large, complex, and dynamic datasets. We explore design conventions and layout strategies to align EO products with the OCI artifact model, with a focus on metadata representation, access efficiency, and storage reuse. By comparing self-contained data packages with modular, layered asset stores, we highlight trade-offs in retrieval performance, interoperability, and client complexity. Recent trends in machine learning model distribution further underscore the growing relevance of OCI-based artifacts for scientific and geospatial workflows. Ultimately, this research positions OCI artifacts as a viable foundation for scalable, standards-aligned, and interoperable EO data handling—paving the way toward more streamlined and resilient data supply chains in the EO domain.