SEPIA (Sample Essentials, Persistent Identifiers & Attributes) is a scalable platform for managing rich, persistent sample metadata across the research lifecycle. It addresses the common challenge that sample descriptions are often incomplete, fragmented, or insufficiently linked to experiments and datasets. SEPIA assigns a unique, persistent identifier to each sample from day zero, enabling comprehensive tracking of sample history, provenance, modifications, and reuse across experiments, beamlines, and facilities. By supporting IGSN and aligning with the DataCite Metadata Schema, SEPIA enables globally resolvable and citable sample identifiers. Technically, SEPIA operates as a standalone service with a PostgreSQL backend, a Flask-based OpenAPI REST interface, and a modern web frontend. It integrates tightly with ICAT via the python-icat client library, delegating authentication and authorization to ICAT while storing only the sample PID reference in ICAT. By separating experimental metadata from rich sample metadata, SEPIA enhances FAIR compliance and supports reproducible, interoperable, and reusable research workflows.
Sedeqi et al. (Tue,) studied this question.