Citations for physical samples: IGSN and the System for Earth Sample Registration

The System for Earth Sample Registration (SESAR) provides services for the registration and unique identification of samples. Registered metadata is maintained in the SESAR Metadata Catalog. Public metadata is made openly and persistently accessible in both human and machine readable formats. As an integral part of this process, SESAR is an allocating agent for the International Geo Sample Number (IGSN). This persistent and globally unique identifier for samples is used to unambiguously reference samples and resolves to a sample metadata profile stored by SESAR.

SESAR provides tools, services, and best practices to guide researchers through the process of metadata registration and citation throughout the sample lifecycle, from the field or lab to publication and beyond. Use of SESAR has grown from individual investigators to include repositories, museums, and large-scale scientific initiatives.

Samples have unique citation considerations. Do you cite the core, dredge, or sampling location, or do you cite the rock powder or thin section taken from this parent object? To address this, SESAR supports sample hierarchies which capture 'parent-child' relationships between samples and subsamples. This allows users to cite a subsample while also maintaining a connection to the parent sample's metadata in the SESAR registry.

SESAR is part of the EarthChem system of services which includes the EarthChem Library. The ECL is a data repository which incorporates metadata and IGSNs for samples registered in SESAR into it's metadata records following the DataCite structure used for related PIDs. The SESAR and ECL teams have found that citations to samples in publications are inconsistently located and formatted which presents challenges to tracking and linking sample citations.

In this presentation we will discuss best practices for sample citations, challenges faced by the physical sample community, and present a vision of a future framework for sample linkage and information exchange, similar to the way SCHOLIX links scholarly literature and data.