Samples are a basic unit for observations in a wide range of Earth and environmental sciences and thus a critical entity for data search and data access. Considering the growing interest in accessing research data at a more granular level and integrating sample-based data for advanced data mining and analysis, this session aims to address the urgent need to develop and implement standards and best practices for machine-readable and interoperable sample-based data. To date, no common protocol is used across different domains to describe and structure data generated by studying physical samples in the field or analyzing them in the laboratory. Substantial progress has been made with the IGSN to provide globally unique, persistent, and resolvable identifiers for samples that allow unambiguous citation of samples, linkages between samples, data, and publications, and previously impossible discovery of data for a given sample that has been published in different papers and data systems. Conceptual models exist such as the Observations and Measurements (O&M) ISO standard, and several ontologies have been developed within specific domains, most notably the Semantic Sensor Network Ontology (SSN) in the Earth Sciences and the Biological Collections Ontology (BCO). This session invites the broadest range of stakeholders working with samples and sample-based data to define requirements, gather use scenarios, and evaluate options,and possible pathways toward developing, testing, and implementing interoperability standards for sample-based data.