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Overview of iSamples Sample Description Scheme

Authors: Richard, Stephen M.;

Overview of iSamples Sample Description Scheme

Abstract

The Internet of Samples (iSamples) project, funded by the U.S. National Science Foundation, is working to enable connections between diverse observation data linked to physical samples across science domains, facilitating interdisciplinary collaborations. The project brings together sample collection and data repository managers from the System for Earth Sample Registration (SESAR), Open Context (a publishing service maintained by the Alexandria Archive Institute, a metadata repository for archaeological artifacts and ecofacts), the Genomic Observatories Meta-Database (GEOME), and Smithsonian Institution Museum of Natural History (NMNH), representing geoscience, archaeology/anthropology, and biology disciplines. The goal is a searchable global index of material samples linked to appropriate metadata and derived data products. iSamples aims to (i) enable connections between diverse and disparate sample-based observations; (ii) support existing research programs and facilities that collect and manage diverse sample types; (iii) facilitate new interdisciplinary collaborations; and (iv) provide an efficient solution for FAIR samples, avoiding duplicate efforts in different domains. To achieve these goals, iSamples must incorporate and help advance development and adoption of metadata vocabularies and content standards across natural science domains. As a starting point, we have developed a core sample description scheme applicable to material samples from any of the partner systems. Our approach to developing the schema was empirical, based on reviewing existing sample description schemes in use (Table 1) and on reviewing the content in the metadata records from project partner systems to evaluate what fields are populated.

Keywords

metadata, material sample, interoperability

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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