Have a personal or library account? Click to login

Abstract

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data.

Language: English
Submitted on: Dec 5, 2020
Accepted on: Feb 12, 2021
Published on: Mar 18, 2021
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2021 Joan E. Damerow, Charuleka Varadharajan, Kristin Boye, Eoin L. Brodie, Madison Burrus, K. Dana Chadwick, Robert Crystal-Ornelas, Hesham Elbashandy, Ricardo J. Eloy Alves, Kim S. Ely, Amy E. Goldman, Ted Haberman, Valerie Hendrix, Zarine Kakalia, Kenneth M. Kemner, Annie B. Kersting, Nancy Merino, Fianna O'Brien, Zach Perzan, Emily Robles, Patrick Sorensen, James C. Stegen, Ramona L. Walls, Pamela Weisenhorn, Mavrik Zavarin, Deborah Agarwal, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.