Sample Identifiers and Metadata to Support Data Management and Reuse in Multidisciplinary Ecosystem Sciences

Damerow, Joan E.; Ely, Kim S.; Varadharajan, Charuleka; Boye, Kristin; Brodie, Eoin L.; Burrus, Madison; Chadwick, K. Dana; Crystal-Ornelas, Robert; Elbashandy, Hesham; Alves, Ricardo J. Eloy; Goldman, Amy E.; Haberman, Ted; Hendrix, Valerie; Kakalia, Zarine; Kemner, Kenneth M.; Kersting, Annie B.; Merino, Nancy; O’Brien, Fianna; Perzan, Zach; Robles, Emily; Sorensen, Patrick; Stegen, James C.; Walls, Ramona L.; Weisenhorn, Pamela; Zavarin, Mavrik; Agarwal, Deborah

doi:10.5334/dsj-2021-011

Title: Sample Identifiers and Metadata to Support Data Management and Reuse in Multidisciplinary Ecosystem Sciences

Journal Article · Thu Mar 18 00:00:00 EDT 2021 · Data Science Journal

DOI:https://doi.org/10.5334/dsj-2021-011· OSTI ID:1768764

Damerow, Joan E. ^[1];

^[2]; Varadharajan, Charuleka ^[1]; Boye, Kristin ^[3]; Brodie, Eoin L. ^[1]; Burrus, Madison ^[1]; Chadwick, K. Dana ^[4]; Crystal-Ornelas, Robert ^[1]; Elbashandy, Hesham ^[1]; Alves, Ricardo J. Eloy ^[1]; Goldman, Amy E. ^[5]; Haberman, Ted ^[6]; Hendrix, Valerie ^[1]; Kakalia, Zarine ^[1]; Kemner, Kenneth M. ^[7]; Kersting, Annie B. ^[8]; Merino, Nancy ^[8]; O’Brien, Fianna ^[1]; Perzan, Zach ^[9]; Robles, Emily ^[1] more »

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Brookhaven National Lab. (BNL), Upton, NY (United States)
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stanford Univ., Palo Alto, CA (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Metadata Game Changers, Boulder, CO (United States)
Argonne National Lab. (ANL), Lemont, IL (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Stanford Univ., Palo Alto, CA (United States)
Univ. of Arizona, Tucson, AZ (United States)

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. Furthermore, our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data.

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Research Organization:: Brookhaven National Lab. (BNL), Upton, NY (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)

Grant/Contract Number:: SC0012704; AC02-05CH11231; AC52-07NA27344; 2004562; AC05-76RL01830

OSTI ID:: 1768764

Alternate ID(s):: OSTI ID: 1777339; OSTI ID: 1788368

Report Number(s):: BNL-221088-2021-JAAM; LLNL-JRNL-819595; PNNL-SA-158301

Journal Information:: Data Science Journal, Vol. 20, Issue 1; ISSN 1683-1470

Publisher:: CODATACopyright Statement

Country of Publication:: United States

Language:: English

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