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Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis Cover

Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis

Data Science Journal
Volume 21 (2022): Issue 1
By: Maegen B. Simmonds,  William J. Riley,  Deborah A. Agarwal,  Xingyuan Chen,  Shreyas Cholia,  Robert Crystal-Ornelas,  Ethan T. Coon,  Dipankar Dwivedi,  Valerie C. Hendrix,  Maoyi Huang,  Ahmad Jan,  Zarine Kakalia,  Jitendra Kumar,  Charles D. Koven,  Li Li,  Mario Melara,  Lavanya Ramakrishnan,  Daniel M. Ricciuto,  Anthony P. Walker,  Wei Zhi,  Qing Zhu and  Charuleka Varadharajan  
Open Access
|Feb 2022

References

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DOI: https://doi.org/10.5334/dsj-2022-003 | Journal eISSN: 1683-1470
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Language: English
Submitted on: Jun 22, 2021
Accepted on: Nov 23, 2021
Published on: Feb 7, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
data management,
archiving guidelines,
FAIR,
terrestrial models,
simulations

© 2022 Maegen B. Simmonds, William J. Riley, Deborah A. Agarwal, Xingyuan Chen, Shreyas Cholia, Robert Crystal-Ornelas, Ethan T. Coon, Dipankar Dwivedi, Valerie C. Hendrix, Maoyi Huang, Ahmad Jan, Zarine Kakalia, Jitendra Kumar, Charles D. Koven, Li Li, Mario Melara, Lavanya Ramakrishnan, Daniel M. Ricciuto, Anthony P. Walker, Wei Zhi, Qing Zhu, Charuleka Varadharajan, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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