Enhancing the FAIRness of Arctic Research Data Through Semantic Annotation Cover

Enhancing the FAIRness of Arctic Research Data Through Semantic Annotation

Data Science Journal

Volume 23 (2024): Issue 1

By: Steven S. Chong , Mark Schildhauer , Margaret O’Brien , Bryce Mecum and Matthew B. Jones

Open Access

|Jan 2024

Authors

Steven S. Chong

stevenchong@berkeley.edu

University of California Berkeley Library, University of California, Berkeley CA

Mark Schildhauer

schild@nceas.ucsb.edu

National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara CA

Margaret O’Brien

margaret.obrien@ucsb.edu

Marine Science Institute, University of California, Santa Barbara CA

Bryce Mecum

mecum@nceas.ucsb.edu

National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara CA

Matthew B. Jones

jones@nceas.ucsb.edu

National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara CA

DOI: https://doi.org/10.5334/dsj-2024-002 | Journal eISSN: 1683-1470

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Language: English

Submitted on: Apr 5, 2023

Accepted on: Nov 28, 2023

Published on: Jan 17, 2024

Published by: Ubiquity Press

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Arctic research data,

data discovery,

knowledge modeling,

semantic annotation,

data repository

© 2024 Steven S. Chong, Mark Schildhauer, Margaret O’Brien, Bryce Mecum, Matthew B. Jones, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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