Summary & Purpose
Environmental research is essential for solving humanity’s sustainability challenges. The era of open data has arrived, with public environmental data proliferating year after year, but the era of open data use has not. Students often lack training to harness ecological and social data, an issue exacerbated by both rising education costs and increasing time pressures on faculty that limit their ability to develop new curricula. Open educational resources for environmental data science can address these challenges. However, it is unclear which data skills are included in existing published teaching materials and whether they adequately prepare students for real-world applications. To fill this knowledge gap, we conducted a systematic literature review focused on the essential data science skills of reproducibility and data linking, i.e. integrating multiple data sources into a single data structure or calculated value. We screened 735 open educational resources, reviewed 266 resources, and found that very few (14%, 36 resources) provide training on linking multiple datasets, and even fewer meet expectations for reproducible open code when linking data (33%, 12/36 resources). The overall contribution of this work is to highlight a need for training in essential data science skills – in particular, data linking and reproducibility – for students of environmental science.
Date of Publication or Submission
7-17-2026
DOI
https://doi.org/10.18122/hes_data.2.boisestate
Funding Citation
This research is supported by the United States Department of Agriculture, Agriculture and Food Research Initiative National Institute of Food and Agriculture, proposal no. 2021-09786, and by the Agriculture and Food Research Initiative Predoctoral Fellowship Program, project award no. 2026-67011-46316, from the U.S. Department of Agriculture’s National Institute of Food and Agriculture.
Single Dataset or Series?
Single Dataset
Data Format
*.csv; R code - plain text; and *.txt
File Size
147 KB
Data Attributes
See readme.txt
Time Period
20260226
Privacy and Confidentiality Statement
Boise State is explicitly compliant with federal and state laws surrounding data privacy including the protection of personal financial information through the Gramm-Leach-Bliley Act, personal medical information through HIPAA, HITECH and other regulations. All human subject data (e.g., surveys) has been collected and managed only by personnel with adequate human subject protection certification.
Use Restrictions
These data from are licensed under the Creative Commons Attribution-NonCommercial 4.0 International license (https://creativecommons.org/licenses/by-nc/4.0/).
Users are free to share, copy, distribute and use the dataset; to create or produce works from the dataset; to adapt, modify, transform and build upon the dataset as long as the user attributes any public use of the dataset, or works produced from the dataset, referencing the author(s) and DOI link. For any use or redistribution of the dataset, or works produced from it, the user must make clear to others the license of the dataset and keep intact any notices on the original dataset.
Code License
Code is licensed under the GNU General Public License 3.0:
Copyright (C) 2026 Carolyn Koehn
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see .
Disclaimer of Warranty
BOISE STATE UNIVERSITY MAKES NO REPRESENTATIONS ABOUT THE SUITABILITY OF THE INFORMATION CONTAINED IN OR PROVIDED AS PART OF THE SYSTEM FOR ANY PURPOSE. ALL SUCH INFORMATION IS PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND. BOISE STATE UNIVERSITY HEREBY DISCLAIMS ALL WARRANTIES AND CONDITIONS WITH REGARD TO THIS INFORMATION, INCLUDING ALL WARRANTIES AND CONDITIONS OF MERCHANTABILITY, WHETHER EXPRESS, IMPLIED OR STATUTORY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT.
IN NO EVENT SHALL BOISE STATE UNIVERSITY BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF INFORMATION AVAILABLE FROM THE SYSTEM.
THE INFORMATION PROVIDED BY THE SYSTEM COULD INCLUDE TECHNICAL INACCURACIES OR TYPOGRAPHICAL ERRORS. CHANGES ARE PERIODICALLY ADDED TO THE INFORMATION HEREIN. COMPANY AND/OR ITS RESPECTIVE SUPPLIERS MAY MAKE IMPROVEMENTS AND/OR CHANGES IN THE PRODUCT(S) AND/OR THE PROGRAM(S) DESCRIBED HEREIN AT ANY TIME, WITH OR WITHOUT NOTICE TO YOU.
BOISE STATE UNIVERSITY DOES NOT MAKE ANY ASSURANCES WITH REGARD TO THE ACCURACY OF THE RESULTS OR OUTPUT THAT DERIVES FROM USE OF THE SYSTEM.
Recommended Citation
Koehn, Carolyn; Hopping, Kelly; Caughlin, Trevor; Som Castellano, Rebecca; and Brandt, Jodi, "Data Linking and Reproducibility Are Underrepresented in Undergraduate Social-Ecological Data Science Training" (2026). Human Environment Systems Datasets. 2.
https://scholarworks.boisestate.edu/hes_data/2