AFS Standard Fish Data App

The primary purpose of this application is to display data collected across North America on fish species, using a standardized collection approach and resulting comparable metrics by AFS. Additionally, users can upload their own data to compare to the provided standardized data.

Link to the deployed app: https://viz.datascience.arizona.edu/afs-standard-fish-data/

Repository file organization

Dashboard

• app/app.R: file that generates dashboard showing standardized fish data and allows user to upload data to compare
• app/standardized_fish_data.csv: standardized fish data file
• app/R/functions.R: functions to calculate three metrics of interest
• app/www/AFS_sponsor_3.png: image file with sponsor logo displayed on dashboard "About" page
• app/example_user_upload_data.csv: simulated example data to show how user uploaded datasets should be formatted

Data prep

• app/process_user_data.Rmd: generates example user upload data (user_example.csv) shown in app; shows development of metric calculations
• app/user_example.csv: example user upload data
• app/download_map_data.R: code to download the EPA Ecoregions data used in app map
• analysis_scripts: folder with scripts to prepare standardized data; newer version of this is in app/R/functions.R
• input_examples: folder containing additional user upload example datasets

Package versions & dependences

• renv folder
• renv.lock
• .Rprofile

Repository metadata

• .gitignore
• AFS_database_code.Rproj
• LICENSE
• README.md
• CITATION.cff

How to cite

Please use the citation below if you use or modify this tool for research purposes.

Tracy, E., Guo, J., Riemer, K., & Bonar, S. (2023). Code for "AFS Standard Fish Data App" (Version 1.0.0) [Computer software]. https://doi.org/10.5281/zenodo.8169922

How to contribute

If you would like to suggest or make changes to this app, there are a few ways to do so. You can reach out via email to Scott Bonar or the CCT Data Science team with suggestions.You can also create an issue describing a problem with the code or improvements under the "Issues" tab.

If you can make changes to the code yourself, feel free to fork this repo and make a pull request. To run the code locally, follow the instructions in run_locally.md. It will be necessary to download the ecoregions map data by running app/download_map_data.R. Additionally, running the app locally requires the standardized fish records location data file app/sites.csv, which is not available in the repo due to sensitive information. Package versions and dependencies are tracked with renv.

Acknowledgements

This app was developed in collaboration with the University of Arizona CCT Data Science team.