/AFS_database_code

Code for app to display standardized fish data in North America

Primary LanguageRBSD 2-Clause "Simplified" LicenseBSD-2-Clause

DOI

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/Test_results_full_012723.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

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/Lat_long_AFSshiny_012023.csv, which is not available in the repo due to sensitive information. Package versions and dependencies are tracked with renv.