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/
Dashboard
app/app.R
: file that generates dashboard showing standardized fish data and allows user to upload data to compareapp/standardized_fish_data.csv
: standardized fish data fileapp/R/functions.R
: functions to calculate three metrics of interestapp/www/AFS_sponsor_3.png
: image file with sponsor logo displayed on dashboard "About" pageapp/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 calculationsapp/user_example.csv
: example user upload dataapp/download_map_data.R
: code to download the EPA Ecoregions data used in app mapanalysis_scripts
: folder with scripts to prepare standardized data; newer version of this is inapp/R/functions.R
input_examples
: folder containing additional user upload example datasets
Package versions & dependences
renv
folderrenv.lock
.Rprofile
Repository metadata
.gitignore
AFS_database_code.Rproj
LICENSE
README.md
CITATION.cff
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
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
.