Aspen Guide

2024-06-20

The goal of the aspen package is to provide data QC, visualization, and publication assistance for MOJN aspen data.

Installation

If you already have a GitHub token for RStudio run the code below to download the aspen package. If you haven’t generated a GitHub token for RStudio, you can follow the guide here to set it up and then run the following code to download the aspen package.

# install.packages("devtools")
devtools::install_github(repo = "nationalparkservice/mojn-aspen-rpackage")

Metadata and AGOL Password

Before running any of the functions in the package you should check that the data in you aspen AGOL database is filled out. Instructions for filling out AGOL metadata can be found [here](https://github.com/nationalparkservice/imd-fetchagol-package.

Before running the functions, it is also recommended that you save the password to your AGOL headless account using the keyring package in R. To add headless account information to the default keyring follow the steps below. The code should only have to be run once.

# Run the function below. Change the username field to the username of your headless account and input the password when prompted
keyring::key_set(service = "AGOL", username = "USERNAME", prompt = "Password for headless account: ")

# To check the key was saved run code below, filling in the username to your headless account
keyring::key_get(service = "AGOL", username = "USERNAME")

Functions

A short summary of what this package contains. For more information see function documentation.

• loadAndWrangleMOJNAspen(): load MOJN aspen data from AGOL into R and perform some basic data wrangling
• loadAndWrangleUCBNAspen(): load UCBN aspen data from AGOL into R and perform some basic data wrangling
• writeAspen(): write aspen data and metadata to CSVs

In addition to these functions the aspen package has some quality control functions, a quality control script, and a visualization script. To learn more about the functions see package documentation. You can find the scripts in the script folder of the GitHub repo or if you cloned the GitHub repo to your desktop you can open the files from there. Download, open, and then run the .qmd file to see the results.