Setting up your dashboard repository

  1. To get started, go to the metricminer-dashboard template GitHub repo
  2. Click the green “Use this template” button in the upper right corner. If you do not see it, make sure you are logged in to GitHub (and have an account).
  3. Name your new metricminer dashboard repository on this screen. Then click “Create new repository”.
  4. Create your GitHub secret by going to https://github.com/settings/tokens/new
  5. Make sure your GitHub secret has the repo scopes box checked. Name it something that will remind you it has to do with your metricminer dashboard and then scroll to the bottom and click “Generate Token”. Keep this page open for now.
  6. Return to your metricminer dashboard repository and go to Settings > Secrets and variables > Actions.
  7. Click on New repository secret. Name your new secret exactly METRICMINER_GITHUB_PAT
  8. Copy and paste your Personal access token in the Secret box and then click the green “Add secret” button.

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Setting up your config file

Return to the Code on your metricminer dashboard github repository. And find the _config_automation.yml github file. Open up that file and we will start setting up which metrics you’d like to be retrieved.

Overall settings

metricminer dashboard is an OTTR website with additional metric collecting functionality powered by metricminer. You can read more details about how to update your metricminer/OTTR website here. If you are not familiar with pull requests, we recommend you go read those OTTR docs first.

At the top of the config file you will see a listing of the checks that are run upon filing a pull request. If at any time you don’t want these checks to be run you can set them to no and GitHub Actions will not run them.

# Check that urls in the content are not broken
url-checker: yes
# Render preview of content with changes (Rmd's and md's are checked)
render-preview: yes
# Spell check Rmds and quizzes
spell-check: yes
# Style any R code
style-code: yes

Where your data are saved

By default there are two destinations you can save your data for metricminer (although if you change the code yourself you can feel free to save the data wherever you like). Built in to metricminer-dashboard however we have github and google as your options for a data destination.

By default your data is saved to github. But this will only be appropriate for small amounts of data (you could use something called git-lfs but we find it can be a bit of a hassle).

### Options are "github" or "google"
data_dest: github
folder_path:

If in your config file you choose “google” as your data destination you will need to do two things: 1. Set up your Google Authentication secrets in this repository 2. Give a folder path to your Google drive where you’d like your data to be saved.

Setting up Google Authentication

Your metricminer dashboard will need permissions to Google if you are saving data there, or wanting to use any data from a Google product including: Google Analytics, Google Forms, Googledrive, or Youtube.

To setup Google Authentication for your metricminer dashboard, you’ll need to open up R on your local computer and run the following code: If you aren’t a regular R user you can always use posit.cloud to avoid the installation process.

install.packages("metricminer")
token <- authorize("google")

Then you can use this object to extract two secrets by printing them out like this and you will need to store both to your metricminer dashboard GitHub secrets (which we will describe how to here).

First, return to your metricminer dashboard repository and go to Settings > Secrets and variables > Actions. - Click on New repository secret. Name your new secret exactly METRICMINER_GOOGLE_ACCESS - Copy what is printed out in R when you run:

token$credentials$access_token

and paste it into the Secret box and then click the green “Add secret” button.

Repeat the same steps for the Refresh token except call this METRICMINER_GOOGLE_REFRESH

token$credentials$refresh_token

This work is funded by NCI UE5CA254170 as a part of the ITCR Training Network

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