move relative paths + focus on compatibility

episodes/read-cases.Rmd

@@ -101,13 +101,12 @@ Similarly, you can import files of other formats such as `tsv`, `xlsx`, ... etc.
 
 ### Why should we use the {here} package?
 
-The `{here}` package is designed to simplify file referencing in R projects by providing a reliable way to construct file paths relative to the project root. Here are the three key reasons to use it:
+The `{here}` package is designed to simplify file referencing in R projects by providing a reliable way to construct file paths relative to the project root. The main reason to use it is **Cross-Environment Compatibility**.
 
-- **Relative Paths**: Allows you to use relative file paths with respect to the `R` Project, making your code more portable and less error-prone.
+It works across different operating systems (Windows, Mac, Linux) without needing to adjust file paths. 
 
-- **Cross-Environment Compatibility**: Works across different operating systems (Windows, Mac, Linux) without needing to adjust file paths. This notation `here::here("data", "ebola_cases_2.csv")` avoids using `"data\ebola_cases_2.csv"` in some and `"data/ebola_cases_2.csv"` in others!
-
-- **Reduces Errors**: Avoids the need to use `setwd()` or absolute paths, reducing errors in scripts shared across machines. This avoids notations like `"C:/Users/mycomputer/Documents/projects/helloworld"`.
+- On Windows, paths are written using backslashes ( `\` ) as the separator between folder names: `"data\raw-data\file.csv"` 
+- On Unix based operating system such as macOS or Linux the forward slash ( `/` ) is used as the path separator: `"data/raw-data/file.csv"`
 
 The `{here}` package is ideal for adding one more layer of reproducibility to your work. If you are interested in reproducibility, we invite you to [read this tutorial to increase the openess, sustainability, and reproducibility of your epidemic analysis with R](https://epiverse-trace.github.io/research-compendium/)
 

learners/setup.md

@@ -37,13 +37,13 @@
 + **Challenges**: complete challenges to test your understanding.
 + **Explainers**: add to your understanding of mathematical and modelling concepts with the explainer boxes.
 
 Also check out the [glossary](../reference.md) for any terms you may be unfamiliar with.
 
 ### Epiverse-TRACE R packages
 
 Our strategy is to gradually incorporate specialised **R packages** into a traditional analysis pipeline. These packages should fill the gaps in these epidemiology-specific tasks in response to outbreaks.
 
 ![I](episodes/fig/pkgs-hexlogos-2.png).
 
 <p><figure>
     <img src="episodes/fig/pkgs-hexlogos-2.png"
@@ -248,14 +248,19 @@
 - **Create an RStudio Project**. If needed, follow this [how-to guide on "Hello RStudio Projects"](https://docs.posit.co/ide/user/ide/get-started/#hello-rstudio-projects) to create a New Project in a New Directory.
 - **Create** the `data/` folder inside the RStudio project or corresponding directory. Use the `data/` folder to **save** the data sets to download.
 
-The directory of an RStudio Project named, for example `workshop`, should look like this:
+The directory of an RStudio Project named, for example `training`, should look like this:
 
 ```
-workshop/
+training/
 |__ data/
-|__ workshop.Rproj
+|__ training.Rproj
 ```
 
+**RStudio Projects** allows you to use _relative file_ paths with respect to the `R` Project, 
+making your code more portable and less error-prone. 
+Avoids using `setwd()` with _absolute paths_ 
+like `"C:/Users/MyName/WeirdPath/training/data/file.csv"`.
+
 ::::::::::::::::::::::::::::::::: 
 
 ### 4. Create a GitHub Account