Correct links to containerization page in OnDemand.md

docs/gateways/OnDemand.md

@@ -197,11 +197,11 @@ Now that we have our environment correctly created, we can launch a Jupyter sess
 4. To shut down an RStudio server, go to the "File" menu at the top and choose "Quit session...". If you have made changes to the workspace, then you will be asked if you would like to save them to `~/.RData`, this is not necessary, but can be helpful. Once completed, a prompt will notify you that your R session has ended and will give you the option to restart a server, if desired. However, it is important to note that quitting the session will not cancel the job you are running. Additionally, closing the window will not terminate the job. To terminate the job, you can use the “My Interactive Sessions” tab in Open OnDemand to terminate running sessions.
 
 **_Important Notes:_** 
-* We have designed the RStudio app in Open OnDemand such that it employs versions of R that match the versions of R that are also available in the CURC module stack. This is done to facilitate moving between using RStudio for interactive work, and running larger R workflows as batch jobs on Alpine or Blanca. Due to system constraints, packages you install in a given version of R in RStudio will not be available if you load the equivalent version of the R module, and vice versa. You will need to (re-)install the packages you need when using the equivalent module. This is due to the fact that RStudio is run from an Ubuntu [container](../Software/Containerizationon.html).
+* We have designed the RStudio app in Open OnDemand such that it employs versions of R that match the versions of R that are also available in the CURC module stack. This is done to facilitate moving between using RStudio for interactive work, and running larger R workflows as batch jobs on Alpine or Blanca. Due to system constraints, packages you install in a given version of R in RStudio will not be available if you load the equivalent version of the R module, and vice versa. You will need to (re-)install the packages you need when using the equivalent module. This is due to the fact that RStudio is run from an Ubuntu [container](../software/Containerizationon.html).
 
 ###### Installing dependencies for RStudio (currently available only on Alpine)
 
-As previously mentioned, the RStudio application is run from an Ubuntu [container](../Software/Containerizationon.html). More specifically, the application uses an Ubuntu container paired with a [persistent overlay](https://apptainer.org/docs/user/main/persistent_overlays.html) that is unique to each user. For this reason, when installing a library via `install.packages`, you may receive an error because the container and overlay do not have a dependency required by the library. For example, let's try to install the library `XVector` using the Bioconductor package manager `BiocManager`, using the below commands in the R command prompt.
+As previously mentioned, the RStudio application is run from an Ubuntu [container](../software/Containerizationon.html). More specifically, the application uses an Ubuntu container paired with a [persistent overlay](https://apptainer.org/docs/user/main/persistent_overlays.html) that is unique to each user. For this reason, when installing a library via `install.packages`, you may receive an error because the container and overlay do not have a dependency required by the library. For example, let's try to install the library `XVector` using the Bioconductor package manager `BiocManager`, using the below commands in the R command prompt.
 ```
 install.packages("BiocManager")
 library(BiocManager)