SESYNC provides access to a remote RStudio session, via a web browser, in order to work in R while directly connected to other SESYNC resources (file storage, databases, the cluster, etc).
Access RStudio by pointing any web browser to https://rstudio.sesync.org/ and logging in with your SESYNC username and password. If you forgot your username or password, please go to https://pwm.sesync.org/. If your SESYNC credentials do not give you RStudio access, please email cyberhelp@sesync.org and ask to enable this resource for your account or whole team.
Once you log in, you will see an RStudio desktop like application. This RStudio Server application works almost identically to the desktop version. To learn how to use all the features of the RStudio IDE, check out the cheatsheet
User contributed R packages can be
installed on RStudio either through the menu or the R console. From the menu
choose Tools -> Install Packages; from the R console use the install.packages
function. If you receive and error saying the package cannot be installed there
is a chance some underlying system library is not installed. Please email the error
message to cyberhelp@sesync.org, and explain which package you need to install.
“Stuff” usually belongs in one of three places:
~/ or equivalently /research-home/USERNAME/)./nfs/PROJECTNAME-data)~/)When you first open RStudio, you will be working in your home directory which is located at “/research-home/USERNAME” or equivalently “~/”. This is a private directory, and only you have access to the files in it. We strongly recommend that you save source code in to your home directory. This will protect against multiple group members attempting to update a project file at the same time. If you need to share code between project members please see ‘Version Controlled Project’ below.
If you’ve requested it your group will have a data directory available. Your
research data directory appears on https://files.sesync.org/ as
PROJECTNAME-data, where PROJECTNAME is the short name assigned for your
project by SESYNC IT staff, and is accessed from https://rstudio.sesync.org at
the path /nfs/PROJECTNAME-data. You can add to this directory either by saving
output from R to folders there, or by using one of the options for uploading
described under How do I access my research data directory?. You should
store all shared data here. Examples of data types that should be placed here
include csv files, landsat imagery, hdf5 data files–anything that’s not code
that you will be sharing with your group members.
We strongly support using version control to manage work with collaborators, not to mention keeping up with principles of reproducible research. SESYNC provides a free GitLab cloud service for private repositories for pre-release projects. Please see Creating a new Git Project for more information on using this service.
To work with version control systems in RStudio, you create an RStudio “project” to pair with a remote repository.
Go to File -> New Project in RStudio
Choose the type of project:
Use Version Control if a remote repository for the project is already populated with files, and be ready to provide the URL (e.g. “git@gitlab.sesync.org:my-group/my-project.git”).
Use Existing Directory if you already have a folder containing only this
project’s files. Once the project exits, go to Project Options -> GitSVN to choose Git
for version control, and be ready to provide the URL (e.g. “git@gitlab.sesync.org:my-group/my-project.git”).
If you don’t have files organized into a folder (or are starting from scratch), start by Creating a new Git Project and go back to Step 1.
Move files into the project directory and add them to a commit.
Since everyone will be working off of the same set of code, there are three options for working with data. If your data is quite small (i.e. a csv with a few hundred rows, also known as “small-batch artisinal data”) you can include it in your project, push it to your remote repository, and everyone will have a clone. Larger datasets should be in your Research Data Directory so that everyone is able to work off one shared copy of the data. Very large datasets may need to be loaded into a RDBMS, and SESYNC provides both MySQL and PostgreSQL servers for this purpose. See our FAQ on Database connections from RStudio or read the following example of shared file usage.
Let’s assume that J. Smith (with USERNAME “jsmith”) is part of the “Trees and
Urban Heat Island Mitigation” working group. When J. Smith logs in to
https://files.sesync.org, the directory “cooltrees-data” will indicate that
the PROJECTNAME mentioned above is cooltrees. After uploading the file
“urbanET.tif”, any member of the project has access to the imagery from RStudio.
For example, a script saved as “~/cool-viz.R” could include
library(raster)
urbanET <- raster("/nfs/cooltrees-data/urbanET.tif")
To make the code more portable (i.e. remove the explicit path to a SESYNC
research data directory), J. Smith could create a shortcut with the R command
file.symlink('/nfs/cooltrees-data', 'data'), and modify the “cool-viz.R”
script to use the shortcut:
library(raster)
urbanET <- raster("data/urbanET.tif")