Welcome to ACCORD (Assuring Controls Compliance of Research Data), a web-based platform which allows researchers from public universities across the state of Virginia to analyze and store their sensitive data in a central location.
ACCORD is appropriate for de-identified PII, FERPA, business confidential, and other types of de-identified sensitive data
Thanks to funding provided by the National Science Foundation, ACCORD is a free service for researchers. ACCORD is project-based, meaning investigators request access to the platform, invite co-investigators, store data, and use application based computing environments to perform their computational research. Currently, the platform supports RStudio, JupyterLab, and Theia Python, however other applications will be added soon.
Users cannot load modules inside the OpenOnDemand App for JupyterLab. Therefore it is not possible to convert a Jupyter Notebook to a PDF directly inside the JupyterLab Interactive App on OpenOnDemand.
There are 2 ways to convert a Jupyter Notebook to a PDF:
Directly from the command line. ssh from your terminal and type the following: module load anaconda/2020 texlive jupyter nbconvert –to pdf you_script.ipynb If you want to use GUI, please request a desktop session. Fill out the form as you normally would for JupyterLab. After you get to a desktop, open a terminal (black box next to Firefox in the top bar) and type these commands: module load anaconda/2020 texlive jupyter notebook This will pull up JupyterLab.
Users cannot load modules inside a JupyterLab session. If you need access to modules, please request a desktop session instead of JupyterLab. Fill out the form as you normally would for JupyterLab. After you get to a desktop, open a terminal (next to Firefox in the top bar) and type these commands:
module load gcc jupyter_conda/.2020.11-py3.8 module load … # your modules here jupyter-lab This should start up Firefox shortly. If you accidentally close the window, right click on the link in the terminal and choose “open link” to restart.
An example of using LaTeX inside a JupyterLab session is shown in the screenshot below.
You can create custom kernels from an Anaconda environment or a Singularity container. In both cases you’ll need to install the ipykernel package.
Jupyter kernel based on Anaconda environment To create a custom kernel of the Anaconda environment myenv that uses Python 3.7:
module load anaconda conda create -n myenv python=3.7 ipykernel <other_packages> source activate myenv python -m ipykernel install –user –name myenv –display-name "My Env" Note:
You can customize the display name for your kernel. It is shown when you hover over a tile in JupyterLab. If you do not specify a display name, the default Python [conda env:<ENV_NAME>] will be shown.
Ivy is a secure computing environment for researchers consisting of virtual machines (Linux and Windows). Researchers can use Ivy to process and store sensitive data with the confidence that the environment is secure and meets HIPAA, FERPA, CUI or ITAR requirements.
Are you submitting a grant proposal and need standard information about UVA research computing environments? Get it here. Overview Ivy consists of both virtual computing environments and secure storage. In order to obtain access to either system, users must
Submit an account request, Complete the Information Security Awareness Training, and Ensure their personal computer meets all High Security VPN requirements.