DataHub

• Begin by creating a public GitHub repository to host all your course materials. This repository will serve as the foundation for generating unique links that you'll share with your students.
• If you are interested in using the GUI version of Github, Check out Github Desktop

• The DataHub link generator is a Berkeley-specific version of the nbgitpuller link generator browser extension. Nbgitpuller is a tool that streamlines the assignment distribution process in course settings. When students click the unique links generated by this tool, they'll be taken directly to Jupyter or RStudio notebooks in DataHub, bypassing the complexities of Git that would otherwise create barriers to entry.
• Install DataHub Link Generator extension in your chrome browser. If you need further assistance with the plugin installation, please check the following documentation.

To generate a shareable link,

• Access the notebook in the GitHub repository.
• Generate a shareable link by following the step-by-step instructions in this documentation.
• Share the link with students through tools such as bcourses, Ed discussions etc..

• Browser Compatibility: Ensure you are using a compatible web browser (Chrome, Firefox, Safari) that is updated to the latest version. 
• Internet Connection: Verify you have a stable internet connection to access DataHub smoothly.

• Activate CalNet ID: Ensure your CalNet ID is activated and functioning properly.
• Access DataHub: Go to datahub.berkeley.edu and log in with your CalNet ID to verify you can access the platform. ( Allow bcourses to authenticate “DataHub is requesting access to your account”.)

• Overview: Review student resources to understand the varied features of DataHub. Interface 
• Tour: Explore the DataHub interface, including the JupyterLab and RStudio environments.

• Course Hub: Use nbgitpuller links shared by your course instructors to launch notebooks in DataHub 
• Notebooks and Scripts: Open and work on Jupyter Notebooks, R scripts, or other files as provided by your instructor. 
• To manage files in JupyterHub: To upload a file, click the "Upload" button in the DataHub interface and select the file from your local machine. To download a file, right-click on the file in the DataHub interface and select the "Download" option

• Regular Use: Regularly log in to DataHub to complete assignments, run analyses, and work on projects. 
• Save Work: Save your progress frequently. It's good practice to manually save your work as well. 
• Check Storage Space: Delete unnecessary files; Regularly check the storage size of the home directories and back up content if you are exceeding 5-10 GB. You can do this by opening a Terminal, and executing `du -sh` 
• Don’t Duplicate Shared Directory Content: If your course work requires shared directories where instructors are storing large datasets, don’t create a copy of the same files in your home directory. As a practice, always read data from the shared directories. 
• Do Your Work in Sub Directories: Create a sub directory for each assignment and do your work there. Avoid working on assignments from the root directory as they may lead to data issues if done wrongly.

• Note: DataHub doesn’t offer collaboration(link is external)(link is external) tools that allow students to work with each other on the same notebook. We are testing the feature extensively and will roll it out when the known security and data corruption issues are solved. 
• Instructor Feedback: Share your work with instructors or TAs for feedback by downloading and submitting your notebooks as required.

• Restart Kernel/Server: Try restarting your kernel as a classic troubleshooting step to see if the error goes away. If the problem persists, restart your server
• Having too many notebooks open on Datahub can cause issues. To check running processes and kill them follow instructions to kill process in Curriculum Guide
• Support: Reach out to course TAs for technical help, and they will contact the DataHub staff if they are unable to resolve your issue.
• What if I can’t access DataHub?
  • Ensure your CalNet ID is active and try logging in again. If the problem persists, inform your TA or check out this guide for additional help.
• How do I install additional packages?
  • Use `!pip install package-name` in a Jupyter Notebook cell for Python packages, or `install.packages("package-name")` in the R console.
• Can I use DataHub off-campus?
  • Yes, you can access DataHub from anywhere with an internet connection.
• What should I do if I encounter a technical issue?
  • First, try restarting your kernel. If the issue persists, contact your course TA, and if they can’t resolve it they will reach out to DataHub staff.

• Backup coursework: Back up your notebooks and data to either your personal device or an external storage service like Google Drive, Dropbox. The data present in the course specific hubs will go away by the end of the semester.
• User Home Directory Archiving: Files unused for 30 days will be archived and stored in a low cost storage. You will need to open a request with the DataHub team to retrieve your unused files.

• Clean Up: Clean up your DataHub workspace by deleting unnecessary files and folders.
• Feedback: Provide feedback on your experience with the DataHub team to help improve the service for future students.