About the Noteable Service

EDINA's Noteable is a cloud-based application providing access to Jupyter notebooks, developed and supported by EDINA, the University of Edinburgh. It can be accessed online from any browser on most devices, via a VLE integration.

• The purpose of Noteable is to allow students and staff to access Jupyter notebooks at any time without the request for pre-installation on individual devices.  
• Noteable is integrated with Learn VLE through LTI1.3 integration to allow for a launch point into a pre-set environment for a course. 
• Noteable is available to all University staff for teaching purposes. There is no cost associated with using the Noteable service.
• Noteable can be used for assessment and feedback using the build in Formgrader functions.
• Visit Noteable Web Site for more information.

See the list of Notebooks offered in Noteable with the respective primary libraries on EDINA website.

Currently (April 2024), if you launch Noteable LTI 1.3 from Learn, these are the available notebooks on a dropdown list:

• Astronomy Notebook
• BioChemistry Notebook
• GeoScience Notebook 
• Language and Machine Learning
• R with Stan
• RStudio
• Sage Notebook
• Standard Notebook (Python 3)
• Stata Notebook

There are also Geoscience (Collaborative session) and Standard (Collaborative session). They use the JupyterLab interface and allow users to co-edit Notebook Documents in real-time.

In addition, Schools' Web Development is a lightweight Jupyter Lab Environment designed to support teaching of basic web development in html, css and javascript.

Each user is allocated with 10GB of storage and 4GB of RAM. Please refer to the data retention policy (on EDINA website).

Computational notebooks are interactive documents that can contain both computer code (such as Python) as well as rich text and media content (paragraphs of text, equations, images and links). As these notebooks are interactive it allows the user to write, edit and run code and then see the output of those code cells within the document. This means that notebooks can become powerful teaching tools, either by providing pre-made documents with live code and explanatory text or by allowing users to play with and then develop code. Computational notebooks also lower the entry point for interacting with code enabling them to become valuable tools for introducing new learners to programming concepts.

If you are interested in how notebooks can be used you can also visit the Gallery of Interesting Jupyter notebooks on Github