Open_Computing_Lab (OCL)

The Open Computing Lab (OCL) approach is being trialled on several Open University modules and aims to provide a common approach to delivering complex software and computing environments on personal computers as well as via remotely hosted online servers.

The motivating idea for the Open Computing Lab approach is the provision of module specific computational environments capable of being run locally by students, on OU hosted onlines servers, and on remote third party servers, using a standardised approach.

The OCL approach is based on the use of:

  • Docker containers, for providing a way of packaging and distributing arbitrary computational envirionments running arbitrary applications; these might include:

    • applications with a native browser based user interface;

    • remote desktop applications (currently limited to Linux desktop; Microsoft Windows applications run under Wine);

  • Jupyter services for providing single and multi-user access to browser accessed applications and environments.

To install the environment, use the installation instructions that are provided for students.

RoboLab is an example of an Open Computing Lab (OCL) environment configured specifically to support your TM129 activities (example).

Design Principles

One important thing to note about the design of the Open Computing lab environments is that a single environment is designed, and then automation tools generate different instances of the environment for use in different locatins (on a student’s own computer, via an OU hosted service, etc.) This guarantees that students see the same environment configuration wherever they access it from.

Accessing Open Computer Lab Environments

There are several ways in which you can access an OCL environment:

  • as a “temporary” online service using MyBinder

  • via the OU hosted JupyterHub environment [if available]

  • locally on your own computer

  • remotely accessed from your own server over your home network TO DO

  • using your own remote host

The current recommended approach is download Docker to your own computer and launch the environment from the command line.