The branches in this repository create pre-configured containers that demonstrate a range of subject specific notebooks capable of generating media rich content from scratch.
The notebooks are a bit dated and some of the packages may have rotted. More recent notebooks can be found at https://gettingstarted-ousefulinfo.notebooks.azure.com . I need to map those back over here to run a single repo that can generate binderhub builds and run notebooks on both Binderhub and in Azure notebooks.
The notebooks contained in this branch demonstrate how notebooks can be used for simple content authoring.
(Demonstrations of how to create rich generated content appropriate to particular topic areas are provided in the repository branches.)
The notebooks should be treated as generative documents that contain instructions for generating the media assets that are included within them. Generative documents can be executed to produce static or interactive generated documents that contain rendered assets or interactives (such as interactive maps).
The phrase (
computational narrative](https://blog.jupyter.org/project-jupyter-computational-narratives-as-the-engine-of-collaborative-data-science-2b5fb94c3c58) is often used to describe the style of document that can be written using computational notebooks. Stephen Wolfram has also used the phrase computational essay to describe similar sorts of document: "A computational essay is in effect an intellectual story told through a collaboration between a human author and a computer. ... There are basically three kinds of things here. First, ordinary text (here in English). Second, computer input. And third, computer output. And the crucial point is that these three kinds of these all work together to express what’s being communicated."
Media assets include, but are not limited to, scientific diagrams and charts, audio files, static and interactive maps and musical notation.
The notebooks show how to create rich content containing interactive and/or dynamically generated, embedded content assets within a Jupyter notebook using standard Python packages.
The containers can be launched via beta.mybinder.org
Drawing on ideas of generative music (music that is ever changing and created in a systematic way) and reproducible research (in which self-contained documents blend text, computational scripts, and assets generated by those computational scripts), generative documents are viewed as documents that blend text content with rich media assets generated from scripts included within the document.
Generative documents support document maintenance through the tight integration of parameterised content and media assets. The generation of media assets supports the automated creation of scientifically accurate charts and diagrams in a reproducible way.
Generative documents can be used to support the creation of maintainable academic and educational texts. They also may texts open-ended, in the sense that parameter values can be changed in one place and the document reflowed, with the textual content and media assets that complement it being generated afresh to reflect changed parameter values.
Topic Specific Examples
The branches of this repository contain environment configurations and demonstation noteooks that are intended to provide worked examples of rich content in particular topic areas.
Examples in the branches are still in an early state of preparation. Some of the notebook extensions that help render rich components may be in a state of disrepair or interact badly with each other. At this stage, the idea is to try to get across an idea of what is possible, and view bugs and issues as things that can be quickly and easily fixed (hopefully!), rather than as blockers.
Current branches include:
(Items nearer the top of list are in a better state than ones lower down the list, which may even be empty or completely broken stubs.)