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DataLad course material

⚠️⚠️⚠️ Development on future talks and workshop materials is continued in ⚠️⚠️⚠️

( was set up with a proper and more up-to-date reveal.js backbone that enables more reveal.js features and reliable PDF exports).

Talks and materials for workshops based on the DataLad handbook.

Slides are written with reveal.js and can be found in talks/. PDFs of the slides are in talks/PDFs.

Casts are written with autorunrecord in the book itself. Finished casts can be found in casts/. To find out how to create casts on your own machine, check out the contributing instructions for the book for casts. Casts can be executed using the tool cast_live found in tools/.

Advice for creating presentations

  • clone the repository to your local computer. From the root of the dataset, run git submodule update on relevant submodules. Those will be reveal.js, and, if you want to access all images, pics/artwork Afterwards, you should be able to open the HTML's in a web browser and see them nicely rendered
  • to generate a PDF from your slides, open the HTML of your talk in Chrome or Chromium, and append ?print-pdf to the URL. Afterwards, you should be able to print to PDF from your browser. Alternatively, start an npm server and use decktape to generate it from HTML to PDF using docker run --rm -t --net=host -v `pwd`:/slides astefanutti/decktape http://localhost:8000 slides.pdf -s 1024x768
  • The tool directpoll works fantastic for virtual talks. See #34 for info on how to use it
  • We have made good experiences with live code demonstrations. The tools/cast_live script is used for this. It is highly advised to test whether this script works on your set-up beforehand! You can write custom casts if you want to. Everything thats within a run '<code here>' statement is executed on Enter, everything within a say '<note>' is written to your private terminal as a note.


CC-BY-SA: You are free to

  • share - copy and redistribute the material in any medium or format
  • adapt - remix, transform, and build upon the material for any purpose, even commercially

under the following terms:

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.


Talks and materials for workshops based on the DataLad handbook







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