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Instructions, exercises and example data sets for Annif hands-on tutorial
Makefile Python
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Annif tutorial

Presentations, exercises and example data sets for Annif hands-on tutorial.

The tutorial was initially organized at SWIB19 but the materials are also made more widely available for self-study.


You will need a computer with sufficient resources (at least 8GB RAM) to be able to install Annif and complete the exercises.

Note also that it might be convenient to have either Docker or VirtualBox installed beforehand. Note that when using Docker desktop (Windows), you might want to increase the available memory for it to 8GB under Settings -> Advanced.

Getting the tutorial materials

To complete this tutorial, you will need a local copy of the materials, especially the data sets (unless you use the pre-built VirtualBox VM, which includes them). The easiest way to get them is to either clone this repository or download it as a zip archive from GitHub (click the green "Clone or download" button).

When you have the files locally, you also need to download the example full text documents for either or both data sets. The downloads are automated using make - see the README files for both data sets (yso-nlf, stw-zbw) for details.


The tutorial material was created by:

  • Osma Suominen, National Library of Finland
  • Mona Lehtinen, National Library of Finland
  • Juho Inkinen, National Library of Finland
  • Anna Kasprzik, ZBW - Leibniz Information Centre for Economics
  • Moritz Fürneisen, ZBW - Leibniz Information Centre for Economics


The materials created for this tutorial (presentations and exercises) are licensed under a Creative Commons Attribution 4.0 International License.

CC BY 4.0

The data sets were collected from other sources and have their own licensing; see each individual data set for details.

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