This repository aims to introduce the idea of Jupyter notebooks in the context of open and reproducible research. Originally these notebooks were developed as workshop for the integrated research training group at the CRC 1270 ELAINE (https://www.elaine.uni-rostock.de), later enhanced for the theme day 'Research Data Management' at the University of Greifswald and the graduate academy of the University of Rostock.

This work is if not otherwise stated licensed under a Creative Commons Attribution 4.0 International License. See the section below for third party contents and the corresponding licenses.

Please use the Zenodo reference:

In order to reference the GitHub repository, please attribute this as:

Max Schröder and Frank Krüger. “Jupyter Workshop,” https://github.com/m6121/Jupyter-Workshop

This repository contains parts of other publications of open source software and data listed below:

1. The data in this repository in the _data folder has been converted from the ARFF files of the following publication of IMU data (CC-BY 4.0): Frank Krüger, Albert Hein, Kristina Yordanova and Thomas Kirste Recognising user actions during cooking task (Cooking task dataset) – IMU Data Rostock : Universität Rostock , 2017 https://doi.org/10.18453/rosdok_id00000154
2. The two Jupyter notebooks 02 Python Introduction.ipynb and 02 Python Introduction (Solutions).ipynb are based on the repositories of: https://github.com/stefanluedtke/NLP-Exercises (MIT License) and https://github.com/spatialaudio/selected-topics-in-audio-signal-processing-exercises (CC0 1.0)

This workshop material can be used for self-studies as well as for interactive workshops. Notebooks are aimed to be worked through according to their numbering in the file name starting with 01 Introduction to Jupyter Notebooks.ipynb.

If you are using this material, make sure to check the License section.

Despite the possibility to install Jupyter on your local computer e.g. by employing Anaconda, you also use Docker images. In the following, we will describe the use of such an image: jupyter/scipy-notebook:latest For further information on the available images consult the corresponding documentation at https://jupyter-docker-stacks.readthedocs.io/en/latest/

$ docker run --rm \
    --name=jupyter-workshop \
    -p 127.0.0.1:8888:8888 \
    -v "$PWD":/home/jovyan/work \
    --user root \
    -e NB_UID=$(id -u) \
    -e NB_GID=$(id -g) \
    jupyter/scipy-notebook:latest

The parameters are used to configure the following aspects:

• --rm: remove the container after stopping,
• --name=jupyter-workshop: the container is named jupyter-workshop,
• -p 127.0.0.1:8888:8888: bind container port 8888 (3rd part) to the host ip address 127.0.0.1 at port 8888 (2nd part),
• -v "$PWD":/home/jovyan/work: connect the current directory $PWD to the container at /home/jovyan/work,
• --user root: needed to set the UID and GID of the user running inside the container in order to keep local permissions,
• -e NB_UID=$(id -u) and -e NB_GID=$(id -g): to actually set the user and group ID to the same as on the host. This ensures write access to the volume mounted by -v.