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# FAIRNB
A Repository for FAIR data handling in Jupyter Notebooks.
It shows the usage of the DBRepo and Invenio platforms to create a genre prediction SVM and make its results reproducible.
## Installation
Install poetry via pip or conda and run
> poetry install
Following packages are additionally needed: git-lfs, libsnfile1 (needed for librosa).
Install them with your package manager.
To authenticate with the DBRepo and Invenio servers, rename example-config_<platform>.yml located in the config folder
to config_<platform>.yml and enter your credentials in the placeholders. Credentials are not needed for runs done fully locally.
The main notebook is located in notebooks/main.ipynb. It executes the full workflow of the project.
Alternatively, notebooks/standalone.ipynb also contains the full workflow.
A docker image is also provided for download on invenio, containing a running jupyter instance with all dependencies installed.
Beware this docker image does not have a config file included and will not be able to authenticate with
the DBRepo and Invenio servers.
Therefore, if one wants to execute the notebooks locally, only_local must be set to true in the execute method.
The project has been done in the context of a bachelor thesis, extensions are not planned for now.
| Name | Identifier |
|-----------------------|--------------------------------------------------------------------------------------------|
| Docker Image on TUWRD | [](https://doi.org/10.48436/f0kah-nnc65)|
| DBRepo Database | [https://dbrepo1.ec.tuwien.ac.at/pid/34](https://dbrepo1.ec.tuwien.ac.at/pid/34) |
| TUgitLab | https://gitlab.tuwien.ac.at/martin.weise/fairnb |
| Thesis | [](https://doi.org/10.5281/zenodo.10679965)