GTN community paper 2020

Now published! https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010752

Paper itself

It is available on Overleaf, changes should be made there (for now at least).

Requirements

• latexmk

Usage

• Build the paper locally

$ make build-paper

• Clean up (i.e. remove) all nonessential files, except dvi, ps and pdf files:

$ make clean-paper

Generation of graphs for the paper

4 Jupyter Notebooks have been used to generate the graphs for the paper:

• One to extract the details about the current resources in the Galaxy Training Material and some statistics
• One to analyze the results of embeded feedback forms at the end of tutorials
• One to extract and plot the TIaaS stats
• One to analyze the Google Analytics stats of Galaxy Training Material website

Requirements

• Install conda

  $ make install-conda
  

• Create the conda environment

  $ make create-env
  

• Generate a Personal access token on GitHub (Settings - Developer settings - Personal access token ) and copy it to config.yaml file

Usage

• Launch Jupyter to access the notebooks to generate graphs

  $ make run-jupyter
  

• Go to http://localhost:8888 (a page should open automatically in your browser)

• Open:

  • src/extract_repo_content_stats.ipynb Notebook to extract the details about the current resources in the Galaxy Training Material and some statistics
  • src/analyze_feedback.ipynb Notebook to analyze the results of embeded feedback forms at the end of tutorials
  • src/plot_tiaas_data.ipynb Notebook to extract and plot the TIaaS stats
  • src/analyze_google_analytics.ipynb Notebook to analyze the Google Analytics stats of Galaxy Training Material website