Towards_Modelling_Organisational_Routines

Source code and data for the paper "Towards Modelling and Simulation of Organisational Routines".

Setup

Python requirements can be found in requirements.txt.

To run the data extraction, you will need a GitHub access token.

Usage

There are three Jupyter notebooks:

• notebooks/01-Data_Extraction.ipynb : Loads data from the GitHub REST API. (note: data can already be found in data/data.xlsx).

• notebooks/02-Data_Analysis.ipynb : Loads data/data.xlsx and applies some pre-processing before loading into routines data model objects. It then extracts recurrent action patterns and builds a summary statistics table about the patterns to data/summary.xlsx. Finally, a state transition matrix is calculated and output to data/transition_matrix.xlsx.

• notebooks/03-Plot_Figures.ipynb : Renders the routines data model class diagram from a PlantUML description in figures/routines_model.txt as an image output to figures/routines_model.png (Fig. 1), then loads data/summary.xlsx and data/transition_matrix.xlsx to generate respective LaTeX tables (Tables 4 and 5). The transition matrix is then used to plot a visualisation of the Markov chain that is output to figures/markov_chain_plot.pdf (Fig. 2).