Exploring Graph Data Models for Timetabling Insights

A proof-of-concept data engineering project

Final Project in support of a Masters in Data Science at UWE Bristol

Overview

This repository contains the final dissertation project for a Master's degree in Data Science. The primary aim of this project is to investigate the viability of using graph data structures for enhanced timetabling analytics and reporting.

Objectives include:

1. Designing an extensible, system-agnostic graph data model for university timetables
2. Developing a configurable ETL (extract, transform, load) pipeline to transition from relational to graph database representations of timetables
3. Discussing how graph-based approaches to timetabling analysis could contribute to measuring and improving timetable quality.

How to View the Project

The easiest way to view the project is via Github pages -> https://zoonalink.github.io/graph-tt-quarto/

The webpage report can be viewed by opening index.html file in your web browser.

You can also download and view the pdf or docx files using appropriate software.

Contents

• root folder: This directory includes the Quarto (.qmd) files used to generate the reports, along with any supporting files citations.

• _output: This directory contains the rendered versions of the dissertation report in various formats:

  • _output\html\index.html: HTML version of the report - open index.html
  • _output\pdf\Graphing-University-Timetables.pdf: PDF version of the report. Avoid - not well formatted.
  • _output\word\Graphing-University-Timetables.docx: Word document version of the report.

Note: The Quarto files may contain code snippets, but they are not intended to be executable. The repository does not include any raw data or scripts for running the analysis.

Disclaimer

This repository is intended for informational purposes only and showcases the final output of the dissertation project. The code snippets within the Quarto files are provided for reference and understanding the analysis process.

No sensitive or confidential data is included in this repository.

Contact

For any questions or further information, please email me

Additional Points to Consider:

• The appendices contain all of the prototype code.

• License: This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

  • To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/

• Acknowledgements

• Future Work: This project is very much a proof-of-concept and may be further developed.