Project Aims and Scope

The primary aim of this project is to investigate the viability of using graph data structures for enhanced timetabling analytics and reporting.

Objectives


  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.

To achieve these objectives, I implement and evaluate a set of proof-of-concept analytical metrics which leverage the graph data model whilst discussing performance capabilities (and limitations) against traditional relational approaches.

It is important to note that this project is positioned as a proof-of-concept and exploratory study.

I will not:

  • reinvent a full-scale timetabling system
  • attempt to optimise real-time timetable generation

I will:

  • focus on the data engineering aspects of transitioning from relational to graph data models
  • demonstrate the potential of graph-based approaches in the analysis of university timetables
  • provide a foundation for future analytical work.

Let’s graph!

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: A randomly generated graph for illustrative purposes.

See Appendix for graph generator code