This is a GitHub Repository (repo for short) that supports teaching of the Transport Data Science module at the University of Leeds. The module can be taken by students on the Data Science and Analytics and (from 2022 onwards) Transport Planning and the Environment MSc courses.
The module catalogue can be found at
catalogue.md.
The computer code accompanying the course can be found in the code
folders. To run this code you will need R and Python installed plus
various packages and libraries.
The timetable can be found:
- On the University’s system (official): http://timetable.leeds.ac.uk/
- In ical format (for import into Google/Outlook/other Calendar systems): https://github.com/ITSLeeds/TDS/raw/master/timetable-2020.ics
- As a .csv file (for easy reading as data): https://github.com/ITSLeeds/TDS/blob/master/timetable-2020.csv
See below for the sessions
The module timetable is shown in the table below.
| Summary | Description | Dtstart | Location | Duration |
|---|---|---|---|---|
| TDS deadline 1 | Computer set-up | 2021-01-29 13:00:00 | Online - Teams | 240 mins |
| TDS Lecture 1: intro | Introduction to transport data science in Online - Teams | 2021-02-01 09:00:00 | Online - Teams | 60 mins |
| TDS Practical 1: structure | The structure of transport data in Online - Teams | 2021-02-04 14:00:00 | Online - Teams | 150 mins |
| TDS Lecture 2: structure | The structure of transport data and data cleaning in Online - Teams | 2021-02-08 09:00:00 | Online - Teams | 60 mins |
| TDS Practical 2: getting | Getting transport data in Online - Teams | 2021-02-11 14:00:00 | Online - Teams | 150 mins |
| TDS Lecture 3: routing | Routing in Online - Teams | 2021-02-15 09:00:00 | Online - Teams | 60 mins |
| TDS seminar 1 | Mapping large datasets | 2021-02-18 14:00:00 | Online - Teams | 150 mins |
| TDS deadline 2 | Practical: visualising transport data | 2021-02-19 13:00:00 | Online - Teams | 150 mins |
| TDS Practical 3: routing | Routing in Online - Teams | 2021-02-25 14:00:00 | Online - Teams | 150 mins |
| TDS seminar 2 | Data science in transport planning | 2021-03-04 14:00:00 | Online - Teams | 150 mins |
| TDS Lecture 4: viz | Visualisation in Online - Teams | 2021-03-15 09:00:00 | Online - Teams | 60 mins |
| TDS Practical 4: modelling | Modelling in Online - Teams | 2021-03-18 14:00:00 | Online - Teams | 150 mins |
| TDS Lecture 5: project | Project work in Online - Teams | 2021-03-22 09:00:00 | Online - Teams | 60 mins |
| TDS deadline 3 | Draft portfolio | 2021-03-26 13:00:00 | Online - Teams | 60 mins |
| TDS Practical 5: project | Project work in Online - Teams | 2021-04-29 14:00:00 | Online - Teams | 150 mins |
| TDS deadline 4 | Deadline: coursework, 2pm | 2021-05-14 13:00:00 | Online - Teams | 60 mins |
For this module you need to have up-to-date versions of R and RStudio. Install:
- R from cran.r-project.org
- RStudio from rstudio.com
- R packages, by opening RStudio and typing
install.packages("stats19")in the R console.
We recommend using at least the latest stable release of R (4.0.0 or above). We recommend running R on a decent computer, with at least 4 GB RAM and ideally 8 GB or more RAM. See Section 1.5 of the online guide Reproducible Road Safety Research with R for instructions on how to install key packages we will use in the module.[1]
Slides can be found online:
- See https://itsleeds.github.io/TDS/slides/1-intro.html#1 for the introductory slides, for example
- Videos of the lectures can be found on the University of Leeds’ Blackboard system (you must must register to courses such as Data Science and Analytics or Transport Planning and the Environment to take the course)
- You will build-up a portfolio of work
- 100% coursework assessed, you will submit by Friday 14th May:
- a pdf document up to 10 pages long with figures, tables, references explaining how you used data science to research a transport problem
- reproducible code contained in an RMarkdown (.Rmd) document that produced the report
- Written in RMarkdown - will be graded for reproducibility
- Code chunks and figures are encouraged
- You will submit a non-assessed 2 page pdf + Rmd report by Friday 26th March
Any feedback or contributions to this repo are welcome. If you have a question please open an issue here (you’ll need a GitHub account): https://github.com/ITSLeeds/TDS/issues
[1] For further guidance on setting-up your computer to run R and RStudio for spatial data, see these links, we recommend Chapter 2 of Geocomputation with R (the Prerequisites section contains links for installing spatial software on Mac, Linux and Windows): https://geocompr.robinlovelace.net/spatial-class.html and Chapter 2 of the online book Efficient R Programming, particularly sections 2.3 and 2.5, for details on R installation and set-up and the project management section.