Course description
Transport Data Science with R
This course teaches two skill-sets that are fundamental in modern transport research: programming and data analytics. Combining these enables powerful transport planning and analysis workflows for tackling a wide range of problems, including:
- How to find, download and import a range of transport datasets?
- How to develop automated and reproducible transport planning workflows?
- How can increasingly available datasets on air quality, traffic and active travel be used to inform policy?
- How to visualise results in an attractive and potentially on-line and interactive manner?
This course will provide tools, code, data and, above all, face-to-face teaching to answer these questions and more, with the statistical programming language R. The data science approach opens a world of possibilities for generating insight from your transport datasets. The course is suitable for researchers in the public sector, academia and industry.
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Upcoming start dates
Suitability - Who should attend?
Who should attend?
Prior experience with transport datasets is a prerequisite for the course. Attendees are expected to:
- Be comfortable with the use of R, using it for everyday data analysis tasks (you will find DataCamp’s free Introduction to R easy)
- Have experience with transport datasets and understand their structure (you will be familiar with the contents of the Transport chapter in Geocomputation with R)
Participants are expected to brush-up on their knowledge before the course, for example by completing the exercises linked-to in the bullet points above.
Outcome / Qualification etc.
By the end of the course you will be able to:
- Find, download and import a variety of transport datasets, including from OpenStreetMap and government data portals
- Work with, analyse and model transport data with spatial, temporal and demographic attributes
- Work with air polution data in R and compare with transport behaviours
- Generate and analyse route networks for transport planning with reference to:
- Origin-destination (OD) data
- Geographic desire lines
- Route allocation using different routing services
- Route network generation and analysis
Training Course Content
Finding, downloading, importing transport data
- An overview of data portals
- Origin-destination data
- OpenStreetMap data
- Other data sources
Working with spatio-temporal data
- Introduction to STATS19
- Temporal analysis
- Spatial analysis
- Analysis and modelling
Traffic data and pollution analysis with R
- An introduction to the openair package
- Traffic count data
- Meteorological data
- Air pollution data: daily, weekly and seasonal variability
- Visualising air pollution data and next steps
From desire lines to route networks
- Handling OD data
- Creating ‘desire lines’ from OD and zone data
- Route allocation and route network creation
- Route network analysis (comparing with other datasets)
- Discussion and applying the methods to your data
Expenses
Please contact the university for more information regarding tuition fees for this program.