Welcome to the Cycling Potential Hackathon, Lisbon (CPHL), on
reproducible methods for estimating cycling potential, based on a case
study of Lisbon, Portugal.
This GitHub repo
contains everything needed to get started with modelling cycling
potential, including example data and reproducible code.
Interested in getting involved? Here’s some key information that will help decide if this is for you and register to participate if so!
The hackathon is organised by Rosa Felix of the University of Lisbon and Robin Lovelace of the University of Leeds, who were awarded funding from the Portuguese Association of Researchers and Students in the United Kingdom’s Bilateral Research Fund (PARSUK BRF) to develop a ‘PCT Portugal’ project building on methods used to develop the Propensity to Cycle Tool (PCT), which is based on open source software.
Attendees are expected to have knowledge of transport planning interventions to enable cycling uptake and/or technical skills needed to analyse, interactively visualise and develop scenarios of cycling uptake. Experience with the statistical programming language R will be particularly useful, although anyone with experience of front-end or back-end development with open source software will be very welcome. Working knowledge of GitHub is highly recommended for collaboration during the hackathon. Here is a tutorial example to get familiarized with GitHub.
A one day participatory code-focussed hackathon. The morning will be dedicated to getting up-to-speed with the input data. The afternoon will be dedicated to the hackathon!
Friday 25th September, 2020, 10:00 to 16:00 (London/Lisbon time, UTC+1).
See Ical file here.
Online, we will send a conference link to participants.
There is a great need for transparent and actionable evidence to support investment in sustainable transport futures, and cycling uptake in particular.
Please take a read of the information below and take a look at (and ideal test) the following resources:
If you plan to use R to develop solutions, please ensure you can reproduce the results of the code shown here: reproducible-example.R. If your output looks like this congratualtions :tada:🎉 you have the necessary packages installed.
Lunch break and finalising teams 12:00 to 13:00
Initial datasets, .geojson
We have developed ideas for a few hack topics:
Any further ideas very welcome, feel free to bring your own!
To sign-up complete this application form.
Feel free to ask any questions related to this hackathon on the issue tracker.
Please note that the cyclingpotential-hack project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.