CASA’s Urban Spatial Science Platform

Author

Jon Reades

Published

September 7, 2023

In order to get you started on your spatial and data science ‘journey’ you will need to follow the guidance provided on the pages we’ve linked to below. These are divided into three sections:

Requirements

Before trying to do anything else you should review the ‘requirements’. As part of that, you’ll need to complete the basic health check, which also includes our recommendations if you are considering buying a new computer when you start your studies. Once you know that your machine and operating system are up-to-date, you should install the basic utilities that will enable you to complete installation of the programming environment. We also provide information about Code Camp which is a self-paced introduction to the fundamentals of programming in Python.

Setup

Installing the computing environment entails thinking not just about how you run code, but also how you manage it and document it. In fact, it’s possible to run code without installing anything at all, but by signing up for, installing, or configuring these services now you know that you are ready to roll!

Soft-Skills

It might seem strange to have a section on soft-skills as part of our ‘preparing to run the Urban Spatial Science platform web site, but MSc programmes are a ’step up’ in terms of independent study, and so knowing how to read, how to think, how to ask for help and how to study effectively is almost as important as being able to run the code. Almost. Moreover, the skills we discuss here aren’t specific to any one module so we’ve put them here as part of your orientation.

To Dos

None outstanding.

Citing

@software{uss:2024,
  author = {Reades, Jon},
  title = {\texttt{sds_env}: A containerised platform for Urban Spatial Science},
  url = {https://github.com/jreades/sds_env/},
  version = {2023},
  date = {2023-10-01},
}

This draws heavily on Dani Arribas-Bel’s work for Liverpool.

DOI

DOI
@software{hadoop,
  author = {{Dani Arribas-Bel}},
  title = {\texttt{gds_env}: A containerised platform for Geographic Data Science},
  url = {https://github.com/darribas/gds_env},
  version = {3.0},
  date = {2019-08-06},
}