Geographic Data Science course

A course created by Dani Arribas-Bel Senior Lecturer in Geographic Data Science at the University of Liverpool .

Statement of need

Data Science (Donoho, 2017) has become one of the most demanded skills thanks to an explosion in the availability of data (Kitchin, 2014). Most of these new sources are, directly or indirectly, geographic in that they can be related to a particular location on a map. However, the vast majority of data science resources available currently ignore the spatial dimension of data, particularly when it comes to the more analytic set of methods covered.

At the same time, traditional resources for teaching the handling, visualisation, and analysis of geographic data are based on a paradigm that emphasises graphical interfaces and “point-and-click” software packages. This approach, although valid, limits the flexibility with which the analyst can effectively move from data to insights, and is more difficult to connect with and benefit from modern advances in both data tools and workflows.

This paper presents a pedagogical bridge between the “spatially unaware” set of practices emerging from Data Science, and more traditional resources designed to teach spatial analysis within a Geographic Information Systems (GIS) environment.

Aims

  • The module provides students with little or no prior knowledge core competences in Geographic Data Science (GDS). This includes the following:
  • Advancing their statistical and numerical literacy.
  • Introducing basic principles of programming and state-of-the-art computational tools for GDS.
  • Presenting a comprehensive overview of the main methodologies available to the Geographic Data Scientist, as well as their intuition as to how and when they can be applied.
  • Focusing on real world applications of these techniques in a geographical and applied context.

Learning outcomes

  • By the end of the course, students will be able to:
  • Demonstrate advanced GIS/GDS concepts and be able to use the tools programmatically to import, manipulate and analyse spatial data in different formats.
  • Understand the motivation and inner workings of the main methodological approcahes of GDS, both analytical and visual.
  • Critically evaluate the suitability of a specific technique, what it can offer and how it can help answer questions of interest.
  • Apply a number of spatial analysis techniques and explain how to interpret the results, in a process of turning data into information.
  • When faced with a new data-set, work independently using GIS/GDS tools programmatically to extract valuable insight.
License
Please see above or at the resource's page regarding the license.
Created by Cyrille Médard de Chardon
on 2024-05-26