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Mapping crime data in R: An Introduction to GIS and spatial data

7 Jun 2022 11:00 am - 12:30 pm
Online
Training
Crime
Data skills
Workshop

Do you want to display crime data on maps but don’t know how? Crime data often contains spatial components. As a result, analyses of crime data can create patterns that are clearly linked to geography. Naturally, putting the data or analysis on a map makes a lot of sense. Unfortunately, if you have never matched statistical data to spatial data then you may not know how easy it can be to make beautiful data maps! That’s where this workshop comes in!

This is the first of two free Mapping crime data in R workshops. This session will cover some fundamental theories and concepts surrounding GIS and spatial data. The second will be a live code demonstration using R to explore these concepts.

The aim of these workshops are to teach participants to use the R statistical and graphical environment to map open-source police recorded crime statistics onto geographic representations.

More specifically, we will:

  • use R packages such as ggplot, sf and tmaps,
  • briefly explore open-source crime data using Surrey as an example,
  • introduce how to download, import and use spatial data in the form of shapefiles,
  • demonstrate how to join crime data to shapefiles,
  •  introduce classification methods,
  •  use census data to accurately map crime rate.

We will be using Mentimeter to ask questions in this workshop so you may benefit from having a second device ready for this, such as a smartphone.

Presenter: Nadia Kennar, UK Data Service

Event Level: Beginner

Prerequisites: This workshop is suitable for intermediate (or higher) users of R but there is need to have experience with GIS software or spatial data. Users should be comfortable with how to set the working directory in R, how to read in data, how to write basic R functions and how to save scripts and output files. R and Rstudio must be already installed.

Target Audience: Researchers/anyone interested in crime and spatial data