CRIME (Crime Resource Interface Management Engine)

Team Name

HACKSAW

Team Members

Project Description

The hack will take Queensland Police Service (QPS) offences data specific to Queensland Local Government Areas (LGAs) and combine it with Australian Census data to identify crime hotspots and emerging trends. The filtering of this data aims to provide a graphical user interface that will:

• Identify crime 'hot spots' to allow efficient QPS resource allocation

• Make clear to local governments the emerging crime trends in their area for budgeting considerations

• Indicate key areas which require better public education and warnings (e.g., the need for better drug awareness)

• Allow local police to focus on issues in their jurisdiction

• Allow the local community to see the issues which affect them and the progress that QPS are making in different areas

Data Story

1. The task needed to intertwine ABS census data sets & Queensland crime data from the QLD Gov Open Data portal to evaluate trends across districts.

2. For the data-set “LGA Reported Offences Numbers”, the 89 individual crimes were filtered into 11 main categories:
   i. Violent Offences
   ii. Sexual Offences
   iii. Other Personal Offences
   iv. Robbery and Theft
   v. Property Offences
   vi. Drugs and Alcohol
   vii. Prostitution
   viii. Weapons Offences
   ix. Fraud
   x. Driver Offences
   xi. Other Minor Offences

3. The monthly crime data was then surmised by year

4. Using R and the GGPLOT Library, a map of Queensland was generated and overlayed with the LGA spatial boundaries to form the foundation of a Choropleth Map.

5. From here an R script was created to fill the map with the appropriate data required by the user:
   i. Crime Category (listed above)
   ii. Form of Data (per Capita or Total Number)
   iii. Year (any selection from 2001 to 2022)

6. The following census data-sets were acquired:
   i. 2021 LGA Populations
   ii. 2011 and 2016 WPP (Working Population Profile)
   iii. 2011 and 2016 PEP (Place of Enumeration Profile)

7. This data was used to find unemployment rates for each LGA and to convert the per-capita crime rate to a total number per LGA as needed.

8. Using R, a ‘Shiny’ App was created to output the data based on customised user inputs in the following two navigation pages:
   i. QLD State-wide Overview (to display the previously mentioned Queensland maps)
   ii. Local Government Area (to plot the results for an individual LGA along with a trendline which could then be compared to the unemployment data to find any correlations)