Overview

This project illustrates the potential of using freely available open data for insightful analysis. By harnessing information from the New Zealand Police and Statistics New Zealand, we incorporate geographic context into crime statistics in a meaningful way.

The app combines interactive maps and detailed charts to present suburb crime statistics in New Zealand, offering clear insights and identifying trends. Originating from our founder’s personal interest in the increasing concerns over crime and gun violence, the project has developed into a comprehensive dashboard. It enables users to explore statistics in their local areas, providing them with the information needed to understand the issues that are most relevant to them.

Dashboards are an exceptionally powerful tool for developing insight about a problem. Data is often available, but stored in such an unhelpful way that to an end user it is meaningless. This project shows what can be done with a few simple tools, making data interactive and accessible to anyone.

Technical Details

We have utilised three core technologies in this project to create an efficient and user-friendly experience. At the heart of our dashboard’s operation though is FME, which automates the retrieval, analysis and publishing of our data. We incorporate freely available data stored in CSV format with the New Zealand Police, and WFS with Statistics New Zealand. FME ensures that this data is frequently retrieved and that our dashboard remains up to date without any need for manual intervention from our team.

For the front-end, we make use of Mapbox in tandem with CS Javascript, crafting an interactive interface where maps and charts are elegantly intertwined. The use of Mapbox Vector Tilesets is pivotal in delivering top-notch performance to our end-users, enabling swift and smooth data visualisation.

While we typically try and use GeoJSON local to the application, in this case due to the volume of data, Vector Tilesets are the ideal solution. C3 JS is an open-source chart library based on the powerful D3, known for it’s excellent data visualisations.