Crime Analysis  ·  Dashboard 2024

Ottawa: Bike Theft Analysis

An interactive Tableau dashboard visualising bike theft patterns across Ottawa — pinpointing high-risk neighbourhoods, peak theft seasons, and trends that cyclists and policymakers need to know.

Tableau Geospatial Crime Analysis Dashboard
Ottawa Bike Theft Dashboard

Overview

Cycling has grown significantly in Ottawa, but so has bike theft. Without a clear picture of where and when thefts happen, both riders and city planners are left guessing on prevention strategies.

This project visualises Ottawa's bike theft incident data in an interactive Tableau dashboard — giving users an at-a-glance view of theft concentrations, seasonal patterns, and neighbourhood risk levels.

Key Insights

  • Neighbourhood Hotspots: A small number of neighbourhoods — particularly around the University of Ottawa campus, the ByWard Market, and Centretown — accounted for a disproportionate share of total thefts, consistent with high foot traffic and dense bike parking areas.
  • Seasonal Surge: Theft incidents spiked sharply in the summer months (May–August), aligning with peak cycling season and longer daylight hours that increase bike usage and exposure.
  • Time of Day: Daytime thefts during business hours were most common, suggesting opportunistic theft from unlocked or poorly secured bikes left at commercial and transit hubs.

Dashboard Features

01

Geographic Map View

An interactive map plots theft incidents across Ottawa wards, with colour coding by incident density to identify hotspot zones at a glance.

02

Temporal Trend Charts

Monthly and yearly trend lines show how theft volumes have changed over time, with seasonal peaks and year-over-year comparisons clearly visualised.

03

Neighbourhood Breakdown

A ranked bar chart breaks down incidents by neighbourhood, allowing users to compare risk levels across the city and identify areas needing targeted intervention.

Explore the Dashboard

Interact with the full Tableau dashboard to explore the data by neighbourhood, time period, and theft type.