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Access public safety and security data for Montréal: criminal incidents, emergency service interventions (fire, police), 311 citizen requests, traffic collisions, fire stations, police stations, coyote sightings, and fire hydrant locations. / Accéder aux données de sécurité publique de Montréal : incidents criminels, interventions des services d'urgence (incendies, police), demandes 311, collisions routières, casernes de pompiers, postes de police, signalements de coyotes et emplacements des bornes fontaines.

alistaircroll By alistaircroll schedule Updated 3/13/2026
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name: safety description: | Access public safety and security data for Montréal: criminal incidents, emergency service interventions (fire, police), 311 citizen requests, traffic collisions, fire stations, police stations, coyote sightings, and fire hydrant locations. / Accéder aux données de sécurité publique de Montréal : incidents criminels, interventions des services d'urgence (incendies, police), demandes 311, collisions routières, casernes de pompiers, postes de police, signalements de coyotes et emplacements des bornes fontaines. triggers: - crime, criminal, police, fire, emergency, 911, collision, accident, safety, security, coyote - crime, criminalité, police, incendie, urgence, collision, accident, sécurité, coyote

Public Safety Data / Données de sécurité publique

Available Datasets / Jeux de données disponibles

Dataset Slug Format Update Frequency Records (approx)
Criminal acts actes-criminels CSV (DataStore) Daily 500K+
311 Service requests requete-311 CSV (DataStore) Real-time 1M+
Road collisions collisions-routieres CSV (DataStore) Daily 100K+
Fire department interventions interventions-service-securite-incendie-montreal CSV (DataStore) Daily 500K+
Fire stations casernes-pompiers CSV + GeoJSON Static 42 stations
Police stations carte-postes-quartier GeoJSON Static 42 stations
Police district boundaries limites-pdq-spvm GeoJSON Static 42 districts
Coyote sightings signalements-de-coyotes CSV (DataStore) Real-time 5K+
Fire hydrants geolocalisation-des-bornes-fontaines CSV + GeoJSON Monthly 8K+

1. Criminal Acts / Actes criminels

Slug: actes-criminels Coverage: All incidents reported to SPVM (Service de police de la Ville de Montréal) Records: 500,000+ since ~2010

Key Fields

Field Type Notes
DATE datetime Date/time of incident
CATEGORIE text Major crime category (FR)
SOUS_CATEGORIE text Crime subcategory (FR)
X float NAD 83 MTM Zone 8 coordinate
Y float NAD 83 MTM Zone 8 coordinate
Latitude float WGS84 latitude
Longitude float WGS84 longitude
QUARTIER text Neighborhood name (FR)

Common Queries

# Count crimes by category (last year)
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"CATEGORIE",COUNT(*)+as+total+FROM+"RESOURCE_UUID"+WHERE+"DATE">%272025-01-01%27+GROUP+BY+"CATEGORIE"+ORDER+BY+total+DESC'

# Crimes near a location
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"DATE","CATEGORIE","SOUS_CATEGORIE","Latitude","Longitude"+FROM+"RESOURCE_UUID"+WHERE+("Latitude"-45.5171)^2+("Longitude"-(-73.5629))^2<0.001+LIMIT+100'

# Crimes by neighborhood (month)
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"QUARTIER",COUNT(*)+as+total+FROM+"RESOURCE_UUID"+WHERE+DATE_TRUNC(%27month%27,"DATE")=%272026-03-01%27+GROUP+BY+"QUARTIER"+ORDER+BY+total+DESC'

2. 311 Citizen Service Requests / Demandes de services 311

Slug: requete-311 Coverage: All non-emergency requests to City services (potholes, noise, graffiti, street cleaning, etc.) Records: 1M+ entries

Key Fields

Field Type Notes
RequestID text Unique request ID
CreatedDate datetime Request submission date
Status text Open, Closed, In Progress (EN)
Category text Service category
Description text Citizen description
Latitude float WGS84
Longitude float WGS84
Ward text Borough/Ward (EN)

Common Queries

# Total requests by category
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"Category",COUNT(*)+as+total+FROM+"RESOURCE_UUID"+GROUP+BY+"Category"+ORDER+BY+total+DESC'

# Open requests in a location
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search?resource_id=RESOURCE_UUID&filters={"Status":"Open"}&limit=50'

3. Road Collisions / Collisions routières

Slug: collisions-routieres Coverage: Police-reported traffic collisions (injury, property damage) Records: 100,000+ incidents

Key Fields

Field Type Notes
NO_ACCIDENT text Collision ID
DT_ACCIDENT datetime Date/time of collision
NOM_RUE_1 text First street (FR)
NOM_RUE_2 text Second street (FR)
GRAVITE text Severity: Fatal, Injury, Property damage (FR)
LATITUDE float WGS84
LONGITUDE float WGS84
NB_MORTS int Fatalities
NB_BLESSES_GRAVES int Serious injuries
NB_BLESSES_LEGERS int Minor injuries

Common Queries

# Collisions by severity (current year)
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"GRAVITE",COUNT(*)+as+total+FROM+"RESOURCE_UUID"+WHERE+YEAR("DT_ACCIDENT")=2026+GROUP+BY+"GRAVITE"'

# Fatal collisions
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search?resource_id=RESOURCE_UUID&filters={"GRAVITE":"Décès"}&limit=100'

4. Fire Department Interventions / Interventions du service de sécurité incendie

Slug: interventions-service-securite-incendie-montreal Coverage: All SSIM (Service de sécurité incendie de Montréal) emergency responses Records: 500,000+ calls annually

Key Fields

Field Type Notes
NumIntervention text Intervention ID
DateDebut datetime Response start time
CodeIncident text Incident type code
DescriptionIncident text Description (FR)
Arrondissement text Borough (FR)
Longitude float WGS84
Latitude float WGS84
TempsReaction int Response time (minutes)

Common Queries

# Incidents by type
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"CodeIncident","DescriptionIncident",COUNT(*)+as+total+FROM+"RESOURCE_UUID"+GROUP+BY+"CodeIncident","DescriptionIncident"+ORDER+BY+total+DESC+LIMIT+20'

# Average response time by borough
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"Arrondissement",AVG("TempsReaction")+as+avg_response+FROM+"RESOURCE_UUID"+GROUP+BY+"Arrondissement"+ORDER+BY+avg_response'

5. Fire Stations / Casernes de pompiers

Slug: casernes-pompiers Format: CSV + GeoJSON Coverage: 42 fire stations across Montréal Update: Static (stations don't move frequently)

Key Fields

Field Type Notes
Station_ID text SSIM station code
Nom text Station name (FR)
Adresse text Street address
Telephone text Station phone
Latitude float WGS84
Longitude float WGS84

6. Police Stations / Postes de police

Slug: carte-postes-quartier Format: GeoJSON Coverage: 42 police stations (PDQ = Poste de quartier) Update: Static

Key Fields

Field Type Notes
name text Station name (FR)
address text Street address
phone text Contact number
geometry GeoJSON Point coordinates (WGS84)

7. Police District Boundaries / Limites des PDQ

Slug: limites-pdq-spvm Format: GeoJSON (Polygon) Coverage: 42 district boundaries Use for: Spatial joins with crime data

Key Fields

Field Type Notes
PDQ_Name text District name (e.g., "Centre")
PDQ_Number text District code (e.g., "01")
geometry GeoJSON Polygon boundary (WGS84)

8. Coyote Sightings / Signalements de coyotes

Slug: signalements-de-coyotes Coverage: Public coyote sightings reported to Ville de Montréal Records: 5,000+ sightings (growing dataset)

Key Fields

Field Type Notes
DateSignalement datetime Sighting date
Adresse text Location (street address)
Description text What was observed (FR)
Latitude float WGS84
Longitude float WGS84
Arrondissement text Borough (FR)

Common Queries

# Coyote sightings by borough (last month)
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search_sql?sql=SELECT+"Arrondissement",COUNT(*)+as+total+FROM+"RESOURCE_UUID"+WHERE+"DateSignalement">%272026-02-13%27+GROUP+BY+"Arrondissement"+ORDER+BY+total+DESC'

# Sightings near a location
curl -s 'https://donnees.montreal.ca/api/3/action/datastore_search?resource_id=RESOURCE_UUID&limit=50&sort=DateSignalement+desc'

9. Fire Hydrants / Bornes fontaines

Slug: geolocalisation-des-bornes-fontaines Format: CSV + GeoJSON Coverage: 8,000+ fire hydrants across Montréal Update: Monthly

Key Fields

Field Type Notes
HydrantID text Unique hydrant ID
Adresse text Street location
RuePrincipale text Primary street (FR)
RueSecondaire text Cross street (FR)
Latitude float WGS84
Longitude float WGS84
Arrondissement text Borough (FR)
TypeBorne text Hydrant type (above/below ground)

Common Questions / Questions fréquentes

Question Dataset Query Approach
"How many crimes in [neighborhood] last year?" actes-criminels SQL GROUP BY QUARTIER, DATE range
"What's the most common crime?" actes-criminels SQL GROUP BY CATEGORIE
"How many collisions on [street]?" collisions-routieres SQL filter on street name
"Nearest fire station to my address?" casernes-pompiers Distance calculation (spatial)
"Police station serving my area?" carte-postes-quartier + limites-pdq-spvm Point-in-polygon GeoJSON
"Any 311 requests for potholes?" requete-311 Filter by Category
"Recent coyote sightings?" signalements-de-coyotes Sort by DateSignalement DESC
"Fire hydrant locations for [street]?" geolocalisation-des-bornes-fontaines Filter by street name

Gotchas & Edge Cases / Pièges et cas limites

  1. Coordinate systems: Latitude/Longitude = WGS84 (standard). Some datasets also have X/Y = NAD 83 MTM Zone 8. Always check.

  2. Crime data lag: Criminal acts data is updated daily but may have a 24–48 hour lag.

  3. 311 requests do not have precise categories in all versions. Categories may be abbreviated (e.g., "POT" for pothole). Check the resource schema.

  4. Collision severity field is bilingual. Values: "Décès", "Blessés graves", "Dommages matériels" (FR). Do not hard-code English values.

  5. Fire station phone numbers may change. Always call 911 for emergencies; use phone field for non-emergency queries only.

  6. Coyote sightings are self-reported. Data quality varies; not all sightings are confirmed by wildlife experts.

  7. Fire hydrants include both above-ground and below-ground types. Check TypeBorne field to filter if needed.

  8. Large datasets (crimes, 311, collisions, fire interventions). Always use LIMIT and pagination. Avoid fetching entire datasets.

  9. Police district boundaries are GeoJSON (Polygon). Requires GIS library for point-in-polygon queries; consider spatial index for performance.

Provenance / Provenance

Source Publisher Gov Level License Contact
Criminal acts SPVM (Police de Montréal) Municipal CC BY 4.0 donneesouvertes@montreal.ca
311 Requests Ville de Montréal Municipal CC BY 4.0 donneesouvertes@montreal.ca
Road collisions SPVM + MTQ Municipal/Provincial CC BY 4.0 donneesouvertes@montreal.ca
Fire interventions SSIM (Montréal Fire Service) Municipal CC BY 4.0 donneesouvertes@montreal.ca
Fire stations SSIM Municipal CC BY 4.0 donneesouvertes@montreal.ca
Police stations SPVM Municipal CC BY 4.0 donneesouvertes@montreal.ca
Police districts SPVM Municipal CC BY 4.0 donneesouvertes@montreal.ca
Coyote sightings Ville de Montréal (Public Health) Municipal CC BY 4.0 donneesouvertes@montreal.ca
Fire hydrants Ville de Montréal (Infrastructure) Municipal CC BY 4.0 donneesouvertes@montreal.ca

All datasets: Published by Ville de Montréal. License: CC BY 4.0 (Creative Commons Attribution 4.0 International).

Related Skills / Compétences connexes

  • query-dataset — SQL patterns for DataStore queries
  • spatial-queries — Geographic proximity and point-in-polygon searches
  • borough-context — Neighborhood names, district codes, boundaries
  • bilingual-handling — French/English crime categories, incident types
  • geojson-handling — Working with fire stations, police boundaries as GeoJSON
Install via CLI
npx skills add https://github.com/alistaircroll/montreal-open-data --skill safety
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