Oslo kommune EV Charging Station Locations Dataset – Norway
Oslo kommune EV Charging Station Locations Dataset – Norway
The City of Oslo's own public charging program, run by its Agency for Urban Environment (Bymiljøetaten) under the "Lad i Oslo" initiative. It installs normal-speed (6.9–22 kW) charging points on municipal parking spaces, mainly for residents without home charging access, with payment and access managed through the "Bil i Oslo" app; separate fast-charging stations on public land are built and run by private operators via public tenders.
There are 314 Oslo kommune EV Charging Stations as of 16 July 2026 in Norway. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Oslo kommune locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.
Dataset Summary
- Dataset Coverage: 314 Oslo kommune ev charging stations in Norway
- Contents: Coordinates, addresses, postal codes, and administrative divisions
- File Format: Fully geocoded CSV dataset (UTF-8)
- Free Sample: Instantly accessible dataset to verify structure and data quality
- Use Cases: Suitable for GIS, retail analytics, site selection, and AI/RAG workflows
- Last Updated: 16 July 2026
Dataset Methodology:
This dataset is compiled from publicly available business listings, official company sources, and geospatial validation workflows. Automated quality checks and manual analyst reviews are applied to improve coordinate precision, address standardisation, duplicate detection, and overall analytical consistency.
It is periodically reviewed and updated to reflect known network changes, closures, relocations, and newly identified locations.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- Town
- Admin_level_1
- Admin_level_2
- Municipality
- Region
- Population
- Postal Code
- Address
Require additional attributes such as charging points, charger types, or charging speed? Contact us to request a custom data enrichment.
Data Preview: Sample geospatial records from the Oslo kommune dataset in Norway
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| de1c43f... | Oslo kommune Charging Station | 59.927483 | 10.762897 | 556 | Falsens gate, 0556, Oslo, Norway |
| b67a9cb... | Oslo Kommune Charging Station | 59.925797 | 10.771681 | 567 | 0567, Oslo, Norway |
| e81f2c7... | Oslo Kommune Charging Station | 59.935453 | 10.775154 | 479 | 31 Nordkappgata, 0479, Oslo, Norway |
| 8841e51... | Oslo kommune Charging Station | 59.921160 | 10.851791 | 673 | 13 Hagapynten, 0673, Oslo, Norway |
| 82cc222... | Oslo Kommune Charging Station | 59.917594 | 10.847517 | 673 | 3A Haugerudhagan, 0673, Oslo, Norway |
Note: Only a subset of the full dataset fields are displayed here. Download the free sample (option above) to view all fields and verify the data structure.
Why download from Geolocet?
- Instant download - full dataset available immediately after purchase, no waiting, no manual fulfilment
- Free sample first - verify structure, fields, and coordinate precision before you commit
- Analysis-ready CSV - clean, standardised, and compatible with Excel, Python, QGIS, Power BI, and PostgreSQL out of the box
- Regularly updated - last updated 16 July 2026
✅ Data looks right? Add to cart ↑ - or download the free sample first.
Regional Distribution Breakdown
Looking at the geographic distribution, the highest concentration of Oslo kommune locations in Norway is found in Oslo Og Viken (314 sites, equivalent to 15.17 Oslo kommune ev charging stations per 100,000 residents).
Also available for Norway
Brand bundle
Top 12 EV Charging Stations Brands in Norway - €380
All major chains in one standardised dataset. Best for competitive benchmarking, network analysis, and market sizing across the leading brands.
View Top Brands dataset →Full market coverage
All EV Charging Stations Locations in Norway - complete POI dataset
Includes everything in the brand bundle plus independent operators, smaller chains, and local businesses not covered by the top brands. Best for full market mapping, territory planning, and white-space analysis.
View full POI dataset →Related geospatial datasets
- Administrative boundaries and full polygon dataset for Norway: Map these Oslo kommune locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Norway: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Oslo kommune locations.
- Explore demographics data insights for Norway: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Explore a rich library of Norway-specific datasets on our dedicated country page: detailed demographics, wealth indicators, multi-level boundaries, and a broad spectrum of retail POIs. View demographics, retail POI, and administrative boundary datasets for Norway
Need the data in another format?
We can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at contact@geolocet.com.
Who uses this data?
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
- Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
- B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
- Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
- Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
- Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
Frequently Asked Questions
Q: Are the datasets suitable for machine learning workflows?
A: Yes. The structured tabular format and standardized coordinates make the datasets suitable for machine learning and predictive analytics applications.
Q: Is this dataset useful for accessibility studies?
A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.
Q: Can this dataset support expansion planning?
A: Yes. Analysts often use the dataset to identify underserved areas, evaluate regional density, and support retail expansion decisions.
Q: How accurate are the coordinates?
A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.
Q: Does the dataset include accessibility-related attributes?
A: Yes. Certain datasets include accessibility-related indicators such as wheelchair accessibility where publicly available.
Q: Does the dataset contain duplicate locations?
A: Duplicate detection and validation workflows are applied during processing to improve consistency and reduce redundant records.
Q: Does the dataset include unique identifiers?
A: Yes. Each record includes a GUID field to support deduplication, joins, and downstream database operations.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Oslo kommune dataset to identify underserved regions in Norway for potential market expansion.""Analyze geographic gaps in the current Oslo kommune network and identify underserved regions in Norway with strong expansion potential.""Measure average inter-store distance between Oslo kommune locations across different regions of Norway."
Disclaimer: All brand logos and trademarks displayed are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data only; no images, logos, or trademark rights are included in the downloadable files.