OpenStreetMap for Regional Reporting

Last reviewed: 26 July 2026Next review due: 26 July 2027

1. What is OpenStreetMap?

OpenStreetMap (OSM) is a free, editable map of the world, built by hundreds of thousands of volunteers — a Wikipedia for geography. Anyone can add a road, a building, a bus stop or a bin. Behind the familiar map picture at openstreetmap.org sits a structured database of tagged features that you can query and download.

For regional and hyperlocal journalism that database is a gift: it can answer questions such as how many pubs a town has lost, where public defibrillators are, or how EV charge points cluster — provided you understand its licence and its limits.

2. The open licence — and what it requires

OSM data is licensed under the Open Database Licence (ODbL). You are free to copy, use and adapt the data commercially, but two obligations follow: you must attribute OpenStreetMap and its contributors, and the licence carries a share-alike clause that can require any derived database you publish to be released under the same terms.

In practice, a published map graphic needs the standard credit line — “© OpenStreetMap contributors” with a link to the licence. If you are building and redistributing a substantial database, read the ODbL in full and, for commercial or systematic reuse, take proper advice. Attribution is not optional courtesy; it is a licence condition.

3. Base map versus dataset

There are two completely different ways journalists use OSM, and confusing them wastes time:

1As a base map — the road-and-place-name background your data sits on. You are using a rendered picture for context, and the credit line is the main obligation.
2As a dataset — the underlying tagged features (points, lines, areas) extracted so you can count, filter and map them. This is where the reporting is, and where verification matters most.

4. Extracting data with Overpass Turbo

overpass-turbo.eu is a free, browser-based tool that queries the live OSM database. You describe the features and the area you want in Overpass QL, press Run, and export the results. The example below finds every feature tagged as a school within a named area:

[out:json][timeout:25];
area[name="Leeds"][admin_level=8]->.a;
nwr[amenity=school](area.a);
out center;

Swap amenity=school for other tags to answer other questions: amenity=pub for pubs, amenity=charging_station for EV chargers, or emergency=defibrillatorfor public defibrillators. Prefer the wizard if you are new — type a plain phrase and it writes the query. When results appear, use Export to download GeoJSON for QGIS, or a table for a spreadsheet.

5. Downloading regional extracts (Geofabrik)

When you need a large, complete slice of the map rather than a targeted query — a whole region or the whole of England — download a ready-made extract from geofabrik.de. Geofabrik publishes regularly updated country and sub-region files that QGIS and GDAL can open directly.

Extracts are big and contain everything, so you filter down after loading. Use them for offline processing, for reproducibility (the file is a fixed snapshot with a date), or when an Overpass query would be too large or time out.

6. Importing OSM data into QGIS

Take the GeoJSON exported from Overpass Turbo and add it with Layer → Add Layer → Add Vector Layer. Your schools or pubs appear as points you can count, label, filter by tag and style. From there it is the same workflow as any other layer: join it to boundaries, aggregate by ward or council, or symbolise by category.

For a full Geofabrik extract, QGIS reads the file directly and lets you select which layers (points, lines, polygons) to load, so you can pull out just the features your story needs. See our QGIS basics guide for styling and export.

7. Features worth querying for local stories

Public defibrillators (emergency=defibrillator) — coverage and gaps in a community.
EV charging points (amenity=charging_station) — the pace of local rollout.
Pubs, banks and post offices — closures and high-street decline over time.
Schools, GP surgeries and pharmacies — access and travel-distance mapping.
Bus stops, cycleways and footpaths — active-travel and transport-desert stories.

8. Verify before you publish

OSM is crowd-sourced. That is its strength and its risk. A feature may be missing because nobody added it, present but out of date, or tagged inconsistently between mappers. An Overpass count is a lead, not a fact.

Cross-check counts against an official register — a council list of defibrillators, or Ofsted for schools — before publishing any number.
Check the edit date and history of key features on openstreetmap.org; some entries are years old.
Watch for tagging variants (an EV charger might be tagged several ways) that split or hide results.
Never state "there are exactly N" from OSM alone; write that OSM records N, and say so.

9. Turning extracts into stories

The strongest OSM stories combine an extract with an official dataset. Map OSM pub locations against licensing records to show closures; overlay defibrillator points on population to reveal cold spots; or plot EV chargers against car ownership to test whether rollout matches need.

Because OSM covers the whole country uniformly, the same query can be repeated for every council area, letting you compare your patch against national context — a natural fit for hyperlocal reporting.

10. Understanding OSM tags

Everything in OpenStreetMap is described by tags, and understanding them is what lets you write good queries. A tag is a key and a value — amenity=school, shop=bakery, emergency=defibrillator. A single feature can carry many tags describing its name, opening hours, operator and more.

The keys and values are conventions agreed by the community and documented on the OpenStreetMap Wiki, not a fixed schema. That has two consequences for reporters:

The same real-world thing can be tagged more than one way, so a single query may miss features tagged under a variant key — always check the wiki for alternatives.
Tags can be deprecated or inconsistently applied, so a clean-looking result may still be incomplete.
Before trusting a count, look up the tag on the wiki and search a couple of alternative tags to be sure you have captured the feature fully.

11. OSM reporting checklist

I have added the correct ODbL attribution to any published map.
I am clear whether I am using OSM as a base map or as a dataset.
I limited my Overpass query to a defined area to keep it fast.
I checked the tagging variants that could split or hide results.
I cross-checked OSM counts against an official register.
I described figures as what OSM records, not as a definitive total.

Map it

Once you have exported an extract, our QGIS and boundary-data guides show you how to join it to council or ward geographies and produce a publication map.

QGIS Basics UK Boundary Data

Frequently asked questions

Do I have to credit OpenStreetMap, and how?

Yes. OpenStreetMap data is published under the Open Database Licence (ODbL), which requires attribution. When you display OSM as a base map, use the standard credit line, typically worded as data copyright OpenStreetMap contributors, with a link to the licence. If you extract OSM data and combine it into a derived database, the ODbL's share-alike terms can also require that you make the resulting database available under the same licence. For a simple map graphic the attribution line is usually enough, but read the licence and, for anything commercial or systematic, take advice.

What is the difference between using OSM as a base map and as a dataset?

A base map is the background imagery — roads, place names and coastlines — that gives your graphic context. You are consuming a rendered picture. Using OSM as a dataset means extracting the underlying structured features, such as every school, pub or EV charge point in a town, as points you can count, filter and analyse. The base-map use is presentational; the dataset use is analytical and is where the journalism usually lies. The same project, OpenStreetMap, supports both, but the workflow and the verification burden are very different.

How complete and reliable is OpenStreetMap for a UK area?

It varies enormously by place and by feature type. Roads, rivers and large buildings are generally excellent across the UK. Amenities like defibrillators, EV chargers or independent shops depend entirely on whether a local mapper has added them, so coverage can be patchy and dates unknown. OSM is crowd-sourced, so a feature may be missing, out of date or misclassified. Treat an Overpass extract as a strong lead, never as a definitive register. Always cross-check counts against an official list before you publish a number.

What is Overpass Turbo and do I need to install anything?

Overpass Turbo is a free web tool at overpass-turbo.eu that runs queries against the live OpenStreetMap database and shows the results on a map you can export. Nothing to install: it runs in the browser. You write a short query in Overpass QL describing the features and the area you want, press Run, and then export the results as GeoJSON to open in QGIS or as a spreadsheet. The built-in wizard writes simple queries for you from plain phrases like amenity equals school, which is the easiest way to start.

When should I download a Geofabrik extract instead of using Overpass?

Use Overpass Turbo when you want a specific set of features in a defined area — the schools in one borough, say. Use a Geofabrik extract when you need a large, complete slice of the map, such as all of England or a whole region, to process offline. Geofabrik publishes regularly updated country and sub-region extracts at geofabrik.de in formats QGIS and GDAL can read. Extracts are large and general-purpose; Overpass is precise and targeted. For most single-story newsroom tasks, Overpass is faster and lighter.

Primary sources

OpenStreetMap— OpenStreetMap Foundation
OpenStreetMap copyright and ODbL licence— OpenStreetMap Foundation
Overpass Turbo — query the OSM database— Overpass Turbo
Geofabrik — regional OSM extracts— Geofabrik
OSM map features and tags reference— OpenStreetMap Wiki