POI and places data: sourcing and use

Points-of-interest data, the businesses, amenities and landmarks that fill a map, underpins location analytics across many sectors. This guide covers what POI data contains, its quirks, and how to source it well.

What POI data is

POI (points-of-interest) data describes places: name, category, location, and often attributes such as opening hours, brand and contact details. It is the backbone of location analytics, mapping and routing context.

Common use cases

Site selection and catchment, competitor and white-space analysis, logistics and routing context, risk and insurance, and enriching other datasets with nearby-place context.

Coverage and freshness

The hard problems with POI are coverage and freshness: places open and close constantly, so a stale dataset misleads. Coverage also varies by region and category. Recency and update cadence are central sourcing criteria.

Deduplication and conflation

The same place often appears in multiple sources with different names or coordinates. Conflating sources into a clean, deduplicated set, while keeping the best attributes, is much of the work and value.

Sourcing considerations

Assess coverage, freshness, attribute richness and licensing (open vs commercial). Combining open and commercial POI with entity resolution typically beats any single source.

Delivery and governance

POI is geospatial, so consistent coordinates and formats matter. Most POI is non-personal, but contact fields may include personal data. A managed partner can conflate sources and deliver a clean places layer.

Coverage, freshness and conflation

The two hard problems with POI data are coverage (which places are present, by region and category) and freshness (places open and close constantly, so a stale set misleads). Because the same place appears differently across sources, conflation, deduplicating and merging while keeping the best attributes, is much of the work. Combining open sources like OpenStreetMap and Overture with commercial data, resolved carefully, usually beats any single feed.

Using POI well

POI is geospatial, so consistent coordinates and formats matter, and contact fields can contain personal data requiring care. Whether for catchment, competitor analysis or routing context, judge a POI dataset on recency and attribute richness as much as on raw count.

Sources & further reading

• OpenStreetMap and Overture Maps: open places data.
• Commercial POI providers and their methodologies.
• Open Geospatial Consortium: location standards.
• EUR-Lex: Regulation (EU) 2016/679 (GDPR) for contact fields.