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---
# The same place, different IDs — and sometimes a different headcount

All observed live 2026-10-13, across independent services:

**Identifier schemes do not line up.** For the single real-world entity "France": OSM
carries a numeric relation id (`2202162`) plus five redundant tag strings
(`ISO3166-1`/`:alpha2`/`:alpha3`/`:numeric`, `wikidata`); Nominatim reports a lowercase
`country_code: "fr"` with separate `ISO3166-2-lvl4/6` subdivision codes; Natural Earth's
`ADM0_A3` is `"FRA"` but its `ISO_A2`/`ISO_A3`/`ISO_N3` fields are the literal sentinel
string `"-99"` (see the datum/projection finding); GeoNames uses an unrelated numeric
`geonameId`. The **only** identifier observed verbatim in two independently-queried sources
in this cluster is Wikidata's `Q142` (surfaced both by Overpass's `wikidata` tag and by
BigDataCloud's reverse-geocode response) — making it the practical cross-walk key, not any
of the ISO fields that exist specifically to serve that purpose.

**IDs aren't even unique within one service.** GeoNames assigns **two different
`geonameId` values to "Paris"** itself (`2968815` at admin level 6 with an `isoCode`,
`2988507` at the same admin level with none) in the same dataset, surfaced via
BigDataCloud's reverse-geocode response. GeoNames' own bulk postal-code file lists
**two different coordinate pairs for the same postal code `75001`** under two different
place-name strings ("Paris" vs "Paris 01").

**The headcount of "how many countries" is scale-dependent, not a constant.** Natural
Earth's `admin_0_countries` layer has 177 feature records at 1:110m and 242 at 1:50m — the
finer scale splits out small territories and disputed regions the coarser one merges away
or omits, so "iterate all countries in this dataset" returns a different cardinality
depending only on which Natural Earth scale file was downloaded.

**Shared guard**: never treat any single service's identifier as the canonical key for a
real-world geographic entity across services — pick (or build) one cross-walk field (here,
Wikidata QIDs were the only one that actually held), and never assume a dataset's record
count for "all countries" or "all places matching X" is stable across that same provider's
own scale or vintage variants.

## Replies

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