Linked Data for places – any advice?

We’d really benefit from advice about what Linked Data namespaces to use to describe places and the relationships between them. We want to re-use as much of others’ work as possible, and use vocabularies which are likely to be well and widely understood.

Here’s a sample of a “vanilla” rendering of a record for a place-name in Cheshire as extracted from the English Place Name Survey – see this as a rough sketch.

<RDF>
<chalice:Place rdf:about=”/place/cheshire/prestbury/bosley/bosley”>
<rdfs:isDefinedBy>/doc/cheshire/prestbury/bosley/bosley
</rdfs:isDefinedBy>
<rdfs:label>Bosley</rdfs:label>
<chalice:parish rdf:resource=”/place/cheshire/prestbury/bosley”/>
<chalice:parent rdf:resource=”/place/cheshire/prestbury/bosley”/>
<chalice:parishname>Bosley</chalice:parishname>
<chalice:level>primary-sub-township</chalice:level>
<georss:point>53.1862392425537 -2.12721741199493</georss:point>
<owl:sameAs rdf:resource=”http://data.ordnancesurvey.co.uk/doc/50kGazetteer/28360″/>
</chalice:Place>
</rdf:RDF>

GeoNames

We could re-use as much as we can of the geonames ontology. It defines a gn:Feature to indicate that a thing is a place, and gn:parentFeature to indicate that one place contains another.

Ordnance Survey

Ordnance Survey publish some geographic ontologies: there are some within data.ordnancesurvey.co.uk, and there’s some older work including a vocabulary for mereological (i.e. containment) relations includes isPartOf and hasPart. But the status of this vocabulary is unclear – is its use still advised?

The Administrative Geography ontology defines a ‘parish‘ relation – this is the inverse of how we’re currently using ‘parish’. (i.e. Prestbury contains Bosley) (And our concepts of historic parish and sub-parish are terrifically vague…)

For place-names found in the 1:50K gazetteer the OS use the NamedPlace class – but it feels odd to be re-using a vocabulary explicitly designed for the 50K gazetteer.

Or…

Are there other wide-spread Linked Data vocabularies for places and their names which we could be re-using? Are there other ways in which we could improve the modelling? Comments and pointers to others’ work would be greatly appreciated.

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