Working With
Overture Data:
A Step-by-Step Guide

Jennings Anderson, PhD

Marc Prioleau
Executive Director of
Overture Maps

Jennings
Anderson, PhD
Research Scientistat Meta

Resources
docs.overturemaps.org
github.com/overturemaps/datagithub.com/overturemaps/schema

What is in the 2023-07-26-alpha.0 data release?
…and why is there no“download all the data here”
button?

What is in the 2023-07-26-alpha.0 data release?
4 Themes:
1.

Administrative
Boundaries (admins)

2.

Buildings

3.

Places4.

Transportation

docs.overturemaps.org

Administrative Boundaries (admins) at-a-glance99,403 features
2,948 localityi.

adminLevel=2 (265) (Polygon/Multipolygon)ii.

adminLevel=4 (2,683) (Multipolygons)

96,455 administrativeBoundary (LineStrings)
iii.

adminLevel=2 (18,825)

iv.

adminLevel=4 (77,630)

Buildings at-a-glance
785,524,851 building features●

27,871,758 have height information (at least 10M from USGS Lidar)●

562,731,640 from OpenStreetMap●

211,937,251 from Microsoft ML Buildings Dataset●

10,855,960 from Esri Community Maps

What is the order of conﬂation?
OpenStreetMap > Esri > Microsoft ML

Places at-a-glance59,175,720 place features●

51,669,480 from Meta●

4,681,011 from Microsoft●2,825,229 from bothTransportation at-a-glance
Re-segmented OSM road network:●294,327,662 segment features●330,606,087 connector features

Let’s dig in
Using Amazon Athena as aninteractive query
environment to read
Overture data
Athena is just one way toaccess the data. Instructions
are available on github.

github.com/overturemaps/dataPlaces Queries
SELECT COUNT(*) FROM places
SELECT * FROM places LIMIT 10
SELECT ROUND(confidence * 10)/10 AS _conf,
COUNT(id) as _count
FROM places
GROUP BY ROUND(confidence * 10)
ORDER BY _conf DESC

Where is the places coverage?
WITH places_with_quadkey AS (SELECT bing_tile_quadkey(BING_TILE_AT(
ST_Y(ST_GeomFromBinary(geometry)),
ST_X(ST_GeomFromBinary(geometry)),
8)) AS q8,
id
FROM places
WHERE confidence > 0.8)
SELECT BING_TILE_POLYGON(BING_TILE(q8)),
count(id) as num_places
FROM places_with_quadkey
GROUP BY q8

Download some data as a CSV with Athena
SELECT TRY(FILTER(names [ 'common' ],name->name [ 'language' ] = 'local') [ 1 ] [ 'value' ]) AS name,categories.main AS category,
confidence,
ST_GeomFromBinary(geometry) as wkt
FROM places
WHERE confidence > 0.8
AND bbox.minX > -126.7952
AND bbox.maxX < -118.5453
AND bbox.minY > 43.5453
AND bbox.maxY < 50.4344

Analyze buildings coverage globally
WITH buildings_with_quadkey AS (SELECT
bing_tile_quadkey(BING_TILE_AT((bbox.maxY + bbox.minY)/2,(bbox.maxX + bbox.minX)/2,8)) AS q8,id,
CARDINALITY(FILTER(sources, x -> x['dataset'] = 'OpenStreetMap'))>0 AS osm_building
FROM buildings)
SELECT
BING_TILE_POLYGON(BING_TILE(q8)),
COUNT(id) as num_buildings,
COUNT_IF(osm_building) AS osm_building,
COUNT_IF(osm_building) / CAST(COUNT(id) AS double) AS percent_osm
FROM buildings_with_quadkey
GROUP BY q8

Download some buildings in Seattle
SELECT class, height,
ST_GeomFromBinary(geometry) as wkt
FROM buildings
WHERE ST_CONTAINS(ST_GeometryFromText('POLYGON((-122.36719284258956
47.618321237733284,-122.33594394153602
47.632404470851924,-122.2775808079059
47.61236859966664,-122.34462990362489
47.58012171471199,-122.36719284258956
47.618321237733284))'),
ST_GeomFromBinary(geometry))Still no download button?
Athena is just one way to access thedata.
Today, we transformed, downloaded,analyzed, and grouped the data all
without needing to ﬁrst download andprocess a massive ﬁle.
If you must download all of the data,
the parquet ﬁles are available!
github.com/overturemaps/dataWhat’s Next?
Future releases will continue improving in coverage and quality on thethe existing themes
The Global Entity Reference System (GERS) will assign stable IDs tofeatures in the 4 themes, allowing matching of external datasets andeasy id-based conﬂation.

Q&A

Thank You