🌏 🍰 🍴 Using StreetCred Data to Improve OpenStreetMap 🍴 🍰 🌎

Ben Chodoroff - October 28, 2019

StreetCred is a company built on the shoulders of giants. A healthy, thriving open-source ecosystem of mapping projects enables companies like ours to come up with new ideas to improve map data. When you use our mobile app, the map layer behind all of our data is from OpenStreetMap, a map of the whole world that anyone can edit and improve. When you improve OSM -- say, by fixing a typo in a building name -- everyone who uses OSM data benefits! This is why we’re publishing a freely-licensed data layer that OpenStreetMap editors can use to improve this free resource.

Now, you can participate in StreetCred’s data collection contests, then easily use the data you (and other participants) collect to improve OpenStreetMap. It’s like having a cake and eating it, but the cake is made of point-of-interest data!

Before & After

Here are screenshots from the iD editor near San Pedro and E 12th Street in Los Angeles:

OSM data in LA
OpenStreetMap's data layer shows very few points of interest in this shopping area.
StreetCred data in LA
StreetCred's data layer can help OSM editors add new points of interest.

Try it out

Open up the OpenStreetMap iD editor (https://www.openstreetmap.org/edit?editor=id#map=19/40.70526/-74.01295 will take you to the Financial District in Manhattan) and press the F key or click on the wand/gear icon to bring up the Map Data menu. From there, click on the β€œ...” button to add a custom data layer.

In the text area, paste in https://tiles.streetcred.co/osm/{z}/{x}/{y}.mvt and click OK. If you’re in an area that has StreetCred points of interest, like that lat/lon in the link above, you’ll see a sea of pink dots. Each dot is a point of interest.

From there, you can add points if you see anything missing, or edit existing data if there are any mistakes. Be sure to keep the source=streetcred tag, as well as the addr and place tags.

About the data

Our ODbL-licensed data is available from an MVT tileserver at https://tiles.streetcred.co/osm/{z}/{x}/{y}.mvt. Read about MVT tiles to learn more about how to ingest this sort of data. The MVT tiles include a single layer, places. Each point of interest is represented by a feature in this layer. Here’s an example of the properties each feature has:

addr:city=New York

If needed, you can find more information about the category IDs, including translated category names, at https://github.com/streetcredlabs/categories.

Let us know if you have any questions about this service! Happy mapping!