[{"data":1,"prerenderedAt":176},["ShallowReactive",2],{"blog-\u002Fblog\u002Fsponsorships-osmf-openaddresses\u002F":3,"related-blog-\u002Fblog\u002Fsponsorships-osmf-openaddresses\u002F":141},{"id":4,"title":5,"abstract":6,"author":6,"body":7,"description":126,"excerpt":6,"extension":127,"head":6,"image":6,"keywords":128,"meta":133,"modified":6,"navigation":134,"path":135,"proficiencyLevel":6,"published":136,"rawbody":137,"schemaOrg":6,"schemaType":6,"seo":138,"stem":139,"__hash__":140},"blog\u002Fblog\u002Fsponsorships-osmf-openaddresses.md","Sponsorship of Two Open Data Projects",null,{"type":8,"value":9,"toc":120},"minimark",[10,14,39,53,56,61],[11,12,5],"h1",{"id":13},"sponsorship-of-two-open-data-projects",[15,16,17,18,26,27,32,33,38],"p",{},"Stadia Maps leverages open-source mapping technologies and datasets.  Since our inception, we have continually\ncontributed our technical expertise back to several projects, including ",[19,20,25],"a",{"href":21,"rel":22,"target":24},"https:\u002F\u002Fvalhalla.github.io\u002Fvalhalla\u002F",[23],"external","_blank","Valhalla","\nand ",[19,28,31],{"href":29,"rel":30,"target":24},"https:\u002F\u002Fmaplibre.org",[23],"MapLibre",", as well as open-sourcing some ",[19,34,37],{"href":35,"rel":36,"target":24},"https:\u002F\u002Fgithub.com\u002Fstadiamaps",[23],"projects of our own",".",[15,40,41,42,47,48,38],{},"We are happy to announce our financial support for two organizations, whose work we both rely on and contribute back to: the\n",[19,43,46],{"href":44,"rel":45,"target":24},"https:\u002F\u002Fosmfoundation.org\u002F",[23],"OpenStreetMap Foundation"," (Bronze level) and ",[19,49,52],{"href":50,"rel":51,"target":24},"https:\u002F\u002Fopenaddresses.io",[23],"OpenAddresses",[15,54,55],{},"We take pride in contributing monetarily to these organizations, playing our role in helping secure their future.",[57,58,60],"h2",{"id":59},"learn-more-about-stadia-maps","Learn More About Stadia Maps",[62,63,64,73,81],"ul",{},[65,66,67,68,38],"li",{},"Read more about the ",[19,69,72],{"href":70,"rel":71,"target":24},"https:\u002F\u002Fstadiamaps.com\u002Fproducts\u002F",[23],"products we offer at Stadia Maps",[65,74,75,80],{},[19,76,79],{"href":77,"rel":78,"target":24},"https:\u002F\u002Fclient.stadiamaps.com\u002Fsignup\u002F?utm_source=marketing_site&utm_medium=blog&utm_campaign=sponsor_organizations&utm_content=sponsorship_osfm_openaddresses",[23],"Create an account"," to start building today!",[65,82,83,84,89,90,95,96,101,102,107,108,113,114,119],{},"Join our community on ",[19,85,88],{"href":86,"rel":87,"target":24},"https:\u002F\u002Fslack.openstreetmap.us\u002F",[23],"Slack"," or ",[19,91,94],{"href":92,"rel":93,"target":24},"https:\u002F\u002Fdiscord.gg\u002FqRBy6qqtdT",[23],"Discord",", follow us\non ",[19,97,100],{"href":98,"rel":99,"target":24},"https:\u002F\u002Fen.osm.town\u002F@stadiamaps",[23],"Mastodon",", ",[19,103,106],{"href":104,"rel":105,"target":24},"https:\u002F\u002Ftwitter.com\u002F@stadiamaps",[23],"Twitter",", or\n",[19,109,112],{"href":110,"rel":111,"target":24},"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fstadia-maps\u002F",[23],"LinkedIn",", or sign-up for our ",[19,115,118],{"href":116,"rel":117,"target":24},"https:\u002F\u002Feepurl.com\u002Fgs51fD",[23],"mailing list","!",{"title":121,"searchDepth":122,"depth":122,"links":123},"",4,[124],{"id":59,"depth":125,"text":60},2,"We continue our support of the open-source community by sponsoring two organizations: The OpenStreetMap Foundation and OpenAddresses.","md",[129,130,52,131,132],"Open Source","OpenStreetMap","Sponsorship","Community",{},true,"\u002Fblog\u002Fsponsorships-osmf-openaddresses","2023-09-04","---\ndescription: \"We continue our support of the open-source community by sponsoring two organizations: The OpenStreetMap Foundation and OpenAddresses.\"\npublished: \"2023-09-04\"\nkeywords:\n  - Open Source\n  - OpenStreetMap\n  - OpenAddresses\n  - Sponsorship\n  - Community\n---\n\n# Sponsorship of Two Open Data Projects\n\nStadia Maps leverages open-source mapping technologies and datasets.  Since our inception, we have continually\ncontributed our technical expertise back to several projects, including [Valhalla](https:\u002F\u002Fvalhalla.github.io\u002Fvalhalla\u002F)\nand [MapLibre](https:\u002F\u002Fmaplibre.org), as well as open-sourcing some [projects of our own](https:\u002F\u002Fgithub.com\u002Fstadiamaps).\n\nWe are happy to announce our financial support for two organizations, whose work we both rely on and contribute back to: the \n[OpenStreetMap Foundation](https:\u002F\u002Fosmfoundation.org\u002F) (Bronze level) and [OpenAddresses](https:\u002F\u002Fopenaddresses.io).\n\nWe take pride in contributing monetarily to these organizations, playing our role in helping secure their future.\n\n## Learn More About Stadia Maps\n\n- Read more about the [products we offer at Stadia Maps](https:\u002F\u002Fstadiamaps.com\u002Fproducts\u002F).\n- [Create an account](https:\u002F\u002Fclient.stadiamaps.com\u002Fsignup\u002F?utm_source=marketing_site&utm_medium=blog&utm_campaign=sponsor_organizations&utm_content=sponsorship_osfm_openaddresses) to start building today!\n- Join our community on [Slack](https:\u002F\u002Fslack.openstreetmap.us\u002F) or [Discord](https:\u002F\u002Fdiscord.gg\u002FqRBy6qqtdT), follow us\non [Mastodon](https:\u002F\u002Fen.osm.town\u002F@stadiamaps), [Twitter](https:\u002F\u002Ftwitter.com\u002F@stadiamaps), or\n[LinkedIn](https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fstadia-maps\u002F), or sign-up for our [mailing list](https:\u002F\u002Feepurl.com\u002Fgs51fD)!\n",{"title":5,"description":126},"blog\u002Fsponsorships-osmf-openaddresses","_S__JbPTIDwhPOcE0TfH9reEbiGONiL5OnhP9vADhqM",[142,155,167],{"title":143,"description":144,"path":145,"published":146,"keywords":147,"rawbody":154},"Why Basic OpenStreetMap Routing Needs Real-Time Traffic","OpenStreetMap is a world-class road network, but without real-time traffic it's a static dataset. Here's why algorithmic ETAs fall apart in production logistics and how Stadia Maps closes the gap with TomTom-powered routing.","\u002Fblog\u002Fwhy-osm-routing-needs-real-time-traffic","2026-05-12",[148,149,130,150,151,152,153],"Routing","Navigation","Traffic Data","Matrix Routing","Logistics","TomTom","---\ndescription: >-\n  OpenStreetMap is a world-class road network, but without real-time traffic\n  it's a static dataset. Here's why algorithmic ETAs fall apart in production\n  logistics and how Stadia Maps closes the gap with TomTom-powered routing.\nexcerpt: >-\n  OpenStreetMap is great geography, but without real-time traffic it falls\n  short on ETAs. Stadia Maps closes the gap with TomTom-powered routing.\npublished: \"2026-05-12\"\nkeywords:\n  - Routing\n  - Navigation\n  - OpenStreetMap\n  - Traffic Data\n  - Matrix Routing\n  - Logistics\n  - TomTom\nauthor:\n  name: \"Ian Wagner\"\n  jobTitle: \"Founder & President \u002F COO\"\n  sameAs:\n    - \"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fian-w-wagner\u002F\"\n---\n\n# Why Basic OpenStreetMap Routing Needs Real-Time Traffic\n\n> OpenStreetMap (OSM) provides a world-class geographic foundation, but it remains a static dataset. Without real-time traffic integration, routing engines must rely on algorithmic proxies—like road class and legal speed limits—which often lead to unreliable ETAs and logistics bottlenecks.\n\n## The Problem\n\n[OpenStreetMap (OSM)](https:\u002F\u002Fwww.openstreetmap.org\u002Fabout) is one of the world's leading road maps, but a persistent gap remains between fixed geographic data and a [live navigation experience](\u002Fproducts\u002Frouting-navigation\u002F). Without dedicated traffic data, Estimated Times of Arrival (ETAs) are essentially educated guesses. While OSM is excellent at mapping the world's road network, a static dataset cannot capture the actual driving conditions at this exact moment. In enterprise-grade logistics, the lack of live data is often the first significant technical hurdle.\n\n## The Limits of Algorithmic Guesswork\n\nIn the absence of real-time data, a routing engine must estimate travel speeds based on tags and a few common proxies:\n\n- **Road Class:** Assuming a motorway is always faster than a residential street.\n- **Tagged Speed Limits:** Using the legal maximum as the baseline (when the tag even exists).\n- **Network Density:** Adjusting for urban vs. rural environments.\n- **Time of Day:** Using low-granularity buckets like \"daytime\" and \"nighttime.\"\n\nReal-world data show wild variances compared to these static estimates. Road class is a blunt instrument for predicting speed. Missing speed limit tags in open datasets force routing engines to rely on broad averages, resulting in unreliable ETAs and logistics delays. Rule-based algorithms are also notoriously bad at predicting choke points because open datasets don't account for traffic light timings, congestion near specific exits, or the \"invisible\" friction of a busy intersection.\n\n## The Stadia Maps Difference\n\nTo move from guesswork to precision, we integrated [TomTom's global traffic data](https:\u002F\u002Fwww.tomtom.com\u002Fproducts\u002Ftraffic-apis\u002F) directly into the [Stadia Maps routing engine](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002F). High-resolution historical profiles and live feeds allow for accurate, real-time routing. We provide this through three key technical pillars:\n\n1. **Global Coverage:** Access to consistent data across more countries than almost any other vendor.\n2. **Rapid Updates:** A traffic latency of approximately two minutes allows our API to suggest alternate routes almost as soon as a wreck occurs.\n3. **Historical Profiles:** Deep granularity forms the backbone of predictive routing. High-resolution historical data enables accurate, time-dependent routing in advance, allowing you to plan a route for Tuesday at 8:00 AM based on what might happen on Tuesdays at 8:00 AM.\n\n## Fleet Intelligence at Scale\n\nFor dispatch, optimization, and fleet operations, [matrix routing](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002Ftime-distance-matrix\u002F) (calculating the time and distance between many origins and destinations) is the engine's most critical function.\n\nThe Stadia Maps infrastructure supports matrix requests that are significantly larger than most competitors allow on standard plans. By integrating traffic data directly into these large-scale requests, we eliminate the need for developers to split requests into smaller chunks, reducing unnecessary complexity and latency.\n\nDevelopers maintain full agency over their implementation. We provide the fastest route based on live conditions, but the frequency of re-routing remains entirely in your control. Choice of revalidation frequency puts you in charge of the trade-off between real-time accuracy and [scaling costs](\u002Fpricing\u002F), ensuring your bills remain as predictable as your ETAs.\n\n---\n\n[Create a free account](https:\u002F\u002Fclient.stadiamaps.com\u002Fsignup\u002F) to start building with real-time traffic and high-performance routing today. Our [documentation](https:\u002F\u002Fdocs.stadiamaps.com\u002Frouting\u002F) provides everything you need to integrate TomTom-powered precision into your existing OSM workflow.\n",{"title":156,"description":157,"path":158,"published":159,"keywords":160,"rawbody":166},"75 Million More Addresses: Expanding Geocoding Precision","Our largest geocoding dataset expansion yet: 75 million new addresses from OpenAddresses, 3 million new POIs from Foursquare OS Places, smarter intent recognition, and new structured address fields (house_number, street, unit) on the v1 search API.","\u002Fblog\u002F75-million-more-addresses-geocoding-precision","2026-04-27",[161,162,52,163,164,165],"Geocoding","Addresses","Foursquare OS Places","Structured Search","Points of Interest","---\ndescription: >-\n  Our largest geocoding dataset expansion yet: 75 million new addresses from OpenAddresses,\n  3 million new POIs from Foursquare OS Places, smarter intent recognition, and new\n  structured address fields (house_number, street, unit) on the v1 search API.\npublished: 2026-04-27\nkeywords:\n  - Geocoding\n  - Addresses\n  - OpenAddresses\n  - Foursquare OS Places\n  - Structured Search\n  - Points of Interest\n---\n\n# 75 Million More Addresses: Expanding Geocoding Precision\n\nInaccurate geocoding breaks the user experience. If your query returns a street-level guess instead of a rooftop coordinate, a user might be on the right street but the wrong block, or a delivery driver gets routed to an approximate centroid instead of a front door. The coordinates are \"close enough\" until they aren't, and your application takes the blame.\n\nWe continuously update our geocoding dataset as new address and POI data becomes available. This release is our largest expansion yet: 75 million new addresses, 3 million new points of interest, improved intent recognition, and a new way to query with structured address fields.\n\n## Rooftop-Level Accuracy at Scale\n\nThe bulk of this expansion comes from OpenAddresses, one of the largest open datasets of address-level coordinates. These aren't interpolated guesses along a road segment. They're rooftop-level points tied to individual parcels, which matters for any application that depends on precise placement: routing, last-mile logistics, property lookup.\n\nThe gains aren't spread evenly. France and the US lead with roughly 25 million new addresses each, followed by Germany with 3 million and notable expansions across Brazil, Australia, and Mexico. If you've been hitting street-level fallbacks in these regions, you should see noticeably better results.\n\n## Fresher Points of Interest\n\nPOI data goes stale quickly. A restaurant opens, a shop closes, a business moves across the street, and suddenly your search results are sending users to the wrong place. We've added 3 million POIs from Foursquare OS Places, bringing our dataset more in line with what's actually on the ground. Better coverage for the kinds of searches your users actually run: finding a specific restaurant, locating the nearest pharmacy, or navigating to a business that opened last month.\n\n## Smarter Search, Fewer Misses\n\nBeyond raw data, we've improved how our [\u002Fsearch APIs](https:\u002F\u002Fstadiamaps.com\u002Fproducts\u002Fgeocoding-search\u002Fgeocoding\u002F) interpret what users actually mean. The changes focus on intent recognition: better handling of queries for larger geographic areas, complex or compound place names, and cases where the most obvious textual match isn't the right result.\n\nYour users should find more of what they're looking for on the first try.\n\n## Structured Address Input, Now on v1\n\nFor developers working with structured address data, this release adds `house_number`, `street`, and `unit` as first-class fields on the geocoding API. Previously, structured queries supported country, region, and postal code, but the address itself arrived as a single text field that we had to parse before running a match.\n\nIf your dataset is already structured that way, you can now pass it through directly. This is common for shipping, CRM, and property data. Queries with the new fields skip the parsing step entirely, which typically means better match quality and faster responses.\n\nThe free-text `address` field isn't going anywhere. If you only have a single string, we'll still parse it for you. The new fields are available on v1 today. Adopt them at your own pace.\n\n## No Tracking Required\n\nA common assumption in the industry is that better geocoding requires more user data: search history, device location, behavioral signals. We don't work that way. These improvements come from better source data and smarter algorithms, not from profiling your end users. Your users' queries are yours, not ours.\n\nAs with everything we build, these updates are available through standard APIs and SDKs, including MapLibre and Leaflet. Technical precision, fair pricing, and privacy are baked in from the start.\n\n## Get Started\n\nThe expanded dataset, structured address fields, and search improvements are live now for all Stadia Maps customers. New here? [Create a free account](https:\u002F\u002Fclient.stadiamaps.com\u002Fsignup\u002F) and start geocoding.\n",{"title":168,"description":169,"path":170,"published":171,"keywords":172,"rawbody":175},"Mapbox GL JS v2 Licensing and Stadia Maps","An Update on Mapbox GL JS v2 Licensing and Stadia Maps","\u002Fblog\u002Fmapbox-gl-licensing-and-stadia-maps","2020-12-09",[173,174,31,129],"Mapbox GL JS","Licensing","---\ndescription: An Update on Mapbox GL JS v2 Licensing and Stadia Maps\npublished: 2020-12-09\nkeywords:\n  - Mapbox GL JS\n  - Licensing\n  - MapLibre\n  - Open Source\n---\n\n# Mapbox GL JS v2 Licensing and Stadia Maps\n\nYesterday (Dec. 8th, 2020), in conjunction with the v2 release of the\nMapbox GL JS library, the code was re-licensed to require an active\ncommercial license and subscription agreement with Mapbox. As a result,\nif you are currently using Mapbox GL JS v1 with Stadia Map tiles and\nupgrade to v2, you will need to pay Mapbox (as well as Stadia Maps) for\nmap usage.\n\nFor now, please continue using Stadia Maps' map tiles with version v1.13 or\nbelow. Since these versions are fully open source and freely licensed, you\nwill not incur any additional charges and your maps will continue to function as\nexpected.\n\nStadia Maps is actively working to build consensus towards a\ncommunity-driven, fully-open and free fork of Mapbox GL JS v1, and we\nwill continue to support and collaborate on these efforts going forward.\nIf you’re a developer or an organization utilizing the Mapbox GL JS or\nGL Native libraries and are looking for an alternative, feel free to\nreach out. We will continue working together for a more open and more\naccessible open mapping ecosystem.\n",1778676027020]