Goodbye to Google Maps: Amazon, Meta and Microsoft Release First Open-Source Map Data


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The Overture Maps Foundation, founded last December by Amazon, Meta, Microsoft and TomTom to create open and interoperable mapping products, has published its first open map dataset that anyone can use for free. The “alpha” release aims to help developers build mapping applications and location-based tools to rival Google Maps.

The initial open data release includes over 59 million places of interest, 780 million unique building footprints, road data from OpenStreetMap, and border information sourced from around the world.

In a press statement, the foundation said this public dataset launch will be the first to “enable current and next-generation interoperable open map products.” The collaboration is based on the idea that map data should be a shared asset to support future map-based applications.

As demands grow for more accurate, up-to-date, and attributed mapping data, the cost and complexity of collecting global map data is too great for any single company, the foundation said.

The open map data is packaged in the newly announced Overture Maps Foundation format. The dataset has four layers — Places of Interest (POIs), Buildings, Transportation Network, and Administrative Boundaries.

The 59 million places of interest records in the first layer have never before been published as open data. The 780 million building footprints in the second layer include some of Microsoft’s proprietary AI-generated building data. The third layer contains road networks worldwide from OpenStreetMap data. The fourth layer comprises country and territory borders translated into over 40 languages.

While not yet robust enough to support full mapping products, the initial open data release aims primarily to garner public feedback. Overture’s executive director Marc Prioleau said the places dataset specifically has the potential for mapping anything from small startups to pop-up markets globally.

Overture plans to include more open data in future datasets, including a “Global Entity Reference System” for consistent map feature identification. Public feedback can be provided on GitHub.

Vishak is a skilled Editor-in-chief at Code and Hack with a passion for AI and coding. He has a deep understanding of the latest trends and advancements in the fields of AI and Coding. He creates engaging and informative content on various topics related to AI, including machine learning, natural language processing, and coding. He stays up to date with the latest news and breakthroughs in these areas and delivers insightful articles and blog posts that help his readers stay informed and engaged.

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