AWS, The Linux Foundation Drive Open Map Data Effort

The Overture Maps Foundation group’s mission is to enable current and next-generation map products by creating reliable, easy-to-use, and interoperable open map data.

The Linux Foundation recently announced the formation of the Overture Maps Foundation, a new collaborative effort to develop interoperable open map data as a shared asset that can strengthen mapping services worldwide. The initiative was founded by Amazon Web Services (AWS), Meta, Microsoft, and TomTom and is open to all parties with a common interest in building open map data.

This is just one of several unrelated map database announcements (see below) made in the last month. The cluster of announcements highlights the growing use and importance of map databases. Such databases are playing an increasingly important role in the emerging areas of location-based services.

Specifically, map data underlies many applications for local search and discovery, routing and navigation, logistics, mobility, autonomous driving, and data visualization. In the future, many companies envision map services powering augmented reality applications that merge the digital and physical worlds to deliver rich user experiences.

With respect to the Overture effort, the group’s mission is to enable current and next-generation map products by creating reliable, easy-to-use, and interoperable open map data. This interoperable map is the basis for extensibility, enabling companies to contribute their own data. Group members will be able to combine resources to build map data that is complete, accurate, and refreshed as the physical world changes.

To that point, Overture, along with other contributors, aim to deliver:

  • Collaborative map building: Overture aims to incorporate data from multiple sources, including Overture Members, civic organizations, and open data sources.
  • Global entity reference system: Overture will simplify interoperability with a system that links entities from different data sets to the same real-world entities.
  • Quality assurance processes: Overture data will undergo validation to detect map errors, breakage, and vandalism to help ensure that map data can be used in production systems.
  • Structured data schema: Overture will define and drive the adoption of a common, structured, and documented data schema to create an easy-to-use ecosystem of map data.

As these objectives are met, the open map data could be used to help developers and map creators build new applications. Additionally, the project seeks to integrate with existing open map data from projects such as OpenStreetMap and city planning departments, along with new map data contributed by members and built using computer vision and AI/ML techniques to create a digital record of the physical world.

See also: Why Data in the Cloud Will Soon Morph into Autonomous Distributed Data

New map database effort aims at agriculture

The Linux Foundation also recently announced work related to the AgStack project. The Linux Foundation will host a new open-source code base alongside a fully-automated, continuous computation engine to “create, maintain and host a global dataset of boundaries’ registry for agricultural fields to aid in such things as food traceability, carbon tracking, crop production, and other field-level analytics.”

The project has the potential to unlock the next revolution of digital agri-services in the public and private sectors, especially for owners of smaller farms. Why? Precise knowledge of field boundaries can help farmers, agricultural companies, and the public sector to monitor and manage crop production, study management practices (crop rotations, cover cropping, tillage, irrigation), determinants of productivity, pest and disease spread, and species diversity. By sharing reusable agricultural data, new insights can also be gleaned for global food security research and innovation.

AgStack’s Asset Registry dataset is built and continuously updated using data from satellites and actual field registrations that contain information on boundaries, which will then train machine learning models to ascertain more boundaries.

Such information is critical for many agricultural applications. “We think that a public field boundary dataset can help turbocharge a lot of smart people and businesses focused on improving agriculture and food security around the world,” said Professor David Lobell of The Center on Food Security and the Environment at Stanford University. (Lobell hosted the original research in this area as the Gloria and Richard Kushel Director of the Center on Food Security and the Environment at Stanford University and the Benjamin Page Professor of Earth System Science.)

According to the group, “by leveraging computer science and artificial intelligence, members will create, curate, and maintain global field boundaries as an open source digital public good available for anyone to use.”

That is where The Linux Foundation can help. The effort seeks to enable all types of agricultural data analysis and services by bridging computing and AI research expertise with a global network of partners in an open-source software ecosystem. That is exactly what the Linux Foundation does.

See also: Cloud Data Platforms: Data Shifts to the Cloud 

Census data update to ArcGIS Living Atlas

In another recent map database-related announcement, the United States Census Bureau released its annual update to its American Community Survey (ACS) data. The ACS 2022 data is important to federal agencies and state and local governments, many of which require its use for their operations and decision-making, as well as to nonprofit organizations that rely on the data for grant applications.

These organizations typically access this information via Esri’s ArcGIS Living Atlas, a widely used collection of global geographic information that includes maps, apps, and data layers used by organizations around the world for research and analysis. Through ArcGIS Living Atlas, users can map and query more than 1,700 annually updated attributes of ACS tables, and this integration provides them with a faster way of accessing and analyzing this data.

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