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Open-Source Data for NDS Maps – challenges and opportunities

10. October 2024

Software development without open source? Hardly conceivable, don’t you think? Almost all digital platforms nowadays, from social media to streaming, are based on open source. Without them, many services that we take for granted wouldn’t even exist. Maps and solutions developed based on the Navigation Data Standard are no exception. As this topic is gaining in importance, the advantages and disadvantages of open-source data in the context of map development should be considered.

It is hardly surprising that there is a growing trend towards community-driven open-source data for mapping such as OSM or Overture Foundation. This development illustrates the growing demand for accessible, adaptable, and community-driven solutions that empower users to contribute and benefit from shared resources. A study by the industry association BITKOM found that almost one in two (53 percent) companies are generally open to OSS. But what does this mean in the context of navigation, maps and automotive innovation?

Open-source data refers to data that is freely available for anyone to use, modify, and distribute. This type of data is often shared under licenses that ensure it remains open and accessible.
Source: Pexels

Accesible and modifiable: Open Source examples

Open-source data encourages collaboration, transparency, and innovation across various fields such as navigation development. It can include a wide range of information, such as geographic data, scientific datasets, or government records.

Key features of open-source data:

  1. Accessibility: Anyone can access and use the data without paying fees.
  2. Modifiability: Users can modify or enhance the data to suit their needs.
  3. Redistribution: Users are allowed to share the data with others, often with the requirement to attribute the original source.
  4. Community-Driven: Many open-source data projects are maintained by a community of contributors who collaborate to keep the data accurate and up to date.

Examples of open-source data sources relevant for navigation

  1. OpenStreetMap (OSM) is a global, community-driven map offering detailed geographic data, including roads, buildings, and natural features. It’s widely used for routing, geolocation, and map-based applications.
  2. The Overture Maps Foundation is a new initiative backed by major tech companies (Meta, Microsoft, TomTom, Amazon) that aims to create reliable, comprehensive open map data to support navigation and other location-based services.
  3. Mapzen offers a suite of open-source tools for building navigation and mapping applications, including search (geocoding), routing, and elevation services.
  4. GeoNames is a geographical database that covers over 11 million place names and locations worldwide, it’s useful for address matching and navigation.
  5. Natural Earth provides free vector and raster map data at various scales, useful for global-scale navigation systems.
  6. USGS National Map offers high-quality data on topography, roads, and hydrography, particularly useful for U.S.-based navigation applications.
  7. TIGER/Line Shapefiles are provided by the U.S. Census Bureau. These shapefiles contain detailed road and boundary data across the United States, often used for routing and address matching.
  8. Public Transport Open Data (GTFS): Google’s General Transit Feed Specification provides data for public transportation schedules and geographic locations. It’s useful for navigation in urban environments.
  9. HERE XYZ (freemium) is a platform offering open and free mapping data layers, useful for mapping and navigation, with an option for freemium services.
  10. OpenAddresses is a repository of worldwide address data, helpful for geocoding and creating navigation systems that require accurate address lookup.
  11. Open Charge is an open-source platform designed for managing and sharing information about EV charging stations. It allows developers and businesses to integrate, access, and share charging infrastructure data, promoting interoperability and easy access to charging services globally.
Some open datasources provide support for developing navigation and mapping systems, offering various levels of detail and global coverage, often maintained by large communities or organizations.
Source: Bing AI

Why NDS.Live?

NDS.Live is based on the many years of experience of leading car manufacturers, system providers, and map data providers. The focus is particularly on the growing requirements of networked vehicles. NDS.Live is modular and self-contained to minimize data consumption, download and cache data and enable both embedded vehicle and cloud systems.

The modular approach allows map data layers to be used by vehicles according to their active feature set, while the architecture of the underlying system scales across the feature portfolio. There is data with very different shelf lives. Some of the information does not need to be updated often. Examples are visual data such as 3D landmarks or a digital terrain model. Then there is data that changes more often and therefore needs to be updated repeatedly – such as POI and speed limits. And then there is data that is needed in near real time and that a system only uses once, for example variable speed limits, the availability of parking spaces or charging stations for electric vehicles. Across the spectrum, data is ideally reused when possible and dynamic data is kept in containers that are as small as possible. A wide variety of data must be mapped for a multitude of use cases.

With NDS.Live, these different data layers can be managed and pre-published to then be configured and bundled as smart layers according to individual needs. Those who need a different configuration later, for example to activate an additional function or to react to market needs, can configure an additional smart layer composition from the pre-published data layers. All this was not possible with a static, non-modular data specification such as NDS.Classic.

Examples of NDS Layers that can be compiled using open-source data: 

  1. Road Topology and Geometry
  2. Road Characteristics
  3. Road Rules
  4. Administrative Hierarchy 
  5. Region Rules 
  6. POI 
  7. Visuals and Display 
  8. Names 

At NDS Conference 2024 NDS member Intellias and GoodYear presented their use case with  open source data “NDS.Live for Vehicle Conditions Featuring Goodyear SightLine” including road network, speed limits and advisory speed limits derived from OpenStreetMap. OSM is a collaborative project that creates a free, editable map of the world. It is built and maintained by a community of volunteers who contribute geographic data, such as roads, landmarks, and other features, which can be freely used by anyone.

Pros and cons of open-source tools and data in navigation development

First of all, it has to be said that the described platforms arefree, flexible and frequently updated. Furthermore, they offer big coverage, local knowledge and access to raw data. On the other hand, there are also a few hurdles. For example, there are points of criticism such as data quality, lack of standardization, missing advanced features and lack of support.

Developers can leverage community-driven open-source mapping data, such as OSM to enrich NDS maps by integrating this data to fill in gaps or enhance details in existing map sources. They can use open-source mapping to customize maps for specific regions, add localized features, and take advantage of the frequent updates provided by the global community.

However, developers also need to consider several factors when using open-source data. Data quality and consistency are paramount, as open-source data can vary in accuracy, especially in less populated areas. Developers should validate the data to ensure it meets the NDS standard. Licensing is another critical consideration, as developers must comply with the terms of open-source licenses, such as the Open Database License (ODbL) used by OSM, and provide proper attribution when required. They also need to ensure that the open-source data is compatible with the NDS format, which might require conversion or transformation processes. Additionally, integrating large amounts of open-source data could increase processing overhead, so efficient data management is necessary.

In conclusion, while using open-source mapping data can be highly beneficial, especially for enriching and customizing NDS Maps, developers should carefully evaluate the quality, legal implications, and integration challenges before fully committing to it. It is advisable to use open-source data with caution, ensuring it complements the overall quality and reliability of NDS Maps.

In the NDS.Live Developer Portal you can find out more about the possibilities and functions of NDS.Live.

Here you can watch the complete presentation by Intellias and GoodYear at this year’s NDS Conference.

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