Geospatial Data Examples: 3 European Headquarters

Geospatial data can often seem complex or overly technical, but its purpose is simple: to describe the world in terms of location. In this article, we aim to simplify key geospatial data terms and illustrate an example of a geospatial dataset using data from the headquarters of three well-known European companies.

At its core, geospatial data refers to any information tied to a specific location on Earth’s surface—such as businesses, parks, buildings, roads, rivers, or even natural features like mountains.

Depending on the type, geospatial data goes far beyond basic coordinates (latitude and longitude) or addresses. Geospatial datasets can include attributes like building footprints and geometry, building types and surface areas, and business-related details such as opening hours, industry classification, contact information, website URLs, ratings, and more. The scope is broad, and these datasets are always built to suit specific needs and use cases—from navigation and urban planning to environmental monitoring and resource management.

There are several types of geospatial data, including vector data, time-based data, POI data, and more. In this article, we focus on a dataset showcasing POIs (Points of Interest) and their basic attributes. To provide real-world examples, we feature the headquarters of three well-known European companies: Louis Vuitton, Volkswagen, and TotalEnergies.

These examples highlight how geospatial data is structured within a dataset and is made ready for immediate use in mapping, navigation, or spatial analysis tools. Below are these three examples, along with key geospatial attributes such as addresses, precise coordinates, building geometry, surface area, building types, and more.