The Map of Human History

You wait an age for a historical Wikipedia map and then two come along at once. Hot on the heels of yesterday's post about Landnotes, we can now explore another Wikipedia-sourced map of human history.

The Globe of History is an ambitious new interactive map that attempts to visualize the entire sweep of human history - 6,000 years of wars, inventions, discoveries, philosophers, political upheavals, and more - on a 3D globe.

Each historical event is mapped using data derived from Wikipedia, resulting in a global atlas of human events that you can explore geographically, chronologically, or thematically. The current mapped categories include:

• Wars
• Battles
• Assassinations
• Inventions
• Discoveries
• Philosophers
• Mass Suicides

Additional layers - including Archaeological Sites, Pandemics, Major Protests, and Peace Accords - will be “coming soon”.

While many history maps pull raw facts from Wikipedia or Wikidata, the creators of Globe of History have built a multi-stage pipeline to turn this information into structured, readable narratives. Using AI, this system expands the raw data into more detailed historical summaries, which are then cross-referenced using AI-driven fact-checking to double-check the generated text.

Representing history on a map is not always easy. Events often span continents, unfold over centuries, or take place at locations that are uncertain. Globe of History accounts for these challenges in several ways:

• Location Pinning: For sprawling historical events such as the Silk Road or World War I, the map chooses a representative epicenter - a key battle, a key city, or an important treaty site.
• Uncertain Coordinates: When precise sites are unknown, city or country centroids are used as stand-ins for historical locations.

The Globe of History also acknowledges the inherent biases in documented history - particularly the overrepresentation of Europe, the U.S., and well-documented ancient civilizations. The team plans to incorporate sources beyond Wikipedia to improve the geographical balance of the dataset.