The US example from the site
They map “United States of America” not as a flat Wikipedia-style article, but as interconnected clusters:
Core clusters shown:
- Historical Foundations – origins, colonial period, influences
- Constitutional Formation – 1787 convention, Federalist papers, ratification
- Civil War – causes, key events, aftermath
The twist: These clusters aren’t siloed. They’re cross-linked through themes like:
- Governance → how power structures evolved from colonial charters → Constitution → Reconstruction
- Economy → mercantilism → industrialization → Civil War economic causes
- Society → demographics, culture, slavery debates cutting across all time periods
So if you’re researching the Civil War, the network would also surface relevant constitutional debates and economic policies from earlier clusters, because they’re tagged and linked.
How you’d likely use it
- Topic discovery: Instead of linear reading, you jump between connected ideas. Researching “Federal Reserve”? The network pulls in “Panic of 1907”, “Jekyll Island”, and “Great Depression” clusters.
- Gap finding: See which cross-links are weak. Maybe “Society” links to “Civil War” are strong, but “Governance” links to “Post-war Tech Boom” are missing.
- Team knowledge: In an org, you could map “Product Launch” → clusters for Marketing, Engineering, Legal, with governance links showing approval flows.
Think of it like Obsidian or Roam but with built-in ecosystem thinking — content nodes, but the edges matter as much. The goal is to show how knowledge circulates, not just where it’s stored.
Want me to check if there’s a public demo or tool for it?
