# Knowledge Graph A knowledge graph represents entities and the relationships among them as an explicit network. Nodes may be people, documents, concepts, organizations, events, or other addressable things; edges carry typed relationships and often provenance. Bryant's anydata and PeopleLinking work, the Obsidian wiki, and the lexical association systems all contain graph-shaped information. The term should not erase their differences: a document graph, social/entity graph, and lexical association graph have different node and edge semantics. Related: [[wiki/Document Graph|Document Graph]], [[wiki/Lexical Knowledge Graph|Lexical Knowledge Graph]], [[wiki/Information Architecture|Information Architecture]]. ## Simple Reminders, Quotations, and Thoughts > "Rather, the brain of all mammals incorporates a long-distance information sharing system that breaks the modularity of brain areas and allows them to broadcast information globally." > **— Stanislas Dehaene**, *2015, Edge annual question “What Do You Think About Machines That Think?”* [[reminders/Information/Mammalian Brains Broadcast Information Globally by Stanislas Dehaene|Mammalian Brains Broadcast Information Globally by Stanislas Dehaene]] > "But the true role of data is to confirm which answers are the correct ones. If some physicist, or some machine, figures it out they have no way to convince anyone else they have the actual answer." > **— Gordon Kane**, *2015, Edge annual question “What Do You Think About Machines That Think?”* [[reminders/Information/Thinking Cannot Replace Experimental Evidence by Gordon Kane|Thinking Cannot Replace Experimental Evidence by Gordon Kane]]