digraphs-with-text

Graphs (networks, webs) are a data structure we have not exploited enough. Tons of research is going into using graphs for artificial intelligence, and for understanding human intelligence (as in this article). But what about using knowledge graphs to augment human intelligence, like a prosthetic? This is the power of Google search. It uses a knowledge graph that models the world (with an emphasis on the internet). The graph is big, but the view of it offered to users is minuscule -- in part to keep the interface as simple as possible, and in part for economic reasons. There is open source software that lets people keep their own knowledge graphs. In Semantic Synchrony [1] you can keep a knowledge graph and merge it with others' knowledge graph. Joshua Shinavier (who wrote Semantic Synchrony) and I share a graph with over 400,000 nodes, a

Rather than a sharp distinction between trusted users and everyone else, or content and non-content, or even between reading and writing, I believe what we need is the more quantum experience of a knowledge graph. One with an easy semantics for creating and navigating nested relationships. It would let users search for, say, "Statements about [topic] which [set of users] agrees on," or "Arguments against [hypothesis]," or "Examples of, stories about, and implications of [principle]", or "Statements which readers judged useful for [goal]." I wrote a demonstration program[1] that does this. I hope to attract more developers. [1] https://github.com/JeffreyBenjaminBrown/digraphs-with-text