Graph Hairball
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Knowledge graph system logic, the "things" and "relations between things" that graph theory calls "vertices" (a.k.a. nodes, points, entities, things) and "edges" (a.k.a. links, lines, relations, associations), looks like a big graph hairball as some people call it an example of which you can see here: Why? This common view of a graph is because there has to be some "general view" of the information provided by the graph. This is just like a general view of the information within a relational database is a table ; a set of ROWS and COLUMNS for exactly one table at a time. So what is interesting is that with a graph database the default view is everything in the graph of knowledge. Whereas the default view of everything in a relational database is one table at a time. Further, it does not really matter whether the information that populates your knowledge graph comes from, say, CSV files, Excel, JSON, XBRL, RDF, PROLOG or whateve...