I stumbled across a bit of text that clarified an earlier discussion on tagging:
Hierarchical: indicates a parent-child (vertical) relationship like cat and dog are children of mammals)
Association: indicates a "similar to" (horizontal) relationship like mammals is similar to animals.
Bingo! This is what people think of when they create categories and tags. Categories are hierarchical, and tags are associative. The problem is - they're both right and wrong.
They're right, because this is in fact what categories and tags provide. But they're wrong in the sense that all knowledge is hierarchical, because all human comprehension is based on sets, and sets are inherently hierarchical.
This proves an earlier point. It isn't the case that some knowledge is hierarchical and some isn't. It's just that some topics are members of hierarchies that haven't been defined yet. "Mammals" isn't similar to "animals". Mammals are animals.
"No problem," you rejoin. "That's just a bad example." To which I reply: prove it. Show me an example of an association that relates two topics yet isn't part of a definable hierarchy. By definition, you can't, because the presence of an association automatically implies some set within which both topics belong.
Now, when it comes to pouring this into software, an obvious fact springs to mind: we can't possibly be expected to have a perfectly complete taxonomy available for use within our publishing platform. Instead, we need a system that is flexible enough to let us build as much or as little hierarchical structure as we need, and then to apply "associative" tags for topics that don't fit into our structure. Furthermore, it would be ideal if there was a way to "round up" topics that aren't part of the structure, and fit them in ex post facto.