Data modeling is hard. Some loosely correlated thoughts and links:

• Model-driven architecture is rigid, at least with the tools as we know them today.
• RDF has a simple basic model but leads to very complex structures, as Adam Bosworth explains.
• Pictures express complex relationships relatively readably, like the picture in this paper. Unfortunately we need to translate the pictures into text in order to use these in software and network protocols.
• The more complex your picture is, the more unreadable your text is.
  
• Text has to be relatively flat to be readable.
  
• References in data formats are like "goto" jumps in programming -- you lose context.
  
• Maybe if data modelers put a little more thought into flattening their models we'd find them easier to use? This may make the models seem less "rich" but "KISS" is good too.
  

I don't know how true all of this is, but I'm learning.

The "relatively flat" observation seems to hold at least some validity in data formats, programs and even books. Experienced programmers, with the help of good indenting, can see quickly that they're within an 'else' statement inside a loop inside another loop inside an 'if' statement, but even experienced programmers screw this up sometimes (and even more experienced programmers flatten out the code by delegating some reasonable piece off to another method). Books are better if there's no more than three (maybe four) layers -- chapter, section, sub-section, and even this much organization requires human-readable text to link from one section to another and summarize what a bunch of sections are going to say.