Interesting. I had a shower idea(tm) one morning where the combination of a rating and user-supplied biographical data at the time of the rating (e.g. "I was a novice with Python when I read it") determined a book's effectiveness.
The idea was founded on the tendency that people are skill-biased when rating books. They might dislike a book for being confusing or too easy because it wasn't designed for them at the time of reading. This was an attempt to figure out which books were just bad, and which were only rated bad because they were read without proper experience (or too much).
Ultimately, using community data, a visitor would be able to discover a "bookpath" of great resources that syncs up with their level of skill.
The wiki approach would be great if the data was laid out appropriately. Community-edited wiki might lead to a singular view of what a good path would be.
The benefit of a multi-axis rating system is that you could lay out data using different permutations and add/subtract inputs (e.g. rater's experience at time of rating/age/hell, maybe even personality type). I'm sort of modeling this off of robust scientific questionnaires.
It does seem to require some more user involvement, but nothing a fantastic UI couldn't fix.
I really like this idea, especially if the "bookpaths" converge.. i.e. the ruby path and python path converge to broader topics such as general software development (pragmatic programmer etc.)
The idea was founded on the tendency that people are skill-biased when rating books. They might dislike a book for being confusing or too easy because it wasn't designed for them at the time of reading. This was an attempt to figure out which books were just bad, and which were only rated bad because they were read without proper experience (or too much).
Ultimately, using community data, a visitor would be able to discover a "bookpath" of great resources that syncs up with their level of skill.