Yep, the tags, a popular categorising tool still spreading, as an alternative to the age old taxonomy tree structures which I find no better. (But as I supported until doubt set in!)
My favourite take away was Dave's request to the audience:
"What's the odd one out from chicken, cow and grass?"What's your answer? Pretty standard IQ test stuff such...
"Here in the West most of us would say grass but in much of the world they'd say chicken. That's because we're trained to filter by categories; elsewhere they filter for relationships."says Dave, and I admit to the same fault. So much for western dominated IQ tests... heh.
Thing about categorising is that it creates relationships between objects in a indirect way, and thus leaves precision out.
Chicken and Cow are not directly related other than both being members of same groups: "Domesticated animals" or both "farm dwellers" or both being "staple food in many countries", when dead and parted of course.
Hardly precise those relationships, and thus not very valuable as knowledge enhancers.
Adding knowledge to the objects is what it's all about.
If precise and fulfilling you and a system can find the right object at the right time - enhancing productivity, learning, speed, precision and minimising errors and waste of time.
Whatever we're doing to software systems or ways of running anything - using the best possible knowledge enhancers is of utmost importance. Without the best the rest is kind of moot.
Back to the cow.
Cows eats grass. That's useful and pretty simple or what?
Cows lives on farms.
Chicken lives on farms.
All relationships. Semantic N-triples - readable by you and me, and a proper system as well.
Allowing queries like "what eats grass?", "what animals lives in same locations as cows?" or even "what is the most popular car brand among owners of locations with grass eating animals and egg laying animals?".
Nifty eh? And not easy to do with categorising...