Chaotic Nihilists and Semantic Idealists by Alistair Croll.
From the post:
There are competing views of how we should tackle an abundance of data, which I’ve referred to as big data’s “odd couple”.
One camp—made up of semantic idealists who fetishize taxonomies—is to tag and organize it all. Once we’ve marked everything and how it relates to everything else, they hope, the world will be reasonable and understandable.
The poster child for the Semantic Idealists is Wolfram Alpha, a “reasoning engine” that understands, for example, a question like “how many blue whales does the earth weigh?”—even if that question has never been asked before. But it’s completely useless until someone’s told it the weight of a whale, or the earth, or, for that matter, what weight is.
They’re wrong.
Alistair continues with the other camp:
Wolfram Alpha’s counterpart for the Algorithmic Nihilists is IBM’s Watson, a search engine that guesses at answers based on probabilities (and famously won on Jeopardy.) Watson was never guaranteed to be right, but it was really, really likely to have a good answer. It also wasn’t easily controlled: when it crawled the Urban Dictionary website, it started swearing in its responses[1], and IBM’s programmers had to excise some of its more colorful vocabulary by hand.
She’s wrong too.
And projects the future as:
The future of data is a blend of both semantics and algorithms. That’s one reason Google recently introduced a second search engine, called the Knowledge Graph, that understands queries.[3] Knowledge Graph was based on technology from Metaweb, a company it acquired in 2010, and it augments “probabilistic” algorithmic search with a structured, tagged set of relationships.
Why are we missing asking users what they meant as a third option?
Depends on who you want to be in charge:
Algorithms — Empower Computer Scientists.
Ontologies/taxonomies — Empower Ontologists.
Asking Users — Empowers Users.
Topic maps are a solution that can ask users.
Any questions?