A bit of background, I've been working in environments next to, and sometimes with, large scale Semantic Graph projects for much of my career -- I usually try to avoid working near a semantic graph program due to my long histories of poor outcomes with them.

I've seen uncountably large chunks of money put into KM projects that go absolutely nowhere and I've come to understand and appreciate many of the foundational problems the field continues to suffer from. Despite a long period of time, progress in solving these fundamental problems seem hopelessly delayed.

The semantic web as originally proposed (Berners-Lee, Hendler, Lassila) is as dead as last year's roadkill, though there are plenty out there that pretend that's not the case. There's still plenty of groups trying to revive the original idea, or like most things in the KM field, they've simply changed the definition to encompass something else that looks like it might work instead.

The reasons are complex but it basically boils down to: going through all the effort of putting semantic markup with no guarantee of a payoff for yourself was a stupid idea.

You can find all kinds of sub-reasons why this was stupid: monetization, most people are poor semantic modelers, technologies built for semantic system generally suck and are horrible (there's pitifully few reasoners built on any kind of semantic data, turns out that's hard), etc.

For years the Semantic Web was like Nuclear fusion, always just a few years away. The promise was always "it will change everything", yet no concrete progress was being made, and the vagueness of "everything" turned out not to be a real compelling motivator for people to start adding semantic information to their web projects.

What's actually ended up happening instead has been the rebirth of AI. It's being called different things these days: machine learning, heuristic algorithms, whatever. But the point is, there's lots of amazing work going into things like image recognition, context sensitive tagging, text parsing, etc. that's finding the semantic content within the human readable parts of the web instead. It's why you can go to google images and look for "cats" and get pictures of cats.

Wikipedia and other sources has also started to look more structured than it previously was, with nice tables full of data, these tables have the side benefit of being machine AND human readable, so when you look for "cats" in google's search you get a sidebar full of semantic information on the entity "cats": scientific name, gestation period, daily sleep, lifespan, etc.

Like most things in the fad driven KM world, Semantic Web advocates are now simply calling this new stuff "The Semantic Web" because it's the only area that kind of smells like what they want and is showing progress, but it really has nothing to do with the original proposal and is simply a side-benefit of work done in completely different areas.

You might notice this died about the same time "Mashups" died. Mashups were kind of an outgrowth of the Semantic Web as well. One of the reasons that whole thing died was that existing business models simply couldn't be reworked to make it make sense. If I'm running an ad driven site about Cat Breeds, simply giving you all my information in an easy to parse machine readable form so your site on General Pet Breeds can exist and make money is not something I'm particularly inclined to do. You'll notice now that even some of the most permissive sites are rate limited through their API and almost all require some kind of API key authentication scheme to even get access to the data.

Building a semantic web where huge chunks require payment and dealing with rate limits (which appear like faults in large Semantic Networks) is a plan that will go nowhere. It's like having pieces of your memory sectioned off behind tolls.

Here's TBL on this in 2006 - http://eprints.soton.ac.uk/262614/1/Semantic_Web_Revisted.pd...

"This simple idea, however, remains largely unrealized."

There's a group of people I like to call "Semanticists" who've come to latch onto Semantic graph projects, not as a technology, but as a religion. They're kind of like the "6 minute ab" guy in "There's Something About Mary". They don't have much in the way of technical idea, but understand the intuitive value of semantic modeling, have probably latched onto a specification of some sort, and then belief caries them the rest of the way "it'll change everything".

But they usually have little experience taking semantic technologies to successful projects (success being defined as not booting up the machine and loading the graph into memory, but actually producing something more useful than some other approach).

There's then another group of Semanticists, they recognize the approaches that have been proposed have kind of dead-ended, but they won't publicly announce that. Then when some other approach not affiliated with the SW makes progress (language understanding AI for example) will simply declare this new approach as part of the SW and then claim the SW is making progress.

The truth is that Doctorow absolutely nails the problems in his essay "Metacrap" http://www.well.com/~doctorow/metacrap.htm

He wrote this in 2001, and the issues he talks about still haven't been addressed in any meaningful way by professionals working in the field, even new projects routinely fall for most or all of these problems. I've seen dozens of entire companies get formed, funded and die without addressing even a single one of these issues. This essay is a sobering measuring stick you can use to gauge progress in the field, and I've seen very few projects measure well against any of these issues.

Semanticists, of both types, are holding the entire field back. If you are working on a semantic graph project of any kind and your project doesn't even attempt to address any of these things through the design of the program (and not through some policy directive or modeling process) you've failed. It's really hard for me to believe that we're decades into Semantic Graph technologies and nobody's bothered to even understand 2.5 and 2.7.

If your plan to fix problems you're experiencing with your project, the reason it isn't producing useful results, is to "continue adding data to it" or "keep tweaking the semantic models" you've failed.

http://semanticweb.com/keep-on-keepin-on_b41339

"The Semantic Web is not here yet."

No, I've rethought this, the SW is not like Fusion, it's more like Communism.