Web 3.0:
Machine talk
Feb 02 2011

by tmartin on February 2, 2011

WEB 2.0. You’ve mastered it, right?

You tweet. Your videos post to YouTube. Your resume highlights nestle into a LinkedIn bio. Your high school friends tracked you down on Facebook. You’ve added your favorite cinnamon roll bakery review to Yelp!

This user generated 2.0 social web thing keeps chugging right along. Of course, you try not to think too much about how someone else rakes in advertising dollars off your posts. And you ignore the privacy questions. And your filter skills have gotten pretty darn good or else you’d have drowned in the dreck by now. But it’s all to the good because 2.0 = the future. And you’re smack dab in the middle of it, riding the crest of the trends. Woot, woot!

Uh, hate to burst that trend bubble, but guess what? There’s a new paradigm in town. Web 2.0, say hello to Web 3.0. Looks like we’ve got a new model to master.

Web 3.0 has been bouncing around for a while, but the idea of the web as one big database where machines could share information with other machines and create value for people has been a bit too, well sci-fi-out-there.

As the world at large begins to understand the value of shared data and the idea of sharing information feels less scary, Web 3.0’s little feet seem to be digging in and gaining some traction and its scampering sounds keep showing up in trade industry articles and development trends.

This week, the World Wide Web Consortium (W3C) launched a new working group (http://www.w3.org/2011/rdf-wg/) to update the guidelines of how machines can share information with other machines.

Yes, I hear the screams from those of you who know this stuff – It’s not new! And Web 3.0 is a meaningless term!

You, my well-educated friends, are of course correct. What we are talking about has long been referred to as the Semantic Web.

Papers from the early 2000s, like Integrating Applications on the Semantic Web (http://www.w3.org/2002/07/swint), talk about the potential of enabling computers and people to work in cooperation.

The core concept was there in Tim Berners-Lee’s original proposal to CERN in 1989 (http://www.w3.org/History/1989/proposal.html).

The computer science/philosophical world totally got the phrase Semantic Web. For the rest of us, though, we needed something more prosaic. Easier to pronounce. Like Web 3.0.

People who enjoy the act of thinking for the pleasure of thinking, love the rabbit hole of semantics. Semantics tries to define meaning. Instead of blithely accepting the images and concepts that d-o-g implies, semantics asks why and how that meaning gets applied, and how that interacts and intersects with other symbols.

It’s kind of fun sometimes to think this way, except that I have a sneaking suspicion it might end up with one lying on the ground staring up at the night sky quivering because one no longer knows what is and isn’t real. Meanwhile, the rest of us just accept that the s-k-y is t-h-e-r-e and settle in for a nice evening of popcorn and a movie.

When you make semantics modify web, as in “Semantic Web,” it becomes even more mind blowing. Imagine a world where meaning is embedded in every bit of information. D-o-g becomes more than string of three characters and instead embodies literally and culturally the ‘dog-ness’ within.

Yeah, I know, this makes your brain hurt and you’re probably wondering right about now if I’m the one staring helplessly at the night sky!

OK, so instead, imagine that all the information connected by the web knows about itself. But more than that, imagine that it knows how to understand all the other information out there, including all the possible points of connection between those bits of meaning.


By the time you’re done, you’ve created a map of all the meaning of all the stuff connected by the web. It sounds complex, but mostly it’s just helping machines do what we humans do naturally.

Remember when you were in kindergarten or first grade and you were learning to write sentences? Sometimes you’d get a little pile of words and you’d have to arrange them from a random pile into a sentence that made sense.

To do that, you needed to know something about each word. You also needed to know the relationship the words could have with each other. You needed to know the rules for making a sentence. With those bits of knowledge, you arranged the words to say, “The flower is red” or “The cat drinks milk” or “The cow jumps over the moon.”

With your context knowledge, you could start using these written sentences proactively. You probably figured out pretty quickly that handing an “I love Mommy” note to mommy, even if she hadn’t asked for it, brought a reward, while handing “I love Mommy” to your sister was pointless.

Building the semantic web isn’t that different. We create a shared set of rules and provide a means of creating connection and context. Suddenly we have a sort of gigantic relational database with hooks to applications that make sense to different users.

Of course, the challenge lies in that we humans already have rule sets about meaning and symbols – and the web doesn’t.

That’s where the W3Cs development of the RDF standard comes in. RDF stands for “Resource Description Framework” and it describes a model for data, meaning, and syntax that can be read by machines. It uses XML as its language, providing a tool for independent and unrelated machines to use and exchange data amongst themselves, with meaning.

So what does this all me for us as we play about in our Web 2.0 world of user-generated content and intersecting user-definable applications? It means a new layer of information will be joining our world and that we need to start thinking differently about how we might interact with machines.

The obvious benefits include easier searching and more powerful data mining, but the interesting stuff happens when we push the boundaries.

Hmm, let’s dream a bit … Can machines monitor other machines and push data to us when we need it? Even in a locational on time specific context? (“Sweet corn is 6/$1 at Stop & Shop this week”)?

Can machines perform analysis based on broad concepts and deliver reminders we forget we needed? (“Ah-hem, time to review that auto policy, there’s new options, should I make the payment for you?”)

Can we have conversations with data? (“What kind of pricing are you seeing on this kind of project? Do you think the cost of lumber is going to rise next week and how can I factor that into my bid?”)

Can our data collaborate? (“I see you’ve got 2011 data an I’ve got 2010 data, let’s get together and merge?”)

I kinda’ like the idea of a floating glowing orb that pops up in front of me at my command, that finds what I ask for, offers what it thinks I might need, and reminds me of what I need to do next. The orb works because it combines my contextual needs with the ability to talk to all the information, everywhere.

Right, that last one is going into the science fiction realm … a little bit.

Web 3.0 might not manifest as an floating glowing orb, but it might show up as knowledge agents, business automation tools, or a plethora of other things that can have immediate impact on how move about in the post-digital age.

Semantic sounds esoteric, but Web 3.0 isn’t about gazing hopelessly at the night sky and pondering its meaning. Rather, is about taking emerging capabilities into our own hands, grabbing those machine by the throat, and shaping it all into a new kind of collaboration to do things we could only dream about yesterday.


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