How Do We Roll Out The Semantic Web? Paradoxically, the fast track may involve getting help from billions of people who know nothing about the Semantic Web and have no interest in it.

Challenges with current approaches

Most of the current approaches to building the Semantic Web focus on content. We create semantic representations of existing assets such as databases, documents, and social media. Machines “read” this knowledge and execute tasks on behalf of consumers. In the Semantic Web world, the approach is content first, consumers second.

Unfortunately, semantifying content is proving to be an extraordinarily daunting task. When we expand the scope of the problem beyond our existing content assets to include knowledge generally, in all its subjective and boundless glory, the challenges of a content-first approach becomes clear. We need alternative strategies, and more importantly, many hands on the problem. (more…)

Web 2.0 is social: many hands make light work. In stark contrast, Web 3.0 is industrial: the automation of tasks displaces human work. But trite definitions won’t prepare us for change. Whatever you call it, our information economy is in the midst of an Industrial Revolution. And if you don’t place the Web within the frame of industrial manufacturing, you won’t see the real disruptive change coming.

This story reads much like the first Industrial Revolution. Artisans and skilled tradesman used to create everything by hand. Then, through the emergence of a handful of technical innovations, came the age of mass production. It was a profound turning point in human history, affecting every aspect of daily life.

Today, most content is still created by hand, the best of it by highly skilled artisans drawing on centuries of scholarship and experience. Recently, we’ve seen significant innovations in social approaches to content creation. But Web 3.0 industrialization takes content manufacturing to an entirely different level. Instead of users manually creating content, machines automate the heavy lifting. Consumers simply push the buttons and get stuff done. Think spinning wheels versus textile mills.

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We’re only a month away from the launch of our thought networking service. On this blog, I’ve outlined our vision of thought networking as a new category of semantic applications. With thought networking, we want to help consumers effortlessly collect their thoughts and bend the Internet around them. Leading up to our launch, I want to summarize our vision for this service and our motivations for creating it.

Addressing a Pervasive Problem

The problem with today’s Internet is that it is imposed on consumers. Information is organized for them in advance, without their input. Consumers are treated not as individuals but as amorphous collections of audiences. Producers spend massive amounts of money trying to guess what their audiences need, and compensate for the gaps with monolithic websites and complicated tools to sift through it all.

A much better approach would put the horse in front of the cart, allowing individual consumers to dictate how the information should be organized for them. Simply ask them, “What are you thinking about?” and make those thoughts the organizing force behind it all. Computers could then wield these concrete representations of our thoughts to reorganize and reconstitute the information for each individual. Producers save money; consumers get the simple, made-to-order Web they deserve.

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Our thoughts are fleeting and immaterial, this mysterious stuff that’s locked away in our heads. Painstakingly, we collect our thoughts and transform them into words and documents. This transformation from thought into action is time-consuming and expensive. Thinking is a decidedly “offline” and manual process.

What would happen if you could instead make your thoughts tangible and concrete? What if you could collect your thoughts as readily as you can search online? What if your thoughts could self-organize around your tasks while you’re off doing other things? Thought networking is the idea that’s driving our efforts at Primal Fusion to explore these big questions.

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The Semantic Web has a branding problem: It was built to manage data, not semantics. Somewhere along the line, insiders renamed it the “Data Web”. That was a great move for Web researchers, but what will the semantics crowd do with the name? Just as “semantics” was misplaced in the Data Web, “web” is misplaced in our vision of a global semantic network. The Semantic Web won’t act like a web at all.

The reason is that form must follow function and “web” is the wrong form for semantics. Do you remember why you stopped using the Yahoo Directory and switched to Google? Both provide lists of Web pages organized by categories. The difference is that search engines involve you in the creation of those categories through your queries. When search engines became comparable to the directories in assembling relevant lists, there was no going back. The form of a directory, as a largely static structure, is incompatible with the function of search.

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The vast majority of semantic technologists are directing their efforts to search. It’s an important use of their talents; search is a hard problem worth solving. But it seems to me that we need to take a broader view. Semantics is the stuff of thought, of meaning, of our most personal and deeply held beliefs. A fully realized semantic web will be much more than “better search”. But the future is hard to imagine. We need concrete examples of semantic applications to demonstrate the potential and fuel our imaginations.

So as a glimpse into this future, consider the world’s first mainstream semantic web: Wikipedia. Wikipedia is most often celebrated as the poster child of Web 2.0. As a social application, this is most certainly true. But its output, its content, may be more illustrative of Web 3.0 semantics. Its articles are abstractions: they summarize a huge body of content down to only the essential aspects of each subject. By maintaining organizational standards and templates, it has become machine-readable (derivatives such as DBpedia and many other research projects make it explicitly so). And the subject matter of Wikipedia is clearly the stuff of thought. Semantic representation and encyclopaedic content have a deep and obvious kinship.

These technical attributes put Wikipedia in the semantics camp. Web 2.0 principles may be driving Wikipedia’s prodigious output, but Web 3.0 semantic qualities are driving the phenomenal mainstream consumption of the information. If Wikipedia is truly illustrative of semantic data, then insights into Wikipedia’s consumption may point to killer applications of semantics.

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Content is king, an annoyingly loud, ostentatious, and over-bearing king. I’m hunting for a new car and I’m drowning in content: auto-makers’ websites, reviews, test reports, consumer opinions, and dealer listings. I’ve retrieved hundreds of pages in total, costing me countless hours of time. The amount of useful information I’ve extracted is minuscule by comparison. I care about a few precious details of safety, fuel economy, and the overall value. The rest is just noise.

What makes this car shopping so painful is that the content is not organized based on my interests. It’s organized by the publishers. Unfortunately, reading about cars is not the task at-hand. I simply want to find my dream vehicle (if I can call a safe, economical, and value-priced vehicle a dream.)

In my last post, I argued that we need to stop organizing content for people and start helping them consume content to get tasks done. Semantic data figures prominently in that. Today, semantics is a second-class citizen, subordinate to content. But in this new world of task-oriented information, semantics may challenge content as the king of our online attention.

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The Web suffers a fundamental problem. Search is a symptom of it. Surfing is a symptom of it. Even the website itself is a symptom of it. The problem is that content is organized for you, in advance. Pre-packaged content is like ordering off the menu at a restaurant. Sometimes it’s convenient, sometimes it’s just what you want, but many times, it’s a difficult choice to make. The Web wants to become made-to-order.

Search certainly helps. If I want to order off the menu, it’s great to have access to lots of restaurants and lots of menus. User-generated content is great, too, if you like to cook. But I don’t want to access content or create content, I want to consume it to get stuff done.

No one retrieves content for the sake of retrieving content; they have a deeper purpose in mind. “I need to create a report for my boss.” “I need to plan a trip for my family.” “I want to be entertained.” We’re task-oriented. All the intervening steps amount to the bill, tax, and gratuity. And since most tasks require us to visit many different sites, the overall cost is extraordinary.

A made-to-order Web would spare us these costs. If you’re ordering a specific task, much of the legwork can be delegated to machines. Computers are becoming increasingly adept at analytical tasks. They can break down content into bite-size pieces for our consumption. They are also capable of synthetic tasks, building the content back up into new forms. These types of analysis and synthesis tasks enable made-to-order.

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