There’s a reason that the world fully embraced HTTP but not Gopher or Telnet or even FTP. That’s because the power of the Internet is best expressed through the concept of a network, lots of interlinked pieces that make up something bigger rather than tunnels and holes that end in a destination.

The World Wide Web captured people’s imaginations, and then everything changed.

I was reminded of this while reading a recent interview with Tim Berners-Lee (via TechCrunch). He talked a bit about the power of linking data:

“Web 2.0 is a stovepipe system. It’s a set of stovepipes where each site has got its data and it’s not sharing it. What people are sometimes calling a Web 3.0 vision where you’ve got lots of different data out there on the Web and you’ve got lots of different applications, but they’re independent. A given application can use different data. An application can run on a desktop or in my browser, it’s my agent. It can access all the data, which I can use and everything’s much more seamless and much more powerful because you get this integration. The same application has access to data from all over the place…

Data is different from documents. When you write a document, if you write a blog, you write a poem, it is the power of the spoken word. And even if the website adds a lot of decoration, the really important thing is the spoken words. And it is one brain to another through these words.”

Data is what matters. It’s a point of interest in a larger context. It’s a vector and a launchpad to other paths. It’s the vehicle for leverage for a business on the Internet.

What’s the business strategy at the data layer?

I have mixed views on where the value is on social networks and the apps therein, but they are all showing where the opportunity is for services that have actually useful data. Social networks are a good user interface for distributed data, much like web browsers became a good interface for distributed documents.

But it’s not the data consumption experience that drives value, in my mind.

Value on the Internet is being created in the way data is shared and linked to more data. That value comes as a result of the simplicity and ease of access, in the completeness and timeliness, and by the readability of that data.

It’s not about posting data to a domain and figuring out how to get people there to consume it. It’s about being the best data source or the best data aggregator no matter how people make use of it in the end.

Where’s the money?

Like most Internet service models, there’s always the practice of giving away the good stuff for free and then upselling paid services or piggybacking revenue-generating services on the distribution of the free stuff. Chris Anderson’s Wired article on the future of business presents the case well:

“The most common of the economies built around free is the three-party system. Here a third party pays to participate in a market created by a free exchange between the first two parties…what the Web represents is the extension of the media business model to industries of all sorts. This is not simply the notion that advertising will pay for everything. There are dozens of ways that media companies make money around free content, from selling information about consumers to brand licensing, “value-added” subscriptions, and direct ecommerce. Now an entire ecosystem of Web companies is growing up around the same set of models.”

Yet these markets and technologies are still in very early stages. There’s lots of room for someone to create an open advertising marketplace for information, a marketplace where access to data can be obtained in exchange for ad inventory, for example.

Data providers and aggregators have a huge opportunity in this world if they can become authoritative or essential for some type of useful information. With that leverage they could have the social networks, behavioral data services and ad networks all competing to piggyback on their data out across the Internet to all the sites using or contributing to that data.

Regardless of the specific revenue method, the businesses that become a dependency in the Web of data of the future will also find untethered growth opportunities. The cost of that type of business is one of scale, a much more interesting place to be than one that must fight for attention.

I’ve never really liked the “walled garden” metaphor and its negative implications. I much prefer to think in terms of designing for growth.

Frank Lloyd Wright designed buildings that were engaged with the environments in which they lived. Similarly, the best services on the World Wide Web are those that contribute to the whole rather than compete with it, ones that leverage the strengths in the network rather than operate in isolation. Their existence makes the Web better as a whole.

Photo: happy via

I have only one prediction for 2008. I think we’re finally about to see the useful combination of the 4 W’s - Who, What, Where, and When.

Marc Davis has done some interesting research in this area at Yahoo!, and Bradley Horowitz articulated how he sees the future of this space unfolding in a BBC article in June ‘07:

“We do a great job as a culture of “when”. Using GMT I can say this particular moment in time and we have a great consensus about what that means…We also do a very good job of “where” - with GPS we have latitude and longitude and can specify a precise location on the planet…The remaining two Ws - we are not doing a great job of.”

I’d argue that the social networks are now really honing in on “who”, and despite having few open standards for “what” data (other than UPC) there is no shortage of “what” data amongst all the “what” providers. Every product vendor has their own version of a product identifier or serial number (such as Amazon’s ASIN, for example).

We’ve seen a lot of online services solving problems in these areas either by isolating specific pieces of data or combining the data in specific ways. But nobody has yet integrated all 4 in a meaningful way.

Jeff Jarvis’ insightful post on social airlines starts to show how these concepts might form in all kinds of markets. When you’re traveling it makes a lot of sense to tap into “who” data to create compelling experiences that will benefit everyone:

“

• At the simplest level, we could connect while in the air to set up shared cab rides once we land, saving passengers a fortune.
• We can ask our fellow passengers who live in or frequently visit a destination for their recommendations for restaurants, things to do, ways to get around.
• We can play games.
• What if you chose to fly on one airline vs. another because you knew and liked the people better? What if the airline’s brand became its passengers?
• Imagine if on this onboard social network, you could find people you want to meet - people in the same business going to the same conference, people of similar interests, future husbands and wives - and you can rendezvous in the lounge.
• The airline can set up an auction marketplace for at least some of the seats: What’s it worth for you to fly to Berlin next Wednesday?

“

Carrying the theme to retail markets, you can imagine that you will walk into H&M and discover that one of your first-degree contacts recently bought the same shirt you were about to purchase. You buy a different one instead. Or people who usually buy the same hair conditioner as you at the Walgreen’s you’re in now are switching to a different hair conditioner this month. Though this wouldn’t help someone like me who has no hair to condition.

Similarly, you can imagine that marketing messages could actually become useful in addition to being relevant. If CostCo would tell me which of the products I often buy are on sale as I’m shopping, or which of the products I’m likely to need given what they know about how much I buy of what and when, then my loyalty there is going to shoot through the roof. They may even be able to identify that I’m likely buying milk elsewhere and give me a one-time coupon for CostCo milk.

Bradley sees it playing out on the phone, too:

“On my phone I see prices for a can of soup in my neighbourhood. It resolves not only that particular can of soup but knows who I am, where I am and where I live and helps me make an intelligent decision about whether or not it is a fair price.

It has to be transparent and it has to be easy because I am not going to invest a lot of effort or time to save 13 cents.”

It may be unrealistic to expect that this trend will explode in 2008, but I expect it to at least appear in a number of places and inspire future implementations as a result. What I’m sure we will see in 2008 is dramatic growth in the behind-the-scenes work that will make this happen, such as the development and customization of CRM-like systems.

Lots of companies have danced around these ideas for years, but I think the ideas and the technologies are finally ready to create something real, something very powerful.

Photo: SophieMuc

What is it that makes my favorite online services so compelling? I’m talking about the whole family of services that includes Dopplr, Wesabe, Twitter, Flickr, and del.icio.us among others.

I find it interesting that people don’t generally refer to any of these as “web sites”. They are “services”.

I was fortunate enough to spend some time with Dopplr’s Matt Biddulph and Matt Jones last week while in London where they described the architecture of what they’ve built in terms of connected data keys. The job of Dopplr, Mr. Jones said, was to “surface coincidence”.

I think that term slipped out accidentally, but I love it. What does it mean to “surface coincidence”?

It starts by enabling people to manufacture the circumstances by which coincidence becomes at least meaningful if not actually useful. Or, as Jon Udell put it years ago now when comparing Internet data signals to cellular biology:

“It looks like serendipity, and in a way it is, but it’s manufactured serendipity.”

All these services allow me to manage fragments of my life without requiring burdensome tasks. They all let me take my data wherever I want. They all enhance my data by connecting it to more data. They all make my data relevant in the context of a larger community.

When my life fragments are managed by an intelligent service, then that service can make observations about my data on my behalf.

Dopplr can show me when a distant friend will be near and vice versa. Twitter can show me what my friends are doing right now. Wesabe can show me what others have learned about saving money at the places where I spend my money. Among many other things Flickr can show me how to look differently at the things I see when I take photos. And del.icio.us can show me things that my friends are reading every day.

There are many many behaviors both implicit and explicit that could be managed using this formula or what is starting to look like a successful formula, anyhow. Someone could capture, manage and enhance the things that I find funny, the things I hate, the things at home I’m trying to get rid of, the things I accomplished at work today, the political issues I support, etc.

But just collecting, managing and enhancing my life fragments isn’t enough. And I think what Matt Jones said is a really important part of how you make data come to life.

You can make information accessible and even fun. You can make the vast pool feel manageable and usable. You can make people feel connected.

And when you can create meaning in people’s lives, you create deep loyalty. That loyalty can be the foundation of larger businesses powered by advertising or subscriptions or affiliate networks or whatever.

The result of surfacing coincidence is a meaningful action. And those actions are where business value is created.

Wikipedia defines coincidence as follows:

“Coincidence is the noteworthy alignment of two or more events or circumstances without obvious causal connection.”

This is, of course, similar and related to the definition of serendipity:

“Serendipity is the effect by which one accidentally discovers something fortunate, especially while looking for something else entirely.”

You might say that this is a criteria against which any new online service should be measured. Though it’s probably so core to getting things right that every other consideration in building a new online service needs to support it.

It’s probably THE criteria.

One of the more interesting sciences, in my mind, is how information relevance is both determined, surfaced and then evolved.

In Fred Wilson’s recent Cautionary Techmeme Tale he argues that making news popular takes away its social context and therefore becomes meaningless. He found Techmeme more useful when its sources more closely resembled his network of friends:

“For years, I’ve been using curators to filter my web experience…Techmeme has been the killer social media curator for my world of tech blogs. Lore has it that it was created using Scoble’s OPML file. It doesn’t matter to me if that’s true or not, I love that story. Because my OPML file was unusable until I found Techmeme and after that I stopped reading feeds and started reading curated feeds.”

This feeds into a larger argument about why pop culture and the art of being or becoming popular can be a bad thing. Not long ago I was inspired by the movie “Good Night and Good Luck” to dive into this idea myself:

“The real problem with popularity-driven models is that they reduce both the breadth and depth of the sources, topics and viewpoints being expressed across a community. Popularity-driven models water down the value in those hard-to-find nuggets. They normalize coverage and create new power structures that interesting things have to fight through.”

This is exactly why personalization, recommendations and social media technologies really matter. They can solve this problem of creating conformist media consumption practices by creating relevance through networks of people rather than through networks of commercial institutions.

I haven’t used My Yahoo! as much as I’d like, but there is a simple function in it that I love which could ultimately create amazing benefits for people who want a human filter for the Internet. It’s called “Top Picks”.

“The Top Picks module automatically highlights stories from your page, based on the articles you have recently read on My Yahoo! The more stories you click on, the more you will see this module reflect your interests.”

Actually, the technology beneath it is not so ’simple’ but the application of it here makes so much sense that it feels like it’s simple when you watch it work. It works by using implicit behaviors. I don’t have to tell it what I like. It learns.

If it could also show me what my social network is tapped into right now, then the experience would feel nearly complete.

Media researchers will note here that people need pop culture to feel connected to a greater whole. I believe that’s true, too. Television is an amazingly powerful community builder.

But I would gladly trade a powerful singular social voice tied together by networks of distribution ownership for a less unified but still loosely connected network of pop culture tied together by my personal activities and my social connections.

Jay Rosen has an interesting post on the failure of AssignmentZero, an effort to build a publicly funded crowdsourced news organization.

Among the many lessons, he keeps coming back to motivation and incentive.

“A well managed project correctly estimates what motivates people to join in, what the various rewards are for participants, and where the practical limits of their involvement lie.

…amateur production will never replace the system of paid correspondents. It only springs to life when people are motivated enough to self-assign and follow through.”

The idea wasn’t fundamentally broken, in my mind. Crowdsourced news is very powerful. As Derek Powazek said,

“At its best, crowdsourcing is about expanding the walls of the newsroom to the internet, giving an opportunity to people with real experience to share their expertise. This is a point that’s often lost on people who are just looking to make a quick buck on Web 2.0.”

More than anything else, I suspect that AssignmentZero failed because there weren’t any readers. Motivation wouldn’t have been a problem with a NYTimes-sized audience.

To date, I’ve never seen a better explanation of the motivations in collaborative online experiences than Yochai Benkler’s paper called Coase’s Penguin. One of my favorite excerpts from that is where he warns against paying for contributions from the community:

“An act of love drastically changes meaning when one person offers the other money at its end, and a dinner party guest who will take out a checkbook at the end of dinner instead of bringing flowers or a bottle of wine at the beginning will likely never be invited again.”

There are as many motivations as there are contributors in a shared media project. What holds them together is more art than science. Some of that art includes good timing and luck. But it also requires a unique kind of commitment and salesmanship from the leaders of the project.

I’ve begun to wonder if the tipping point happens when the confluence of the community size, the ROI to the contributors and the depth of the trust relationship with the company or the brand creates more value than the sum of the parts. Maybe the science of collaboration services can be found by quantifying the meaning of the relationships between those elements: size, cost, benefit and trust.

Or it could also be that the secret sauce inside the Craig Newmarks, Stewart Butterfields and Jimmy Waleses of the world is much more complicated and nuanced than anyone realizes.