This a personal impression based on actual conversations, not based on the attendance list.

• Serial entrepreneurs seeking their next big venture. I spoke to two of them. What was interesting was that both were very successful, knew very little about the semantic Web (they were there to learn), and were extremely open to seeking where the opportunities lie. In other words, they were at the formative stages of their ventures.
• Semantic Web pioneers. Conference organizers made it very clear they did not want an echo chamber of SemWeb experts talking to SemWeb experts. They wanted SemWeb experts to connect with business people who had problems that needed solving. That seemed to be happening.
• Connectors, money guys, promoters. There were quite a few of these, usually a sign that something is either happening or about to happen.
• Publishers. Well, the conference was in New York, so you would expect publishers, of all types, both big and small.
• Semantic Web ventures that are already getting traction. Most of these appearances took the form of speakers and conference sponsors.

Where Is the Value in this Next Phase of the Web?

This is what the serial entrepreneurs were asking. Here is my view after a few days of reflection. Three big market opportunities will see semantic Web technology used in different ways in the near term:

• Scientific/technical/medical (STM) publishing,
• Market research information created from random social media chatter,
• Improved advertising relevance.

Each of these deserves closer inspection.

Scientific/Technical/Medical Publishing

Open-source data will disrupt traditional data publishing -- in particular and immediately STM publishing -- similar to how open-source software disrupted the software industry. STM publishing is a market worth more than $10 billion, so this is significant. Similar forces will play out in financial, legal, and other data-rich industries, but STM is likely to be in the vanguard for the following reasons:

• Everybody in the eco-system wants this to happen except the current publishers. Governments and institutions that fund research want it to be freely available. The authors are not like book authors; they don't get paid per book sold. They want wide distribution and peer recognition.
• There are huge benefits to the raw data being machine-readable, not the least of which is that the data can be used for further analysis, rather than be squeezed into the artificial format designed for print journal distribution.
• Scientists and researchers will use the semantic Web tools that consumers and business people consider too complex (until some great UI designers take on this challenge).

As in any market transition, there will be winners and losers.

Winners:

• Scientists and researchers,
• (Indirectly) everyone who benefits from the products created by scientists and researchers,
• New publishers (or some other entity) that add enough value to free source data that they are still able to charge for it.

Losers:

• Traditional STM publishers who cling too tightly to their current cash cow and so cannot effectively ride the next wave.

After it goes through the STM sector, this wave will crash through other data-rich publishing markets, such as:

• Finance
• Law

Market Research Information Created from Social Media Chatter

The Web 2.0 era has unleashed an enormous amount of social media chatter. These conversations are inconsequential to all except the participants... until, that is, they are aggregated, structured, and analyzed. This is not simple to do, as security and intelligence agencies have long understood. When you can record any conversation you like, you quickly find that discovering something useful is really hard. Historically, only intelligence agencies have had access to this volume of chatter. And the public has only had access to conversations between "important" people about important subjects. Multiply the chat you and I had about what we had for breakfast a few million times, and someone might get interested, specifically someone in the market research industry.

Market research is a large industry. Obtaining explicit data about people by getting them to fill in surveys is becoming increasingly hard and expensive. Perhaps gathering data about what people are actually talking about and deriving something useful from that would be easier.

This is not likely that elusive native revenue model for social media. But it could be a useful add-on revenue stream. Semantic Web ventures that can pay social media sites for raw data, extract that data, add meaning, and sell it to marketers could do very well. That won't be easy to do well, though.

Improved Advertising Relevance

AdWords represented a massive advance in advertising relevance. It changed the advertising and media industries beyond recognition and made Google the most powerful technology company on the planet.

But is this as far as we can go with advertising relevance? Almost certainly not. Whether Google or another venture leverages the semantic Web, there is little doubt that semantic Web technology will improve advertising relevance. Quite how to do this is the subject of another post.

Disclosure: Web 3.0 was a sponsor of ReadWriteWeb, but we have no other financial interest in the event.

At this month's DEMO 09 conference, one of the most apparent trends was the emergence of several new intelligent web services. In this transitional period between Web 2.0 and Web 3.0 (or whatever it is that comes next), the tools of the future are just now being revealed. Although at first glance some of these services and applications may seem somewhat incomplete, in many cases they actually represent years' worth of work to have reached the point they're at now. These are no simple Web 2.0 applications; these are highly complex and intelligent tools of tomorrow's smarter web.

A.I.-Powered Shopping (Gazaro)

Gazaro is a new service that lets you make what they call "personal sales fliers." Instead of sifting through the local paper to find the latest deals, you just tell Gazaro what sorts of products you're interested in. The service then scours the web for the best deals and presents its findings in a clean, easy-to-read interface. But Gazaro isn't simply a price comparison engine. It's a really smart one.

Gazaro knows that a "camera" is a "camera" or that an "LCD" is an "LCD." It's not doing simple keyword matching, it really understands the difference. In other words, you'll never get results for a camera lens or camera accessories when you're searching for just a camera because Gazaro knows those are not the same things.

The reason it can differentiate between items is because it's powered by Artificial Intelligence (A.I.) on the back end. In this case, "A.I." is no buzzword - the company was incubated by Apption Software who had developed A.I. technology for use in the enterprise. They realized that the same technology could deliver value in a consumer application as well, and from there came Gazaro.

When Gazaro goes out and crawls the internet, it compares the items it finds to the items it already knows in order to determine what exactly the new items are. If it encounters something it doesn't know, it makes an educated guess using its A.I. "brain." And the more it crawls, the more it learns.

After identifying what an item is, Gazaro then determines if the item found is actually a good deal. How good of a deal it is or not is represented with the "Gazaro Deal Score." These deal ratings are based on Gazaro's knowledge of historical prices, how often an item goes on sale, what other retailers are selling it for now and what they've sold it for in the past. All that analysis is done using the A.I. technology in order to rate the deal on a scale from 1 to 10, with 10 being the best deal.

To the consumer using the system, the complexity of what the A.I. is doing is all hidden behind the scenes. The end user only sees a simple interface where they can enter in the items they're shopping for and then find the best prices. Gazaro can also alert users to new sales and deals using email, RSS, or Twitter. At the moment, Gazaro is for consumer electronics shopping only, but in time the system could expand and learn more product categories.

Understanding Intentions (Primal Fusion)

Another company of interest is Primal Fusion whose new "thought networking" service is a semantic technology platform designed to help you research the subjects that interest you. Unfortunately, "thought networking" is a buzzword-sounding phrase that doesn't really convey what the system does. Primal Fusion essentially is an alternative to doing traditional web searches when you want to learn about a particular topic.

Once signed up for the Primal Fusion service, you enter in your topic in the search box provided and you'll see a tag cloud of words appear which are relevant to the word you initially searched on. You can either select those words by checking them or you can click on the individual words to further drill down into a more specific aspect of the original topic.

In the example they demonstrated today, a student researching climate change might see a tag cloud featuring words and phrases like "pollution," "co2," "greenhouse gases," etc. In addition, the service can also return relevant photos to your topic from sites like Flickr.

Initially, Primal Fusion searches Wikipedia to deliver the tag cloud, but once you have your specific interests checkmarked you can then change a drop-down box to search the web instead. This web searching is done courtesy of a Yahoo BOSS integration and it's here where Primal Fusion one-ups a normal search engine. Instead of just returning the top 5 or 10 results on the original keyword, it sifts through all the results found and returns only those relevant to your specific interests - even if those results would have been pages deep on a normal search query. Whatever Primal Fusion retrieves can then be extracted to a web page, document, or RSS feed. At the moment, Primal Fusion only extracts to web pages - files and feeds will come later. The web pages created by the service are public sites representing your research around a particular topic and are filled with links and images relevant to your query.

Because Primal Fusion comes off as somewhat of a confusing mind-mapping tool, many folks will probably miss the point: Primal Fusion is infrastructure, not an application. The way it understands the relationships between words and phrases and how it can then extract the most relevant search results based on that understanding is what's most important about the company's technology.

Remember: This Is Only the Beginning

If you go out and try most of the services we've profiled in this series, you might walk away feeling a bit disappointed. You'll probably be thinking of all the things the service doesn't do but that you wished it could. Or perhaps you'll find the UI unappealing or the recommendations provided somewhat incomplete. However, It's important to understand that many of these services aren't ready for mainstream use just yet. Instead, they represent the beginnings of tomorrow's web - a web that better understands the data it contains. And by better understanding itself, the new intelligent web of the future can then better understand and serve you.

We're moving beyond the days of a simple search box in which you type a query and get a list of results. Today, companies are trying to build a smarter web - one that understands what things are, how they relate, and perhaps most importantly, what things you're going to like. But has Web 3.0 arrived in its full semantic glory? No, not yet. But it's clear we are getting closer than ever before.

To begin, there's the seemingly minor announcement from Xmarks, the company formerly known as Foxmarks, but now rebranded thanks to their multi-browser support. Xmarks has introduced additional features to their bookmark synchronization product which include things like site suggestions and smarter search. By leveraging their large stash of data (600 million bookmarks), Xmarks is now able to recommend sites right within your search results. This is done by placing an Xmarks icon next to those results which are most popular, meaning most bookmarked, on their service. Also, when you visit a web site and click the Xmarks icon in your address bar, Xmarks will return a list of sites similar to the one you're currently browsing.

The data used to deliver these recommendations and suggestions are anonymized - a good thing considering that our browser bookmarks are often the ones we have specifically chosen not to share with others. For bookmarks to become recommended in this fashion, they must be fairly popular on the service - a level that's determined by the number of times saved as a percentage within a particular category.

In a way, what Xmarks is doing is very similar to what StumbleUpon's browser extension does too. Like Stumble, Xmarks annotates our search results highlighting those that may be of value to us. Yet Xmarks takes it a step further by discovering related sites, too.

The Smarter Tracking Tool (Evri)

Another company revealing new innovations here at DEMO 09 is Evri, a semantic search engine which understands what's called "natural language." Evri knows the different parts of a sentence (subject, verb, object) and it knows how those parts are connected to each other.

Although still too raw to be your main search engine, Evri has a new "Collections" feature which lets you follow topics (aka search queries) that are of interest to you. After returning a list of search results which include Wikipedia entries, news articles, videos, and images, you can click the star labeled "Follow this" to continue to track that topic. What's missing from this feature, though, is an alerting system which will inform you of updates via email or RSS. However, the company says that's coming later on.

Evri is also branching out from being a web destination alone by introducing Evri widgets which can now be seen in action on the Washington Post's web site. These widgets parse the content on the page to deliver smart recommendations of similar articles both on the site itself as well as elsewhere on the web. 

Another new feature launching now is Evri's browser toolbar. By clicking on a button next to the Evri search box in the toolbar, the people, places, and things on a web page are highlighted. Click on these items and pop-ups appear with more information about the keyword, what's related to the topic plus news, images, and videos.

This additional layer of information on top of standard text makes browsing the web and reading articles a deeper and richer experience. No longer do you need to perform web searches in a separate window to understand definitions, context, and meaning. Instead, Evri's toolbar adds an intelligence to the web that was never there before. It's clear that the company is still working towards making that additional layer more accurate and more relevant, though, but conceptually the idea is solid.

The RSS Reader That Learns (Ensembli)

Ensembli, an RSS reader of sorts, takes a different approach to tracking topics than Evri does with its "Collections" feature. Where Evri's UI can sometimes feel a bit cluttered with its multimedia results, Ensembli's interface is simple - you just type in a topic and it will continue searching for new articles related to what you entered. But this reader doesn't simply pull information for you - it learns what you like. Every time you read, ignore, or discard a story, Ensembli gets to know your tastes a  little bit better.

While this feed reader is far too simplified for RSS junkies like us, it's easy to see how Ensembli could be a good introductory tool for RSS beginners. Still, the sources it returns sometimes seem lacking and it's hard to say if this will ever be any more useful that a simple Google Alert, for example. Nevertheless, it's not really the feed reading itself which makes Ensembli intriguing, it's the learning element. Whatever algorithm is at work behind the scenes figuring out your likes and dislikes is what's the most important aspect of this new technology.

Getting Smarter...Little by Little

Taken by themselves, the above announcements may have seemed more evolutionary than revolutionary, but look at them within a broader scope and you can see a pattern beginning to develop. In this transitional period from Web 2.0 to Web 3.0, we're starting to see tools and services that aim to expand upon the traditional search experience in order to deliver us to a more intelligent web. On this new web, we're moving beyond SEO and PageRank to determine relevance and instead are seeing new technologies develop that better understand meaning, context, and personal preferences.

Stayed tuned...part 2 of "The Smarter Web" will continue tomorrow.

With the extraordinary growth of the Internet and the interlinking of information that the social Web has brought with it, it's time to examine the footprints we leave on the Web as we move into the future that promises to "throttle the 'wisdom of the crowds' from turning into the 'madness of the mobs,'" as described so eloquently by Jason Calacanis.

With Internet usage growing at a remarkable pace it comes as no surprise that comScore recently rated Google as the most popular Internet property in the world, attracting over 777.9 million visitors as of December 2008. Not surprising either is the growth of social and news sites. According to Compete some of the top social sites attracted visitors in the millions during December 2008:

• FaceBook: 59 million visitors
• MySpace: 59 million visitors
• Digg: 33 million visitors
• Twitter: 4.4 million visitors

This growth can be contributed in part to the media as they realize the benefits of instant access to an enormous well of information that the Web provides. As media folk are becoming increasingly tech savvy, they're realizing results from search engines are often lacking. In an effort to gain as much insight into specific topics they are now turning to social sites for research.

Interconnected on the Web

While it's exciting to live in an ever connected and always on world, the flip side that we have to accept is that we also live in a world where information is becoming increasingly interlinked. Today it is relatively simple to follow footprints on the Web if we want to track both people and brands.

For instance, take a look at my public profile on Twitter and you'll notice I can also be found on other sites: BlogWell, ReadWriteWeb and The Drill Down. Visit BlogWell and you'll notice I can be found at WebMama and TechTalkRadio. Visit The Drill Down and you'll see my contact information for Digg. While I occasionally use different user names on sites, I publicly declare my affiliations and unless you know me really well, or have reason to follow me across the Web, you may not realize the relationships I have or where I can be found online by visiting any one site.

While the information about me on the Web is not terribly exciting, I do leave a little bit of information on every site I visit. And therein lies the rub. Say something in passing on a social site and it may come back to haunt you.

There is No Delete Button on the Web

It is becoming increasingly difficult to remove content from the web. The Internet Archive and its Way Back Machine gives you a historical snapshot of a site within seconds. Google gives you cached pages displaying pages that may have been deleted for any number of reasons. Photo sharing sites that store images online combined with services like Twitpic that let you quickly upload pictures to social sites - all of these great social Web resources also leave your historical Web footprints open to dissection in the future.

And although the information you put out on the Web may seem insignificant today, you have to ask the question of whether it will be insignificant tomorrow, or in five years when you need to apply for college or seek new employment. Additionally, you have to ask yourself whether you're just leaving more junk for the next generation to clean up.

New York Times' Policy on Social Networking

Poynter Online recently published the New York Times' policy regarding social networking sites, as provided by The Times' assistant managing editor Craig Whitney. In the memo, Whitney, who is responsible for overseeing journalistic standards, points out that social sites "can be remarkably useful reporting tools," but is quick to warn reporters to take care when using them. "Anything you post online can and might be publicly disseminated, and can be twisted to be used against you by those who wish you or The Times ill."

For a long time, The New York Times Company has had a policy on ethics in journalism and this move to document a social media policy can only be seen as a step in the right direction. However, there are some that see this as one of the reasons "mainstream media is doomed to irrelevance."

For the record, it is possible to remain passionate and true to your beliefs while participating on the social Web. What social sites should not allow - nor excuse - is a belief held by many that common courtesy and simple manners should be bypassed simply because you're not there in the flesh.

Whether you agree or disagree with Whitney's take on the social Web, it's important to recognize this huge step that The Times has taken. It has finally worked out that information on the Web is intricately intertwined. The article is well worth a read.

Getting Caught on the Web with Your Pants Down

There have been many instances where people and corporations have been caught out by content they upload to the Web. Whether the content is an image, a 140 character Tweet, or a blog post, we hope the following examples will give you time to reflect on the content you are uploading today.

Meltdown on Twitter

Last week, the Applicant blog talked about a hypothetical human resource bot in an attempt to persuade its readers of the importance of being aware of what they post to the Web. It was predominantly written to encourage readers to consider the ramifications of outbursts on the Web as applied to career and employment.

The very next day Twitter user Astrospace suffered an online meltdown which was captured as an image and posted on Applicant, giving their hypothetical post a great big shove into reality. "If I were an employer this certainly wouldn't be my ideal applicant, and at this point their brand is without a positive brand image," the Applicant post says.

While Astrospace may have had good reason for his rant (as most of us do), his outburst has now been captured and will possibly remain online for a very long time.

You Never Know Where Your Dulcet Tones will Turn Up

Last year when David Berkowitz boarded a train in New York he heard an argument between a woman and a man. While his first instinct was to get off the train, he made the decision to continue on.

This turned out to be fortunate for those with a sense of humor as he decided to record the argument and it now resides somewhere out there on the Web.

In this instance it may be more difficult, if not impossible to track the folks involved in the argument across the Web, but it still shows the importance of putting your best foot forward when in public - whether online or off.

Do You Know Who's Following You Online?

Peter Shankman recently discovered a seemingly off-the-cuff Tweet by James Andrews, an executive of Ketchum New York.

"True confession but I'm in one of those towns where I scratch my head and say "I would die if I had to live here!"

Sounds innocuous enough right? Not so. Andrews was in Memphis and on the way to meet his client FedEx. Turns out a Fed-Ex employee was terribly offended and responded with an e-mail that was copied to a variety of people including the folks in charge at Ketchum and the execs from Fed-Ex.

According to Shankman, the letter begins like this:

"Mr. Andrews,

If I interpret your post correctly, these are your comments about Memphis a few hours after arriving in the global headquarters city of one of your key and lucrative clients, and the home of arguably one of the most important entrepreneurs in the history of business, FedEx founder Fred Smith."

Read the entire e-mail here.

Clearly, what you do on social media leaves traces and cannot be easily removed from the Web. Information can fairly easily be tracked back to you and what you say and do will be public for a long time. Whether you believe in monitoring yourself online or not, don't forget the point of the social Web: to get to know other like minded people, share resources, have fun, and leave the place a little nicer than you found it.

Although we were planning to include a resource list of tools and services to help you monitor your online presence today, we've decided to leave it for next weekend given the length of this post.

As always, your opinion is very much appreciated and we look forward to hearing your thoughts in the comments.

Image Credit: Vu Bui

The first demonstration of the OpenKnowlege system is aimed to enhance the abilities of those seeking health-related information on the web. Instead of solely relying on a doctor to prescribe a course of treatment, people today tend to seek out medical information on their own using the web. Unfortunately, that data is often inaccurate and misleading. What OpenKnowledge intends to do is provide patients with structured information that has been checked for accuracy. To test this system, OpenKnowledge is working with Cancer Research UK on a project related to treatment methods.

2) Emergency Response

When there's an emergency situation, there is often a centralized point that disseminates critical information to people in need. But if that system itself breaks down, people are out of luck. OpenKnowledge aims to decentralize those systems so that a "backup" decentralized network of peers could be put into place. There, people could help each other out when the centralized system failed. This is currently being testing with emergency response authorities in Trentino, Italy.

3) Protemoics Research

Protemoics research (the study of the structure and function of proteins) can also benefit from the OpenKnowledge framework. In this area of science, many researchers worldwide rely on a small number of databases, creating a bottleneck of sorts which stresses the infrastructure of the databases themselves as well as those that maintain them. Researchers also find it hard to share data and results directly with other groups. In addition, the quality of the information in those databases is very mixed.

OpenKnowledge aims to solve all three problems by letting the researchers share data with each other directly, peer-to-peer style. This relieves the burden on the databases while the feedback will continually improve the quality of the data shared. This is currently being tested in an existing proteomics network in Spain called ProteoRed.

So...What Is It Exactly?

Understanding how a system like this works is difficult and the Open Knowledge web site doesn't make the process of comprehension any easier. Even despite the cute, Harry Potter-themed slideshow meant to describe the process, the actual details are hard to grasp. Obviously written by brainy researchers, they can't even call the slideshow a "slideshow," instead referring to it as a "simple pictorial introduction."

Still, if you can wade through the academic speech on the site, what you may find is a creative idea for sharing information. Basically, through open source downloadable code, OpenKnowledge sets up a peer-to-peer network where users can trade in information and data similar to how BitTorrent users trade mp3s and video files.

In the OpenKnowledge system, anyone can easily become a peer or even create their own peer by sharing existing code or writing their own. In order to become an OpenKnowledge user, you simply need to download the OpenKnowledge kernel from here together with some additional components that you might want to use. In addition to users, services, such as WSDL services, can also be made into peers on the OpenKnowledge network.

OpenKnowledge is more of a framework for decentralizing the systems on the web. It's not so much of a consumer-friendly web app than it is a model for information sharing that can help advance areas of science and research. You may not ever use OpenKnowledge yourself on your home computer, but your life may very well be impacted one day by the innovations it made possible.

For those of you who don't know, Zigtag is another entry in the social bookmarking collection of tools. Like delicious, Diigo, and Ma.gnolia, Zigtag helps you categorize your bookmarks and share them with others. When Zigtag went into development, bookmarking was all the rage. The company's goal was to make bookmarking easier by adding a layer of semantics to the tags themselves.

Zigtag, you see, understands the meaning of the words you assign to a tag. When you tag to a page, Zigtag actually assigns it meaning rather than just a simple word. If that sounds revolutionary...well, that's because it is. Sort of.

Not the Only Semantic Tagging Service

Because of Zigtag's slow progress, they can no longer claim to be the only semantic tagging application available today. Another, Faviki, also offers an intelligent tagging service based on structured data. Both services attempt to address the problem of user-generated tags. That is, even though what you tag "NY" may be the same link that I tagged "New York," no bookmarking service ever knew the tags were related.

Zigtag and Faviki attack this problem in different ways. Faviki suggests tags for you to use, not from a community of users and their tagging history, but from structured information extracted from DBpedia, a community-maintained database created by extracting information from Wikipedia.

Zigtag, however, eschews suggestions and lets you tag items as you wish. It doesn't matter what personal system you use for tagging (one word, two words, underscores, plus signs, etc.) because Zigtag understands the meaning of the tags. In Zigtag, a link tagged "New York" is returned along with other links tagged "New_York." Zigtag also understands that one tag may have different meanings and groups those items accordingly. For example, there's a New York and Company clothing store and a New York in England that may have been tagged "new york." That level of understanding is something that's unique to Zigtag and sets it apart from other bookmarking services.

Thanks to the service's ability to understand meaning, Zigtag users can join groups related a shared interest. Since Zigtag knows what you mean by your tags, it is, in theory, easier to find links you would be interested in on Zigtag than with other bookmarking services.

Is This Really Web 3.0?

Zigtag may be one of the first tools to step out of the Web 2.0 box. Where "Web 2.0" implies there is a social element to a service, it's generally speculated that Web 3.0 will bring about the intelligent web. Zigtag delivers this intelligence, but is it enough?

The only downside to Zigtag is that it requires you, the user, to manually insert the tags. In fact, it even relies on user-generated tagging and has built its entire service around that concept. That may be where Zigtag went wrong. Although two years ago, what it offered was ground-breaking and unique, as we enter 2009, we're asking the question: "Is tagging dead?"

At first, collaborative tagging, also known as a folksonomy, appeared to be the future of the web. It was a rejection of the search engine in favor of the community. It was our collective intelligence harnessed for the purpose of applying meaning and order to the pieces of the web in ways that computer-based tools could not.

As time went on, though, the one thing that made a folksonomy appealing - it was made by people! - was also the very thing that gave it problems. User-generated tags were likely to produce unreliable results. Zigtag addresses that problem, but it does not address what may end up being the true source of failure for folksonomy-based systems: people are lazy.

Now that there are myriads of services using tagging, thanks to the explosion of Web 2.0, we're getting sick of all the manual labor involved. Tag your links, tag your photos, tag your blog entries, tag your RSS feeds, etc.

While at one time, a semantic-based tagging system like Zigtag may have seemed like a vision of Web 3.0, we've now come to a point where we wonder if it does enough. It's possible the next revolution of the web won't be a system that understands the meaning of the tags we created, but knows how we would have tagged things if we had bothered to do so and then does it for us. And if that's not the future of the web...well...perhaps it should be.

What Twitchboard does is tie together different services on the social web and automates their interactions. Specifically, Twitchboard watches your Twitter stream and notices when you post a URL. It then automatically sends that link to your del.icio.us account. And, according to the company's homepage, they're working on connections to many other services for the future.

Blogger Chris Arkenberg says Twitchboard is a part of the "emerging class of cloud agents." These cloud agents, as he describes them, will help us sort and search the massive volumes of data we interact with regularly. He envisions that soon we'll have many of these cloud agents, swarming around us, working on our behalf, helping to parse the data flowing in and providing us with the information that we need, separated from the noise.

If that's true, then we seriously can't wait. We hope that in 2009, we'll start seeing more of these smart cloud agents and less of those "yet another"apps. Developers, start your engines, it's time to build some real tools.

"It hears everything that's going on around you; it knows where you are, it knows the motion of your body, it sees what's in front of it, it knows your contacts, and it hears your phone calls". Imagine the possibilities.

Certainly the fear of the unknown is a concept we are all familiar with. Hawke suggests we can only get past this, and move onto the many new opportunities Web 3.0 offers, if we find a good way to control all of that data.

But where would we start? According to Hawke, the basic requirements would be a clear, robust and simple-as-possible model that is based on consensus rights and responsibilities, making everything predictable for all parties, and gives shared control to the originating parties. While he admits that this would still not be risk free, it certainly seems to be a great starting point in a move towards Web 3.0.

The Advantages and Issues Surrounding Data Portability

Daniela Barbosa (co-founder of the DataPortability Project) began her presentation with a video that shows why most of us suffer from network fatigue, and why it is imperative that we have control of our own personal data.

DataPortability - Connect, Control, Share, Remix from Smashcut on Vimeo.

According to Barbosa, the biggest hurdle is convincing vendors to unlock their information. While most users can see the benefits of data portability, the majority of vendors only have questions:

1. Why would a vendor allow users to leave their service?
2. Why make it easy for users to take the precious data you have about them and use it on other sites?
3. What is the business justification and risks for letting data walk out the door.

Her answer to these questions is that businesses are effectively losing out. "Is it really worth it to lock in your users data? Because, you only get a piece of their [users] information."

An important point: When users sign up to new services they generally set up their accounts once, so any friends they add to other services at a later date, won't be shared across all services. As a vendor, you have no way of knowing about any new information on other services, unless the user updates the information manually across all accounts - and really, how many people do that?

Monetizing Your Data

Michael Benedek (Vice President, AlmondNet) begins his presentation with a quote by Imran Khan, Internet analyst, JPMorgan:

More than 80% of online inventory currently sells for less than $1 CMP. This means many page views are meaningless to advertisers unless user information can be gathered and ads are targeted. In order to most effectively target the ads, publishers need to have access to user behavior on multiple sites to collect data and to repeatedly show ads to the same user.

"We all know that Internet ad spending is booming; advertisers like it because there is measurability and targetability," Benedek said, "yet, the vast majority of ads on the Internet are really not targeted. For instance, I'm from Canada and I can't vote in the United States, but all I see lately are ads about Obama."

Benedek believes there are tremendous opportunities available with Web 3.0 to leverage the data available and to deliver more targeted ads, but there are many issues to consider:

Privacy Issues

• Role of Government: Industry Self Regulation vs. Government Regulation
• Technology: Deep Packet Inspection vs. adware vs. 1st party cookies vs. 3rd party cookies
• Types of Data: Personally Identifiable Information (PII) vs. merged PII/non PII vs. sensitive non PII vs. non PII
• Notice and consent: Opt-in (PII) vs. opt-out (Non PII)

Business Issues

• Standardization: Who is an auto intender?
• Scalability: Opt-in (impractical) vs. opt-out (practical when non PII is collected/shared)
• Data Ownership: Advertiser (3rd party ad server/cookie) vs. publisher vs. consumer

Conclusion

Web 3.0 still seems to have a way to go, and there are still debates about its meaning, but we expect the ride will be interesting. Do we follow the recommendations of the W3C and look for a common standard; do we want the ability to share our data across networks as recommended by the DataPortability Workgroup, or do accept that advertising is here to stay and help businesses target us better as recommended by AlmondNet?

Who do you want to be in control of your data?

ReadWriteWeb is a media sponsor of the Web 3.0 Conference & Expo

Web 2.0 is the business revolution in the computer industry caused by the move to the internet as platform, and an attempt to understand the rules for success on that new platform. Chief among those rules is this: Build applications that harness network effects to get better the more people use them. (This is what I've elsewhere called "harnessing collective intelligence.")

We can perhaps simplify that even further: Web 2.0 is the web as a platform and collective intelligence (or, leveraging of user created data). Now let's look at Tim's definition of Web 3.0 (which actually predates his last Web 2.0 definition):

Recently, whenever people ask me "What's Web 3.0?" I've been saying that it's when we apply all the principles we're learning about aggregating human-generated data and turning it into collective intelligence, and apply that to sensor-generated (machine-generated) data.

Which we can simplify to mean, the leveraging of the things we created in Web 2.0. And here's the Web 2.0 defintion he had up on a slide yesterday during his keynote:

• The Internet is the platform
• Harnessing the collective intelligence
• Data as the "Intel Inside"
• Software above the level of a single device
• Software as a service

O'Reilly talked about Web 2.0 in terms of taking user-generated data and turning it into user facing services. So now we're starting to see a lot of overlap between the two definitions. He's also brought in a lot of Web 3.0 definitions that other people have given and used them as part of this broader definition of Web 2.0. For example, Eric Schmidt of Google talked about Web 3.0 in terms of sofware as a service and cloud computing. Our own Alex Iskold talked about Web 3.0 in terms of web sites being turned into platforms. And so on.

"For 'Web 3.0' to be meaningful we'll need to see a serious discontinuity from the previous generation of technology ... I find myself particularly irritated by definitions of 'Web 3.0' that are basically descriptions of Web 2.0," Tim O'Reilly once said, which is mildly ironic given that his current Web 2.0 definition basically eclipses his old Web 3.0 definition. But in reality, I think O'Reilly is saying that the versioning doesn't really matter -- the web is the web.

"The points of contrast [between Web 2.0 and Web 3.0] are actually the same points that I used to distinguish Web 2.0 from Web 1.5. (I've always said that Web 2.0 = Web 1.0, with the dot com bust being a side trip that got it wrong.)," wrote O'Reilly last fall. In otherw words, the versioning of the web is silly. Web 1.0, 2.0, or 3.0 is all really just whatever cool new thing we're using the web to accomplish right now.

And he has a point. A couple of days ago, we wrote about the history of the term Web 3.0 and noted that the term itself doesn't really matter, what matters is the discussions we have when trying to define it. "It is the discussion that is helpful rather than coming to any accepted definition. Some might argue that version numbers are silly on the web, that Web 2.0 and Web 3.0 are just marketing ploys, and that we shouldn't use terms that are so nebulous and difficult to define. Those are all fair points. But at the same time, the discussions we have about defining the next web help to solidify our vision of where we're going -- and you can't get there until you decide where you want to go," we wrote.

Web 2.0 and Web 3.0 -- they don't really exist. They're just arbitrary numbers assigned to something that doesn't really have versions. But the discussion that those terms have prompted have been helpful, I think, in figuring out where the web is going and how we're going to get there; and that's what is important.

So next time someone asks me what we cover on ReadWriteWeb, maybe I won't use the term "Web 2.0" in my reply, I'll just tell them that we write about the web, what you can do with it now, and what you'll be able to do with it in the future.

Last April, we held a contest asking readers to define Web 3.0 and had nearly 50 different responses -- clearly, this is something people have a lot of ideas about. The winning entry talked about Web 3.0 as a "decentralized asynchronous me." Basically, that means a web that understands how to personalize your experience and recommend what you're looking for, and it's a definition we've used again. But it is one of just many -- it would appear that we're having a hard time deciding where the web is going.

Blogger Jonas Bolinder has painstakingly assembled a list of some of the most talked about definitions of Web 3.0 over the past three years. He's broken them down into 4 basic definition groups: the Semantic Web (which is what might enable the "decentralized me"), the proliferation of APIs and web services (aren't we already living that?), the rise of the mobile web, smart devices, and web applications (maybe the just launched Live Mesh has something to do with Web 3.0?), and the "implicit web."

It could be that all of these definitions are right. It could be that they're all wrong. It is the discussion that is helpful rather than coming to any accepted definition. Some might argue that version numbers are silly on the web, that Web 2.0 and Web 3.0 are just marketing ploys, and that we shouldn't use terms that are so nebulous and difficult to define. Those are all fair points. But at the same time, the discussions we have about defining the next web help to solidify our vision of where we're going -- and you can't get there until you decide where you want to go.

So which is your favorite definition of Web 3.0? Where do you see the web going over the next 5 or 10 years?

Last April, we held a contest asking readers for their web 3.0 definitions. Our favorite came from Robert O'Brien, who defined Web 3.0 as a "decentralized asynchronous me."

"Web 1.0: Centralized Them. Web 2.0: Distributed Us. Web 3.0: Decentralized Me," he wrote. "[Web 3.0 is] about me when I don't want to participate in the world. It's about me when I want to have more control of my environment particularly who I let in. When my attention is stretched who/what do I pay attention to and who do I let pay attention to me. It is more effective communication for me!"

What O'Brien was getting at is basically what Kiss was getting at: personalization and recommendation. And that's the promise of the Semantic Web. The easiest way to sell the Semantic Web vision to consumers is to talk about how it can make their lives easier. When machines understand things in human terms, and can apply that knowledge to your attention data, we'll have a web that knows what we want and when we want it.

ReadWriteWeb contributor Sramana Mitra put it another way on this blog last February, when she said that web 3.0 will be about adding context to personalization. "Personalization has remained limited to some unsatisfactory efforts by the MyYahoo team, their primary disadvantage being the lack of a starting Context," she wrote. "In Web 3.0, I predict, we are going to start seeing roll-ups. We will see a trunk that emerges from the Context, be it film (Netflix), music (iTunes), cooking / food, working women, single parents, ... and assembles the Web 3.0 formula that addresses the whole set of needs of a consumer in that Context." Or in other words, web 3.0 will be about feeding you the information that you want, when you want it (in the proper context).

Of course, the versioning of the Internet is kind of silly, and probably shouldn't keep going, but it is a fun way to look to the future and predict what we might be coming our way. What do you think of Kiss's idea about web 3.0 being about recommendation and personalization?