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.

Question: Talk about your investments in the space? Who did you fund and how much did you put in?

Amanda Reed (Palomar): In 2003 Palomar Ventures funded Attensity, a text analytics startup that provides insights based on unstructured feedback from customers. The platform is able to leverage emails, web pages, documents of different types, etc. and then automatically infers connections between people, places, companies, events, and more to deliver business insights that otherwise would be buried in unmanageable amounts of text.

The second investment we made was in Silver Creek Systems, which offers information transformation, data extraction and cleansing services. The platform is able to consume and normalize large volumes of unstructured enterprise data and is currently used in eTailing and financial services markets. Both companies received funding in $4-7M range from Palomar and $10-15M range overall.

Eghosa Omoigui (Intel): Intel Capital is the investment arm of the Intel Corporation, and it has $3 billion under management. 93 invest professionals are working with 422 companies on deals ranging in size from seed stage investments to hundreds of millions of dollars. The most recent investment was in Endeca, which specializes in content aggregation and management for enterprises. We have a lot of interest in the semantic space and have been following it for over five years. There are several deals that are currently pending that I can't name. One is doing dynamic, large-scale ontologies - taking content and overlaying dynamic ontologies. The company is based out of Asia and will be announced soon.

Stephen Hall (Vulcan): Vulcan Capital started looking into this space in 2004-05. In addition to several investments in the space, the firm has internal R&D efforts. We're excited about the sector and look at it quite broadly. In 2005 Vulcan invested in ZoomInfo - a company that focuses on extracting information about people and companies from unstructured text. ZoomInfo offers an application which is both in vertical search and recruiting/sales intelligence.

Another big investment by Vulcan was a seed round in Radar Networks which recently unveiled its first product, a collaborative semantic knowledge sharing space called Twine. [ReadWriteWeb's review -- Ed.] I'm excited about Twine, and believe that the company is paving the way toward a new type of data organization - one that is social. We also invest in a stealth startup called Evri, which is going to launch next week at the Wall Street Journal conference.

Evri will automatically index the web, connect people, places and other entities and offer a way to shortcut search. The bigger promise of semantics is not to improve search, but to avoid it all together, because once context is known, relevant information can be inferred. We believe that Evri will deliver a new and disruptive way of bringing us information.

Lastly, Vulcan funded a company in the email space, which is still in stealth mode. It aims to apply semantic technologies to mining information buried in emails.

Question: During this conference an executive from Oracle claimed that semantic technologies are not going to reach the mainstream on their own. Instead they will be absorbed by large enterprise products, such as Oracle's. Can you comment on that?

Stephen Hall (Vulcan): That's not so. There are tremendous opportunities in the space. If we did not believe that, we would not have made all the investments that we have. The the amount of unstructured information out there is huge and rapidly growing, creating more and more need for automatic/semantic technologies to cope with the information explosion. This need is what drives the opportunities both in the consumer and enterprise space.

Question: Nova Spivack said that most VCs are looking for only 1 play in the Semantic Web space, is that true? Also, someone else commented that VCs would rather invest in applications instead of platforms. Is that so?

Amanda Reed (Palomar): VCs do not think about this as a single market. Those venture capitalists who really understand the power of semantic technologies do not fund companies because they use the technologies, they fund companies for which there is market need and opportunity. VCs want to put money into companies that are solving real problems and have clear user benefits. Having semantic technologies as infrastructure is certainly interesting and impressive, but by no means is it a deciding factor.

It is true that VCs like apps over platforms. Platforms have traditionally had a challenge with pricing. In all of the investments that Palomar has made in this space, a big focus has been on pushing companies to build applications on top of platforms. Another important observation to make is that once a platform is turned into an application and it reaches customers, the word semantic disappears from the marketing. Enterprise customers, like consumers, simply do not need to know what is inside as long as it works and solves the problem.

Eghosa Omoigui (Intel): One of the strategies that is interesting in the semantic space is the stack of solutions based on a theme. There is a great diversity in semantic web technologies and problems, so by adopting this as a theme, VCs can build a portfolio of companies that collectively offer solutions along the entire stack. One needs to look for the best company in each niche, with a clear proposition and superior technology. And so with that, if someone says we only invest in 1 company in the space, run, because that means they don't get the space.

Question: Give us examples of particular market areas where you see opportunities now.

Amanda Reed (Palomar): Enterprise infrastructure investments. Product transformation, data quality, cleaning data. There is big pressure to reuse data in different applications and services. People tend to shy away from the enterprise because of the lengthy sales cycles and costs to scale the sales, but there is a lot of money to be made.

Stephen Hall (Vulcan): There are a lot of light-weight services that are beginning to tap and re-wire the existing web. As an early example, SmartLinks from AdaptiveBlue leverages existing URLs as semantic markers. These type of top-down contextual / semantic technologies that are leveraging existing bits of the web are just in their infancy and we will see much more in the space. Another variety of consumer technologies that have a lot of promise are things like Trippit. Taking unstructured information from email, recognizing it, cleaning it, and inserting it automatically into iCalendar is an example of applying semantic technologies to consumer task automation. There are lots of opportunities like this in the consumer space.

Amanda Reed (Palomar): Speaking of Trippit, the space is not semantics, the space is really travel. Semantics is really the means to an end, but not the main point. We are excited about the companies that put semantic technologies to good use in verticals and solve real, specific problems.

Question: How do you expect to make money on the Semantic Web? What are the monetization strategies that you are seeing?

Stephen Hall (Vulcan): It really depends on the company and the business model. Twine will be partially monetized via advertising, but there will be other components. In general, Vulcan quite likes the advertising space, which will be doubling to $40B with room still for growth. Semantic technologies that are impacting ad quality is another interesting area. There are companies in that space, for example Dapper, that are leveraging semantics to deliver more targeted, more contextual advertising.

Amanda Reed (Palomar): There are several business models that we are seeing out there. Most often, it is a web service or service offering. There are licenses in the enterprises as well, of course. In addition, we are seeing new models where services are packaged into boxes and bundled with software. This is a hybrid model that seems to be interesting to many enterprises because of the finer control. It is important for startups to figure out how to match the value proposition to the business model.

Question: How are today's funding models different from, say, 5 years ago? How much capital do startups need these days typically in series A, series B?

Amanda Reed (Palomar): Cloud computing has changed the startup game in a very significant way. The cost to get to market is substantially lower as more startups are now able to buy critical infrastructure from companies like Amazon.

Stephen Hall (Vulcan): There is really no formula for how to fund a company. Deciding on a capital needs depends on many factors. Some companies need $10M, some need $50M and there is a comparable upside. Some of the opportunities today simply could not have existed yesterday because we did not have the scalable and readily available grid infrastructure.

Eghosa Omoigui (Intel): Intel has launched amazing products for deploying cutting edge tech. This drives the value for every dollar. Another big difference is outsourcing, which has had a dramatic impact. These days you can hire a stellar development team in Eastern Europe at a fraction of the cost of one in the US or even Asia.

In general, there is a big difference between launching a software and a hardware business. Chip businesses can require hundreds of millions of dollars to get going, but software is on the order of magnitude cheaper to build. Everything is dependent on the target market.

Amanda Reed (Palomar): Another important thing to keep in mind is that VCs are looking for entrepreneurs who know how VC firms work. For example, the size of the investment is driven by the size of the fund. A billion dollar fund does not have capacity to put $1M into the company. A partner can only focus on 5-7 companies and to make it worthwhile for the fund, each investment needs to be much more substantial. A lot of entrepreneurs do not understand that and apply to funds that are unable to fund them.

Question: What are the proof points that you look for for series A and B funding?

Stephen Hall (Vulcan): Series A, pre-product pre-revenue, you need to have comfort that the team understands technologies and can manage issues around scale. Particularly in the web space, scale is critical. Also, looking for passionate people with past success. The biggest thing, which is often missing, is a go-to-market strategy. VCs will help refine the path, but you need to have clarity to have success.

Eghosa Omoigui (Intel): Too many use cases is always something that plagues this industry. When there are many use cases, there is a lack of focus. Go and figure out where the need is. It is most important not to get it right, but to articulate the problem and to know what you are after.

Question: How early are you getting into companies and what is the mininimum you are putting in?

Eghosa Omoigui (Intel): Depends on the opportunity. We do everything from $300K seed funding to $300M rounds.

Amanda Reed (Palomar): We like early stage. We will do a $250K seed deal if we know that series A is coming. We tend to top out in high $20M pre-money valuations.

Stephen Hall (Vulcan): Depends on the deal but we prefer early, series A. Can do less than $1M and seek to put in $10M over the lifetime of the company.

Disclosure: Alex Iskold is Founder/CEO of AdaptiveBlue.

Standards?

No. Inform crunches straight text and outputs HTML. I asked whether they publish content with any standards based semantic markup and they said that actual publishing is up to publishers. That's a shame, I don't see any reason why Inform wouldn't participate in the larger semantic web to make its publishers' content more discoverable. Perhaps when you've got 100 live clients and now $15m in the bank, it feels like there's no reason to open up and play nice with a movement of dreamers having trouble getting other apps out of academia.

Different Approaches

While many publishers have been criticized for linking only to their own internal pages for reference (including many leading blogs) it's good to see that Inform at least provides the option of including outside links. That is, after all, one of the most important characteristics of the web - links from one site to another.

Inform indexes blogs, audio and video as well at standard web pages. It's a smart idea and similar to a number of related companies you may be more familiar with. Our own Alex Iskold runs AdaptiveBlue, a semantic company that offers related links tied to links already added by publishers and a semantic browser plug-in. SystemOne is an elegant system that offers related content automatically during the writing process. Lijit is a custom search engine of sorts, allowing you and your readers to manually search through a confined set of content.

The key way the above services probably differ is the degree of automation that they offer. Inform is highly automated, once a publisher sets up general rules for brining in related content. A publisher might say, for example, to insert a link to their own content on any terms they have more than 20 articles about from the past week, or that their affiliate network can provide content for with a certain minimum percentage of relevance.

There's some heavy math and linguistics going on at Inform and it's a good example of how proprietary technology is headed for the bank while open standards based approaches dawdle. In theory openness and standards should be clear winners in terms of ultimate value delivered to any company, someday. In the meantime, publishers can deploy Inform's semantic technology now.