Video from my panel at DEMO Fall ’08 on the Future of the Web is now available.

I moderated the panel, and our panelists were:

Howard Bloom, Author, The Evolution of Mass Mind from the Big Bang to the 21st Century

Peter Norvig, Director of Research, Google Inc.

Jon Udell, Evangelist, Microsoft Corporation

Prabhakar Raghavan, PhD, Head of Research and Search Strategy, Yahoo! Inc.

The panel was excellent, with many DEMO attendees saying it was the best panel they had ever seen at DEMO.

Many new and revealing insights were provided by our excellent panelists. I was particularly interested in the different ways that Google and Yahoo describe what they are working on. They covered lots of new and interesting information about their thinking. Howard Bloom added fascinating comments about the big picture and John Udell helped to speak about Microsoft’s longer-term views as well.

Enjoy!!!

I’m here at the BlogTalk conference in Cork, Ireland with a range of bloggers and technologists discussing the emerging social Web. Including myself, Ian Davis and Paul Miller from Talis, there are also a bunch of other Semantic Web folks including Dan Brickley, and a group from DERI Galway.

Over dinner a few of us were discussing the terms “Semantic Web” versus “Web 3.0″ and we all felt a better term was needed. After some thinking, Ian Davis suggested “Web 3G.” I like this term better than Web 3.0 because it loses the “version number” aspect that so many objected to. It has a familiar ring to it as well, reminding me of the 3G wireless phone initiative. It also suggests Tim Berners-Lee’s “Giant Global Graph” or GGG — a synonym for the Semantic Web. Ian stayed up late and put together a nice blog post about the term, echoing many of my own sentiments about how this term should apply to a decade (the third decade of the Web), rather than to a particular technology.

My company, Radar Networks, has just come out of stealth. We’ve announced what we’ve been working on all these years: It’s called Twine.com. We’re going to be showing Twine publicly for the first time at the Web 2.0 Summit tomorrow. There’s lot’s of press coming out where you can read about what we’re doing in more detail. The team is extremely psyched and we’re all working really hard right now so I’ll be brief for now. I’ll write a lot more about this later.

Twine

It’s been an interesting month for news about Radar Networks. Two significant articles came out recently:

Business 2.0 Magazine published a feature article about Radar Networks in their July 2007 issue. This article is perhaps the most comprehensive article to-date about what we are working on at Radar Networks, it’s also one of the better articulations of the value proposition of the Semantic Web in general. It’s a fun read, with gorgeous illustrations, and I highly recommend reading it.

BusinessWeek  posted an article about Radar Networks on the Web. The article covers some of the background that led to my interests in collective intelligence and the creation of the company. It’s a good article and covers some of the bigger issues related to the Semantic Web as a paradigm shift. I would add one or two points of clarification in addition to what was stated in the article: Radar Networks is not relying solely on software to organize the Internet — in fact, the service we will be launching combines human intelligence and machine intelligence to start making sense of information, and helping people search and collaborate around interests more productively. One other minor point related to the article — it mentions the story of EarthWeb, the Internet company that I co-founded in the early 1990′s: EarthWeb’s content business actually was sold after the bubble burst, and the remaining lines of business were taken private under the name Dice.com. Dice is the leading job board for techies and was one of our properties. Dice has been highly profitable all along and recently filed for a $100M IPO.

The folks at Read/Write Web have a great analysis of AOL’s recent move to support the OpenID initiative. AOL has integrated with OpenID, adding 63 million users in a bid to make AIM handles sticky.

Digg also just announced they are joining OpenID.

OpenID is one of the technologies that I am tracking as a key enabler of Web 3.0.

Tom Hayes has an interesting post in which he coins the word ‘beme" to mean a meme that spreads in the blogosphere.

Michael Malone’s ABC News column on Thursday mentioning "bemes" has certainly produced a lot of interest.  Originally, I coined the word beme
to describe a meme propagated by blogs and bloggers.  Now I can see
that the turn of phrase has a much bigger potential to capture the
rapidly-moving cultural touchstones of the Bubble Generation.

As you may know, "meme" was first defined by Richard Dawkins in 1976
as "a unit of cultural information" spread from one mind to another.
In other words, a viral idea that eventually becomes common knowledge.

Fast forward three decades, and it seems to me that technology has turbo-charged the meme process.  Looking for the juste mot
to describe a "purposeful" meme fed into the vast human network of the
Internet, either by blog, email, video, phonecast, social media or
other viral means, beme seems to fit the bill. 

A beme is a turbo-charged meme made possible entirely by the
existence of the network affect.  A beme can be impactful because it is
lurid–a photo of a panty-less Britney Spears, or humorous–a
whimisical video of the band OKGO on treadmills, or gut-wrenching–the
sad tirade by comedian Michael Richards.  A beme can cement an idea
with the public in a way that cannot be legislated or regulated.  No
legal effort by Cisco to enforce a trademark, for example, will make
the public unlearn that Apple produces the iPhone.

• A meme is old media, a beme is new media.
• A meme takes off by accident, a beme by design.
• A meme can take years to surface, a beme hours.

It’s been a while since I posted about what my stealth venture, Radar Networks, is working on. Lately I’ve been seeing growing buzz in the industry around the "semantics" meme — for example at the recent DEMO conference, several companies used the word "semantics" in their pitches. And of course there have been some fundings in this area in the last year, including Radar Networks and other companies.

Clearly the "semantic" sector is starting to heat up. As a result, I’ve been getting a lot of questions from reporters and VC’s about how what we are doing compares to other companies such as for example, Powerset, Textdigger, and Metaweb. There was even a rumor that we had already closed our series B round! (That rumor is not true; in fact the round hasn’t started yet, although I am getting very strong VC interest and we will start the round pretty soon).

In light of all this I thought it might be helpful to clarify what we are doing, how we understand what other leading players in this space are doing, and how we look at this sector.

Indexing the Decades of the Web

First of all, before we get started, there is one thing to clear up. The Semantic Web is part of what is being called "Web 3.0" by some, but it is in my opinion really just one of several converging technologies and trends that will define this coming era of the Web. I’ve written here about a proposed definition of Web 3.0, in more detail.

For those of you who don’t like terms like Web 2.0, and Web 3.0, I also want to mention that  I agree — we all want to avoid a rapid series of such labels or an arms-race of companies claiming to be > x.0. So I have a practical proposal: Let’s use these terms to index decades since the Web began. This is objective — we can all agree on when decades begin and end, and if we look at history each decade is characterized by various trends. 

I think this is reasonable proposal and actually useful (and also avoids endless new x.0′s being announced every year). Web 1.0 was therefore the first decade of the Web: 1990 – 2000. Web 2.0 is the second decade, 2000 – 2010. Web 3.0 is the coming third decade, 2010 – 2020 and so on. Each of these decades is (or will be) characterized by particular technology movements, themes and trends, and these indices, 1.0, 2.0, etc. are just a convenient way of referencing them. This is a useful way to discuss history, and it’s not without precedent. For example, various dynasties and historical periods are also given names and this provides shorthand way of referring to those periods and their unique flavors. To see my timeline of these decades, click here.

So with that said, what is Radar Networks actually working on? First of all, Radar Networks is still in stealth, although we are
planning to go beta in 2007. Until we get closer to launch what I can
say without an NDA is still limited. But at least I can give some
helpful hints for those who are interested. This article provides some hints, as well as what I hope is a helpful tutorial about natural language search and the Semantic Web, and how they differ. I’ll also discuss how Radar Networks compares some of the key startup ventures working with semantics in various ways today (there are many other companies in this sector — if you know of any interesting ones, please let me know in the comments; I’m starting to compile a list).

(click the link below to keep reading the rest of this article…)

Semantic Social Software: The Semantic Web for Consumers

Here at Radar Networks, we are building a next-generation Web-based
online service that will bring the Semantic Web to consumers and
professionals across the Web. This application is focused on enabling
the next generation of social software (note that
social software is not necessarily social networking — that is subset
of social software). It is an example of what "the
Intelligent Web" will be like. We are very excited about this service
and what it already does, but there’s still more to do before we
release it.

Our app is based on the Semantic Web. It will
enrich and facilitate more intelligent online relationships, community,
content, collaboration and even commerce. It will help to bring the
Semantic Web from research to reality by making it user-friendly,
accessible and most of all, directly useful and valuable, to ordinary
people. We are focused on providing value to consumers — not just developers or early-adopters. But like I said, I can’t really provide more details until we
get closer to launch.

Our Web 3.0 Applications Platform

In order to build our product we had to first build a new platform
to support the kinds of features and capabilities we designed — we
could not find any existing platform that could do what we wanted to
do. Existing platforms for the Semantic Web were too research-oriented
and did not provide the levels of scalability, performance and
ease-of-use that we required.

We have been working on this platform
over several years and several generations of our codebase. It is now
very robust and sophisticated. We believe it is also significantly more
scalable and performant than any platform we’ve seen in the Semantic
Web space to-date.

Our platform is a comprehensive, Java-based framework for semantic
web applications and services that has some similarities to Ruby on
Rails (although it is also very different from RoR and we are not going after the platform market — we’re really more focused on our application right now). Our platform also includes a lot of other technology such as our
extremely fast and scaleable storage layer for semantic data tuples,
powerful semantic query capabilities, and a range of algorithms for
analyzing data and doing intelligent things for users.

The platform
could be called a "Web 3.0" applications platform because it is
inherently based around RDF/OWL and the emerging Semantic Web. In
addition to the "Web 3.0" aspects of what we are doing, our platform
also makes heavy use of "Web 2.0" methods and technologies such as
AJAX, REST, widgets, and RSS/ATOM, to name a few.

What We are Not Doing: Natural Language Search

First of all, we at Radar Networks are NOT building a new search engine to compete with Google, like Powerset and TextDigger are doing — so we’re not competing with them. Companies like Powerset and TextDigger are working on natural language search. Natural language search is not equivalent to the Semantic Web, although the Semantic Web can certainly help that process.

Companies working specifically on natural language search are making
use of semantics, but at the word-level only. They use networks of words that are linked to synonyms, antonyms, homonyms and other variations. These are sometimes called semantic networks. Based on these networks of word meanings, they can understand the meaning of various words and expressions.

More sophisticated natural language search algorithms don’t just look at the words alone, they look at them in context, by analyzing the grammar and the rest of the content around them. The point of natural language search is ultimately to try to match the meaning of words in search queries to the content of various documents — and to do this better than Google, which basically just matches keywords without paying attention to the meaning of the words.

Essentially natural language search requires at least some level of artificial intelligence. Machine
understanding of natural language is a difficult problem and there has
been a lot of work on this over the last few decades. Today there are
many technologies that focus on this but the majority of them are based
on the assumption that software should do all the work to figure out
the meaning of information.

What We Are Doing: Semantic Web

In contrast to natural language search which focuses on trying to derive the meanings of words, the approach of the emerging Semantic Web makes use of metadata to encode the meaning of information.

In this approach, the meaning of the information can be explicitly
coded into the information just as HTML codes are added into content today — and this can be done by people or software, and even by communities. Once this meaning — or semantics — is explicitly encoded into content, it can then be re-used by other applications to make sense of the content. It’s worth noting that explicit semantics in content can also help natural language processing apps, as well as apps that don’t understand natural language.

In the Semantic Web approach, the meaning of the information is encoded using markup
languages such as RDF and OWL, which are W3C open standards. Words and concepts in the content of documents and data records can be marked up with RDF/OWL expressions to indicate what they mean — does a certain word or phrase such as "Lotus" for example, mean a software company, a software product, an exotic sportscar brand, or some other kind of concept? Without sophisticated natural language processing it is often difficult for software to determine this on its own. The Semantic Web provides markup codes that explicitly indicate the intended meaning of information in an unambiguous, machine-readable format.

Marking up content with additional metadata was possible before the Semantic Web using XML: you could just say <sportscar>Lotus</sportscar> but the problem is that the meaning of "sportscar" still had to be coded into applications in order for them know what it implies. With RDF/OWL that meaning can be formally encoded outside of applications in a set of definitions called an ontology. An ontology defines facts such as "a sportscar is a kind of car," "a car is a ground vehicle," "a car is a product," "a car is a device," "a sportscar is a recreational or competitive vehicle," etc.

Semantic Markup

By marking up content with OWL indicating that it is a sportscar, that meaning refers to the appropriate definitions in an ontology, from which any application that can read the ontology can then then infer these various specific intended meanings. The point here is that semantics are less ambiguous — they are explicitly encoded by the ontology which functions as a kind of more advanced data schema of sorts.

But this is really an oversimplification — OWL and ontologies can actually go a lot further than just defining the meaning of concepts — they can also define their logical relations as well. For example, how exactly are two things connected and are there any special restrictions on that connection? For instance, an ontology can define that a person’s sister must be female, or that a person can only have 1 biological mother, etc.

All kinds of apps can benefit from the extra hints about the meaning of
the information that can be provided by Semantic Web metadata around
content. For example, even a natural language search engine could do
less analysis and would need less intelligence, if it could leverage
existing semantic metadata that was already in content.

It’s important to note that applications and people don’t have to necessarily ever look at RDF or
OWL code (thank heavens!) — they can just work with objects and forms
like they already do on the Web and the underlying markup can be
created automatically for them. Nobody should have to look at raw RDF and OWL (unless they really want to), and the Semantic Web doesn’t force anyone to. For example, most of us don’t write HTML or XML or CSS by hand — but if we are using blogs or wikis or even posting listing on sites like job boards and auctions, we we are doing things that result in HTML, XML and CSS being created.

It should be clear from the above section that natural language search is a specific process that makes use of word-level semantics, but the Semantic Web is a broad set of technologies for defining the meaning of any kind of information (including, but not limited to words). The Semantic Web can help improve the process of natural language search, but today many natural language search algorithms do not make use of the Semantic Web or RDF/OWL data structures. However, as these technologies begin to converge (as they are here at Radar Networks, in fact) we will see new levels of accuracy become possible — the combination of traditional natural language processing and the richer semantics of RDF/OWL markup enables even more powerful machine-understanding and processing of text. That said, once again, I want to be clear that Radar Networks is not a search company — although we do use next-generation semantic search quite extensively in our application and platform.

Any application that can understand RDF/OWL can correctly interpret
the meaning of any content that is marked up with RDF/OWL metadata. If
a news article that mentions "Paris" many times is marked up with
RDF/OWL metadata then any app that can understand that metadata can for
example, correctly determine that the article is about the place Paris,
Texas, not the place Paris, France, and not the person Paris Hilton
either. The application doesn’t have to do any fancy natural language
processing to know this. Even a relatively "dumb" application that has
no ability to do natural language processing can still make sense of a
document if it can at least understand RDF/OWL.

So how does this explicit semantic markup in the form of
RDF/OWL metadata get into the document in the first place? Well it could have been added
automatically by some other software app that did  natural language
processing on it, or it could have resulted from newspaper editors and/or
even readers categorizing and/or tagging the document with tags for places, people, etc. in
a manner not unlike how they tag content in services like Flickr today.

The main point here is that adding the semantic metadata does not require
the apps that create or consume consume the content to understand natural language, nor does it require people to be XML coders — even regular end-users can help to define
the semantics of content by simply tagging it. The Semantic Web provides a much
richer and more expressive framework for doing this than is currently available in Web 2.0 "tags," but it’s not that far off either.

The Semantic Web can enhance word-level understanding and processing
of text in many ways, but note that it is not limited only to
word-level applications. The Semantic Web provides a way to make any
information more understandable to other applications — including data
records in databases, documents on the desktop and the Web, enterprise
data, photos, videos, music, and even Web services and software code.

Simple Examples of Semantics

For example, today there is a big problem in integrating data across
applications. In the enterprise for example, one application might define a record called a "Customer"
while another might call that concept by the term "Client." If a user
then searches for "Customers" they won’t necessarily also find records
for Clients. But using the Semantic Web the data records for Customers
and Clients can be mapped together so that applications can treat them
as equivalent. Any search for one will return the other as well. Not only can records be mapped to each other, but also the fields of those records can be
mapped together. For instance, the Customer record might have a field
named "Referred by" while the Client record might have a field called
"Introduced by" — these can be mapped together as well.

A similar example could apply to a consumer use-case — for example shopping: different stores describe the same product differently — with different terms. In one store a laptop is called a "laptop computer" and in another it is called a "portable computer," while another calls it a "desktop replacement." A search for any of these terms should return products that use any of these. Within a single commerce site this is not so hard, but what about searching across many commerce sites (which isn’t really even that easy to do at all today…)? If different commerce sites used the same underlying semantic metadata definitions to markup their various products, then users could search across their products with less trial-and-error, and they would get better results.

Of course the
technology for mapping between databases is not new — there are many
ways to do this — but the Semantic Web provides a way to do it that
may be more open and efficient in the long-run. Central to this approach is that an organization or
online service can use ontologies that centrally define key
concepts in a rigorous way. So instead of every different app and data
record having to be individually mapped to every other, they can
potentially all just map to the central ontology which functions as a
kind of semantic switchboard of sorts. All applications and queries can
use a common ontology (or set of them) to unify access to data records across many
different online services and databases. In a sense ontologies provide a way to define and share common languages for data, content, relationships and applications.

SPARQL and the Emerging Data-Web

More recently a new Semantic Web technology called SPARQL has also started to
emerge. SPARQL provides a common query language, like SQL, for querying
data that is stored in RDF. Any site or database that has RDF data and
that provides a SPARQL interface can be searched by any application
that speaks SPARQL. This means that the dream of "deep web search" is
finally going to become a reality. There is a huge amount of interest
in SPARQL at the moment and there are already a growing number of
SPARQL endpoints popping up around the Web. These new SPARQL endpoints
are to data what websites were to documents. It’s the beginning of what
some call "The Data Web" — which is the first step to the full-blown
Semantic Web. SPARQL is also a big piece of what we are doing.

Reasoning: The Next Frontier After Search

Another key benefit of using RDF/OWL is that these languages are
designed to support formal logical reasoning. By marking up information
with RDF/OWL sophisticated search and inferencing can then take place
around it. For example, by marking up various people and their social
connections it is then possible to infer for example, that Sue is
Jane’s cousin, that Bob and Dave are colleagues, and that product A is
incompatible with product B, etc.

This kind of logical reasoning and
inference is essential to enable the next-generation of the Web — an
Intelligent Web — where software and online services start to help
people work, communicate, socialize and shop more productively. For
example it will enable something beyond search — it will enable
services that provide answers or suggestions. This is not necessarily important for all applications today, but it
will become increasingly important in the future. Content that exists
in RDF/OWL essentially has a longer shelf-life and will be easier to
reuse, integrate and reason across in the future.

Differentiating The Players

The Semantic Web provides a comprehensive and growing framework of
technologies that enable the next evolution of the Web — it is therefore a
much broader and farther-reaching vision than natural language search,
even though that is certainly one area that it will benefit. Natural language search is really just about matching search queries to documents, by analyzing the meaning of words. The Semantic Web is about defining the meaning of data — any data — words, data records, documents, social relationships, product listings, etc. — and providing a way to query that data, integrate it, and reason across it.

In our own
application and platform we make use of a lot of natural-language
processing (NLP) and we also provide semantic search capabilities, but
our focus is on something quite different than searching the Web — yet
equally useful and important to everyone. Frankly, I’m glad we are not
working on search, as big an opportunity as that is — I think
competing directly with Google is a daunting task and not one I would
want to be on! Instead, we are providing a new environment in which
people can start to benefit from the power of the Semantic Web in areas
that Google is very weak in today or is not in at all in some cases;
it’s really quite orthogonal to Google and other search engines.

So from the above conversation it should be clear that we are
working on The Semantic Web, not just natural language search and
so we are quite different from companies like Powerset, Textdigger and
others who are working on word-level semantic understanding of text.
But what about Metaweb — how do
we differ from them? — Well from what we can glean so far, what we are
doing is also very different from them as well but perhaps not as
different as we are from Powerset.

Radar Networks and Metaweb are
frequently cited as the two main startups working to bring
semantically-driven Web 3.0 online services to consumers. My guess is
that there will be some similarities but even more differences. There
may even be opportunities for us to work together someday. But we’re
all still in stealth, so it’s hard to get very specific about our
similarities and differences today. One thing is for sure, 2007 is
going to be an exciting year for both our companies, and for the
emerging Web 3.0 generation of companies and products.

Web 3.0 is just beginning

In any case the next-evolution of the Web — what we call "The
Intelligent Web" (and what many are also calling "Web 3.0") is still in
the very early stages and I don’t think it will really hit big until
2010 (for a graphical timeline of how I think this will unfold, click here). In the meantime we are all putting the pieces in place.

Fortunately Web 3.0 is a big space with a lot of opportunity and there is
room for a many different players and business models to co-exist and
compete. The fact that there are now several ventures in this space is
a good thing for all of us, for as one person said to me the other day,
"a rising tide lifts all boats." I’m happy that there is enough action
for there to actually be some confusion for me to clear up! Only a year
ago it felt like we were the only commercial voice a wilderness of
academic research. Today VC’s are lining up to speak to us and the other
companies in the space, and we are literally having to keep them at bay
until we start our B round.

Solving Information Overload

The key realization behind all this recent interest in semantics is that keyword
search and traditional content and data representations are declining
in productivity. As the Web gets vaster and more complex, and as
consumers must work with a growing array of content and services,
productivity is seriously being threatened — not only in search, but
also in every other area of our digital lives. Most of us who work
intensively with knowledge and information already have a direct and
intuitive experience of how information overload has grown, even in the
last decade. Clearly something must be done about this or in another
few years we will all be buried in our own information.

The Semantic Web provides the best (and really the only) long-term
solution to information overload and complexity. By starting to add
richer semantics to data, and by enabling applications to start
leveraging this, it will make it possible to help people regain more of
their productivity and to make software smarter — without having to
attempt to create super-duper science fiction artificial intelligence.

It’s very important to keep in mind that The Semantic Web does not require that machines understand or reason as well as people — the semantics of the Semantic Web can be created by people and/or machines, and it doesn’t have to be perfect, it simply has to add hints that make content less ambiguous and more structured. By contrast, both the keyword approach of Google and the natural language search approach of companies like Powerset — if they are to keep up with the growing complexity of the Web — will require increasingly intelligent software, because basically in such systems the software has to do all the work by itself.

The Semantic Web actually is really more about leveraging the
collective intelligence of people and applications to enrich content — rather than trying
to make applications do all the work on their own — but this will be a lot clearer later in the process when there are several Semantic Web apps that demonstrate this.

Here at Radar Networks we have
been working towards this vision steadily — and we’re proud of the fact that we started working with semantics long before it was "cool" — we know this space inside out
and we think that our first application on our platform will be an "Aha
experience" for users.

It certainly has taken some time to bring the Semantic Web to
fruition, but when you think about it, Web 1.0 took about 5 years to
really get started, so it’s not without precedent. A new generation of
the Web is a big undertaking. For now, all of us working on anything having to do with "semantics"
or Web 3.0 need to work together to start mapping out this space and educating the marketplace so
that people (including the press and VC’s, and early-adopters) can
understand the companies and technologies more clearly. The rather
humorous irony for all of us, is that the meaning of the term "semantic" is still so
ambiguous today!

Here is my timeline of the past, present and future of the Web. Feel free to put this meme on your own site, but please link back to the master image at this site (the URL that the thumbnail below points to) because I’ll be updating the image from time to time.

This slide illustrates my current thinking here at Radar Networks about where the Web (and we) are heading. It shows a timeline of technology leading from the prehistoric desktop era to the possible future of the WebOS…

Note that as well as mapping a possible future of the Web, here I am also proposing that the Web x.0 terminology be used to index the decades of the Web since 1990. Thus we are now in the tail end of Web 2.0 and are starting to lay the groundwork for Web 3.0, which fully arrives in 2010.

This makes sense to me. Web 2.0 was really about upgrading the “front-end” and user-experience of the Web. Much of the innovation taking place today is about starting to upgrade the “backend” of the Web and I think that will be the focus of Web 3.0 (the front-end will probably not be that different from Web 2.0, but the underlying technologies will advance significantly enabling new capabilities and features).

See also: This article I wrote redefining what the term “Web 3.0″ means.

See also: A Visual Graph of the Future of Productivity

Please note: This is a work in progress and is not perfect yet. I’ve been tweaking thepositions to get the technologies and dates right. Part of thechallenge is fitting the text into the available spaces. If anyone outthere has suggestions regarding where I’ve placed things on thetimeline, or if I’ve left anything out that should be there, please letme know in the comments on this post and I’ll try to read just and update the image from time to time. If you would like to produce abetter version of this image, please do so and send it to me forinclusion here, with the same Creative Commons license, ideally.

NOTES

• Master Copy can be found at this URL or http://tinyurl.com/yynb93
• Last Update: Tuesday, November 7, 2006, 10:17AM PST
• License — This article is distributed under the Creative Commons Deed. If you would like to distribute a version of thisarticle, please link back to http://www.mindingtheplanet.net from yourversion, thanks.
• Printable version — Click here to download the printable PDF version of this article
• Illustrated Version — See the version by the Lifeboat Foundation

Prelude

Many years ago, in the late 1980s, while I was still a college student, I visited my late grandfather, Peter F. Drucker, at his home in Claremont, California. He lived near the campus of Claremont College where he was a professor emeritus. On that particular day, I handed him a manuscript of a book I was trying to write, entitled, “Minding the Planet” about how the Internet would enable the evolution of higher forms of collective intelligence.

My grandfather read my manuscript and later that afternoon we sat together on the outside back porch and he said to me, “One thing is certain: Someday, you will write this book.” We both knew that the manuscript I had handed him was not that book, a fact that was later verified when I tried to get it published. I gave up for a while and focused on college, where I was studying philosophy with a focus on artificial intelligence. And soon I started working in the fields of artificial intelligence and supercomputing at companies like Kurzweil, Thinking Machines, and Individual.

A few years later, I co-founded one of the early Web companies, EarthWeb, where among other things we built many of the first large commercial Websites and later helped to pioneer Java by creating several large knowledge-sharing communities for software developers. Along the way I continued to think about collective intelligence. EarthWeb and the first wave of the Web came and went. But this interest and vision continued to grow. In 2000 I started researching the necessary technologies to begin building a more intelligent Web. And eventually that led me to start my present company, Radar Networks, where we are now focused on enabling the next-generation of collective intelligence on the Web, using the new technologies of the Semantic Web.

But ever since that day on the porch with my grandfather, I remembered what he said: “Someday, you will write this book.” I’ve tried many times since then to write it. But it never came out the way I had hoped. So I tried again. Eventually I let go of the book form and created this weblog instead. And as many of my readers know, I’ve continued to write here about my observations and evolving understanding of this idea over the years. This article is my latest installment, and I think it’s the first one that meets my own standards for what I really wanted to communicate. And so I dedicate this article to my grandfather, who inspired me to keep writing this, and who gave me his prediction that I would one day complete it.

This is an article about a new generation of technology that is sometimes called the Semantic Web, and which could also be called the Intelligent Web, or the global mind. But what is the Semantic Web, and why does it matter, and how does it enable collective intelligence? And where is this all headed? And what is the long-term far future going to be like? Is the global mind just science-fiction? Will a world that has a global mind be good place to live in, or will it be some kind of technological nightmare?

I’ve often joked that it is ironic that a term that contains theword “semantic” has such an ambiguous meaning for most people. Mostpeople just have no idea what this means, they have no context for it,it is not connected to their experience and knowledge. This is aproblem that people who are deeply immersed in the trenches of theSemantic Web have not been able to solve adequately — they have notfound the words to communicate what they can clearly see, what they areworking on, and why it matters for everyone. In this article I havetried, and hopefully succeeded, in providing a detailed introductionand context for the Semantic Web fornon-technical people. But even technical people working in the fieldmay find something of interest here as I piece together the fragmentsinto a Big Picture and a vision for what might be called “Semantic Web2.0.”

I hope the reader will bear with me as Ibounce around across different scales of technology and time, and fromthe extremes of core technology to wild speculation in order to tellthis story. If you are looking for the cold hardscience of it all, this article will provide an understanding but willnot satisfy your need for seeing the actual code; there are otherplaceswhere you can find that level of detail and rigor. But if you want tounderstand what it all really means and what the opportunity and futurelookslike – this may be what you are looking for.

I should also note that all of this is my personal view of what I’vebeen working on,and what it really means to me. It is not necessarily the official viewof the mainstream academic Semantic Web community — although there arecertainly many places where we all agree. But I’m sure that somereaders will certainly disagree or raise objections to some of myassertions, and certainly to my many far-flung speculations about thefuture. I welcome those different perspectives; we’re all trying tomake sense of this and the more of us who do that together, the more wecan collectively start to really understand it. So please feel free towrite your own vision or response, and please let me know so I can linkto it!

So with this Prelude in mind, let’s get started…

The Semantic Web Vision

The Semantic Web is a set of technologies which are designed toenable aparticular vision for the future of the Web – a future in which allknowledge exists on the Web in a format that software applications canunderstand andreason about. By making knowledge more accessible to software, softwarewillessentially become able to understand knowledge, think about knowledge,and createnew knowledge. In other words, software will be able to be moreintelligent –not as intelligent as humans perhaps, but more intelligent than say,your wordprocessor is today.

The dream of making software more intelligent has been around almost as longas software itself. And although it is taking longer to materialize than past experts hadpredicted, progress towards this goal is being steadilymade. At the same time, the shape of this dream is changing. It is becomingmore realistic and pragmatic. The original dream of artificial intelligence wasthat we would all have personal robot assistants doing all the work we don’twant to do for us. That is not the dream of the Semantic Web. Instead, today’sSemantic Web is about facilitating what humans do – it is about helping humansdo things more intelligently. It’s not a vision in which humans do nothing andsoftware does everything.

The Semantic Web vision is not just about helping software become smarter –it is about providing new technologies that enable people, groups,organizations and communities to be smarter.

For example, by providing individuals with tools that learn about what theyknow, and what they want, search can be much more accurate and productive.

Using software that is able to understand and automatically organize largecollections of knowledge, groups, organizations and communities can reachhigher levels of collective intelligence and they can cope with volumes ofinformation that are just too great for individuals or even groups tocomprehend on their own.

Another example: more efficient marketplaces can be enabled by software thatlearns about products, services, vendors, transactions and market trends andunderstands how to connect them together in optimal ways.

In short, the Semantic Web aims to make software smarter, not just for itsown sake, but in order to help make people, and groups of people, smarter. Inthe original Semantic Web vision this fact was under-emphasized, leading to theimpression that Semantic Web was only about automating the world. In fact, it isreally about facilitating the world.

The Semantic Web Opportunity

The Semantic Web is one of the most significant things to happen since theWeb itself. But it will not appear overnight. It will take decades. It willgrow in a bottom-up, grassroots, emergent, community-driven manner just likethe Web itself. Many things have to converge for this trend to really take off.

The core open standards already exist, but the necessary development tools haveto mature, the ontologies that define human knowledge have to come into beingand mature, and most importantly we need a few real “killer apps” to prove thevalue and drive adoption of the Semantic Web paradigm. The first generation ofthe Web had its Mozilla, Netscape, Internet Explorer, and Apache – and it alsohad HTML, HTTP, a bunch of good development tools, and a few killer apps andservices such as Yahoo! and thousands of popular Web sites. The same things arenecessary for the Semantic Web to take off.

And this is where we are today – this all just about to start emerging.There are several companies racing to get this technology, or applications ofit, to market in various forms. Within a year or two you will see mass-consumerSemantic Web products and services hit the market, and within 5 years therewill be at least a few “killer apps” of the Semantic Web. Ten years from nowthe Semantic Web will have spread into many of the most popular sites andapplications on the Web. Within 20 years all content and applications on theInternet will be integrated with the Semantic Web. This is a sea-change. A bigevolutionary step for the Web.

The Semantic Web is an opportunity to redefine, or perhaps to better define,all the content and applications on the Web. That’s a big opportunity. Andwithin it there are many business opportunities and a lot of money to be made. It’snot unlike the opportunity of the first generation of the Web. There areplatform opportunities, content opportunities, commerce opportunities, searchopportunities, community and social networking opportunities, and collaborationopportunities in this space. There is room for a lot of players to compete andat this point the field is wide open.

The Semantic Web is a blue ocean waiting to be explored. And like anyunexplored ocean its also has its share of reefs, pirate islands, hidden treasure, shoals,whirlpools, sea monsters and typhoons. But there are new worlds out there to be discovered,and they exert an irresistible pull on the imagination. This is an excitingfrontier – and also one fraught with hard technical and social challenges thathave yet to be solved. For early ventures in the Semantic Web arena, it’s notgoing to be easy, but the intellectual and technological challenges, and the potentialfinancial rewards, glory, and benefit to society, are worth the effort andrisk. And this is what all great technological revolutions are made of.

Semantic Web 2.0

Some people who have heard the term “Semantic Web” thrown around too muchmay think it is a buzzword, and they are right. But it is not just a buzzword –it actually has some substance behind it. That substance hasn’t emerged yet,but it will. Early critiques of the Semantic Web were right – the early visiondid not leverage concepts such as folksonomy and user-contributed content atall. But that is largely because when the Semantic Web was originally conceivedof Web 2.0 hadn’t happened yet. The early experiments that came out of researchlabs were geeky, to put it lightly, and impractical, but they are already beingfollowed up by more pragmatic, user-friendly approaches.

Today’s Semantic Web – what we might call “Semantic Web 2.0” is a kinder,gentler, more social Semantic Web. It combines the best of the original visionwith what we have all learned about social software and community in the last10 years. Although much of this is still in the lab, it is already starting totrickle out. For example, recently Yahoo! started a pilot of the Semantic Webbehind their food vertical. Other organizations are experimenting with usingSemantic Web technology in parts of their applications, or to store or mapdata. But that’s just the beginning.

The Google Factor

Entrepreneurs, venture capitalists and technologists are increasinglystarting to see these opportunities. Who will be the “Google of the SemanticWeb?” – will it be Google itself? That’s doubtful. Like any entrenchedincumbent, Google is heavily tied to a particular technology and worldview. Andin Google’s case it is anything but semantic today. It would be easier for anupstart to take this position than for Google to port their entireinfrastructure and worldview to a Semantic Web way of thinking.

If it is goingto be Google it will most likely be by acquisition rather than by internal origination. Andthis makes more sense anyway – for Google is in a position where they can just wait and buy the winner,at almost any price, rather than competing in the playing field. One thing to note however is that Google has at least one product offering that shows some potential for becoming a key part of the Semantic Web. I am speaking of Google Base, Google’s open database which is meant to be a registry for structured data so that it can be found in Google search. But Google Base does not conform to or make use of the many open standards of the Semantic Web community. That may or may not be a good thing, depending on your perspective.

Of course the downside of Google waiting to join the mainstream Semantic Web community until after the winner is announced is very large – once there is a winner it may be too late for Google to beat them. Thewinner of the Semantic Web race could very well unseat Google. The strategistsat Google are probably not yet aware of this but as soon as they seesignificant traction around a major Semantic Web play it will become of interestto them.

In any case, I think there won’t be just one winner, there will be severalmajor Semantic Web companies in the future, focusing on different parts of theopportunity. And you can be sure that if Google gets into the game, every majorportal will need to get into this space at some point or risk becomingirrelevant. There will be demand and many acquisitions. In many ways the Semantic Web will not be controlled by just one company — it will be more like a fabric that connects them all together.

Context is King — The Nature ofKnowledge

It should be clear by now that the Semantic Web is all about enablingsoftware (and people) to work with knowledge more intelligently. But what isknowledge? Knowledge is not just information. It is meaningful information – itis information plus context. For example, if I simply say the word “sem” toyou, it is just raw information, it is not knowledge. It probably has nomeaning to you other than a particular set of letters that you recognize and asound you can pronounce, and the mere fact that this information was stated byme.

But if I tell you that “sem” it is the Tibetan word for “mind” then suddenly,“sem means mind in Tibetan” to you. If I further tell you that Tibetans have about as many words for “mind” as Eskimos have for “snow,” this is further meaning. Thisis context, in other words, knowledge, about the sound “sem.” The sound is raw information. When it is given context itbecomes a word, a word that has meaning, a word that is connected to conceptsin your mind – it becomes knowledge. By connecting raw information to context,knowledge is formed.

Once you have acquired a piece of knowledge such as “sem means mind in Tibetan,” you may then also form further knowledgeabout it. For example, you may form the memory, “Nova said that ‘sem means mind in Tibetan.’” You mightalso connect the word “sem” to networks of further concepts you have about Tibet and your understanding of what the word “mind” means.

The mind is the organ of meaning – mind is where meaning is stored,interpreted and created. Meaning is not “out there” in the world, it is purelysubjective, it is purely mental. Meaning is almost equivalent to mind in fact.For the two never occur separately. Each of our individual minds has some way of internally representing meaning — when we read or hear a word that we know, our minds connect that to a network of concepts about it and at that moment it means something to us.

Digging deeper, if you are really curious,or you happen to know Greek, you may also find that a similar sound occurs inthe Greek word, sēmantikós – which means “having meaning” and in turn is the root of the English word “semantic”which means “pertaining to or arising from meaning.” That’s an odd coincidence!“Sem” occurs in Tibetan word for mind, and the English and Greek words that allrelate to the concepts of “meaning” and “mind.” Even stranger is that not only do these words have a similar sound, they have a similar meaning.

With all this knowledge at yourdisposal, when you then see the term “Semantic Web” you may be able to inferthat it has something to do with adding “meaning” to the Web. However, if youwere a Tibetan, perhaps you might instead think the term had something to dowith adding “mind” to the Web. In either case you would be right!

Discovering New Connections

We’ve discovered a new connection — namely that there is an implicit connectionbetween “sem” in Greek, English and Tibetan: they all relate to meaning andmind. It’s not a direct, explicit connection – it’s not evident unless you digfor it. But it’s a useful tidbit of knowledge once it’s found. Unlike the direct migration of the sound “sem” from Greek to English,there may not have ever been a direct transfer of this sound from Greek toSanskrit to Tibetan. But in a strange and unexpected way, they are all connected. This connectionwasn’t necessarily explicitly stated by anyone before, but was uncovered byexploring our network of concepts and making inferences.

The sequence of thought about “sem”above is quite similar to kind of intellectual reasoning and discovery that theactual Semantic Web seeks to enable software to do automatically.  How is this kind of reasoning and discovery enabled? The Semantic Web providesa set of technologies for formally defining the context of information. Just asthe Web relies on a standard formal specification for “marking up” informationwith formatting codes that enable any applications that understand those codesto format the information in the same way, the Semantic Web relies on newstandards for “marking up” information with statements about its context – itsmeaning – that enable any applications to understand, and reason about, the meaning of those statements in the same way.

By applying semantic reasoning agents to large collections of semantically enhanced content, all sorts of new connections may be inferred, leading to new knowledge, unexpected discoveries and useful additional context around content. This kind of reasoning and discovery is already taking place in fields from drug discovery and medical research, to homeland security and intelligence. The Semantic Web is not the only way to do this — but it certainly will improve the process dramatically. And of course, with this improvement will come new questions about how to assess and explain how various inferences were made, and how to protect privacy as our inferencing capabilities begin to extend across ever more sources of public and private data. I don’t have the answers to these questions, but others are working on them and I have confidence that solutions will be arrived at over time.

Smart Data

By marking up information with metadata that formally codifies its context, we can make the data itself “smarter.” The data becomes self-describing. When you get a piece of data you also get the necessary metadata for understanding it. For example, if I sent you a document containing the word “sem” in it, I could add markup around that word indicating that it is the word for “mind” in the Tibetan language.

Similarly, a document containing mentions of “Radar Networks” could contain metadata indicating that “Radar Networks” is an Internet company, not a product or a type of radar technology. A document about a person could contain semantic markup indicating that they are residents of a certain city, experts on Italian cooking, and members of a certain profession. All of this could be encoded as metadata in a form that software could easily understand. The data carries more information about its own meaning.

The alternative to smart data would be for software to actually read and understand natural language as well as humans. But that’s really hard. To correctly interpret raw natural language, software would have to be developed that knew as much as a human being. But think about how much teaching and learning is required to raise a human being to the point where they can read at an adult level. It is likely that similar training would be necessary to build software that could do that. So far that goal has not been achieved, although some attempts have been made. While decent progress in natural language understanding has been made, most software that can do this is limited around particular vertical domains, and it’s brittle — it doesn’t do a good job of making sense of terms and forms of speech that it wasn’t trained to parse and make sense of.

Instead of trying to make software a million times smarter than it is today, it is much easier to just encode more metadata about what our information means. That turns out to be less work in the end. And there’s an added benefit to this approach — the meaning exists with the data and travels with it. It is independent of any one software program — all software can access it. And because the meaning of information is stored with the information itself, rather than in the software, the software doesn’t have to be enormous to be smart. It just has to know the basic language for interpreting the semantic metadata it finds on the information it works with.

Smart data enables relatively dumb software to be smarter with less work. That’s an immediate benefit. And in the long-term as software actually gets smarter, smart data will make it easier for it to start learning and exploring on its own. So it’s a win-win approach. Start with by adding semantic metadata to data, end up with smarter software.

Making Statements About the World

Metadata comes down to making statements about the world in a manner that machines, and perhaps even humans, can understand unambiguously. The same piece of metadata should be interpreted in the same way by different applications and readers.

There are many kinds of statementsthat can be made about information to provide it with context. For example, youcan state a definition such as “person” means “a human being or a legalentity.” You can state an assertion such as “Sue is a human being.” You canstate a rule such that “if x is a human being, then x is a person.”

From thesestatements it can then be inferred that “Sue is a person.” This inference is soobvious to you and me that it seems trivial, but most software today cannot dothis. It doesn’t know what a person is, let alone what a name is. But ifsoftware could do this, then it could for example, automatically organizedocuments by the people they are related to, or discover connections betweenpeople who were mentioned in a set of documents, or it could find documentsabout people who were related to particular topics, or it could give you a listof all the people mentioned in a set of documents, or all the documents relatedto a person.

Of course this is a very basicexample. But imagine if your software didn’t just know about people – it knewabout most of the common concepts that occur in your life. Your software wouldthen be able to help you work with your documents just about as intelligentlyas you are able to do by yourself, or perhaps even more intelligently, becauseyou are just one person and you have limited time and energy but your softwarecould work all the time, and in parallel, to help you.

Examples and Benefits

How could the existence of the Semantic Web and all the semantic metadata that defines it be really useful toeveryone in the near-term?

Well, for example, the problem of email spam would finally be cured:your software would be able to look at a message and know whether it wasmeaningful and/or relevant to you or not.

Similarly, you would never have to file anything by hand again. Your software could atuomate all filing and information organization tasks for you because it would understand your information and your interests. It would be able to figure out when to file something in a single folder, multiple folders, or new ones. It would organize everything — documents, photos, contacts, bookmarks, notes, products, music, video, data records — and it would do it even better and more consistently than you could on your own. Your software wouldn’t just organize stuff, it would turn it into knowledge by connecting it to more context. It could this not just for individuals, but for groups, organizations and entire communities.

Another example: search would bevastly better: you could search conversationally by typing in everyday naturallanguage and you would get precisely what you asked for, or even what youneeded but didn’t know how to ask for correctly, and nothing else. Your searchengine could even ask you questions to help you narrow what you want. You wouldfinally be able to converse with software in ordinary speech and it would understandyou.

The process of discovery would be easier too. You could have software agent that worked as your personal recommendation agent. It would constantly be looking in all the places you read or participate in for things that are relevant to your past, present and potential future interests and needs. It could then alert you in a contextually sensitive way, knowing how to reach you and how urgently to mark things. As you gave it feedback it could learn and do a better job over time.

Going even further with this,semantically-aware software – software that is aware of context, software thatunderstands knowledge – isn’t just for helping you with your information, itcan also help to enrich and facilitate, and even partially automate, yourcommunication and commerce (when you want it to). So for example, your software could help you with your email. It would be able to recommend responses to messages for you, or automate the process. It would be able to enrich your messaging anddiscussions by automatically cross-linking what you are speaking about withrelated messages, discussions, documents, Web sites, subject categories,people, organizations, places, events, etc.

Shopping and marketplaces wouldalso become better – you could search precisely for any kind of product, withany specific attributes, and find it anywhere on the Web, in any store. You could post classified ads and automatically get relevant matches according to your priorities, from all over the Web, or only from specific places and parties that match your criteria for who you trust. You could also easily invent a new custom datastructure for posting classified ads for a new kind of product or service and publishit to the Web in a format that other Web services and applications couldimmediately mine and index without having to necessarily integrate with yoursoftware or data schema directly.

You could publish an entiredatabase to the Web and other applications and services could immediately startto integrate your data with their data, without having to migrate your schemaor their own. You could merge data from different data sources together to create new data sources without having to ever touch or look at an actual database schema.

Bumps on the Road

The above examples illustrate thepotential of the Semantic Web today, but the reality on the ground is that the technology isstill in the early phases of evolution. Even for experienced software engineersand Web developers, it is difficult to apply in practice. The main obstaclesare twofold:

(1) The Tools Problem:

There are very few commercial-gradetools for doing anything with the Semantic Web today – Most of the tools forbuilding semantically-aware applications, or for adding semantics toinformation are still in the research phase and were designed for expertcomputer scientists who specialize in knowledge representation, artificialintelligence, and machine learning.

These tools require a largelearning curve to work with and they don’t generally support large-scaleapplications – they were designed mainly to test theories and frameworks, notto actually apply them. But if the Semantic Web is ever going to becomemainstream, it has to be made easier to apply – it has to be made moreproductive and accessible for ordinary software and content developers.

Fortunately, the tools problem isalready on the verge of being solved. Companies such as my own venture, RadarNetworks, are developing the next generation of tools for building Semantic Webapplications and Semantic Web sites. These tools will hide most of thecomplexity, enabling ordinary mortals to build applications and content thatleverage the power of semantics without needing PhD’s in knowledge representation.

(2) The Ontology Problem:

The Semantic Web providesframeworks for defining systems of formally defined concepts called “ontologies,”that can then be used to connect information to context in an unambiguous way. Withoutontologies, there really can be no semantics. The ontologies ARE the semantics,they define the meanings that are so essential for connecting information tocontext.

But there are still few widely used or standardized ontologies. Andgetting people to agree on common ontologies is not generally easy. Everyonehas their own way of describing things, their own worldview, and let’s face itnobody wants to use somebody else’s worldview instead of their own.Furthermore, the world is very complex and to adequately describe all the knowledgethat comprises what is thought of as “common sense” would require a very largeontology (and in fact, such an ontology exists – it’s called Cyc and it is solarge and complex that only experts can really use it today).

Even to describe the knowledge ofjust a single vertical domain, such as medicine, is extremely challenging. Tomake matters worse, the tools for authoring ontologies are still very hard touse – one has to understand the OWL language and difficult, buggy ontologyauthoring tools in order to use them. Domain experts who are non-technical andnot trained in formal reasoning or knowledge representation may find theprocess of designing ontologies frustrating using current tools. What is needed are commercial quality tools for buildingontologies that hide the underlying complexity so that people can just pourtheir knowledge into them as easily as they speak. That’s still a ways off, butnot far off. Perhaps ten years at the most.

Of course the difficulty ofdefining ontologies would be irrelevant if the necessary ontologies alreadyexisted. Perhaps experts could define them and then everyone else could justuse them? There are numerous ontologies already in existence, both on thegeneral level as well as about specific verticals. However in my own opinion,having looked at many of them, I still haven’t found one that has the rightbalance of coverage of the necessary concepts most applications need, andaccessibility and ease-of-use by non-experts. That kind of balance is arequirement for any ontology to really go mainstream.

Furthermore, regarding the presentcrop of ontologies, what is still lacking is standardization. Ontologists havenot agreed on which ontologies to use. As a result it’s anybody’s guess whichontology to use when writing a semantic application and thus there is a highdegree of ontology diversity today. Diversity is good, but too much diversityis chaos.

Applications that use differentontologies about the same things don’t automatically interoperate unless theirontologies have been integrated. This is similar to the problem of databaseintegration in the enterprise. In order to interoperate, different applicationsthat use different data schemas for records about the same things, have to bemapped to each other somehow – either at the application-level or the data-level.This mapping can be direct or through some form of middleware.

Ontologies canbe used as a form of semantic middleware, enabling applications to be mapped atthe data-level instead of the applications-level. Ontologies can also be usedto map applications at the applications level, by making ontologies of Webservices and capabilities, by the way. This is an area in which a lot ofresearch is presently taking place.

The OWL language can expressmappings between concepts in different ontologies. But if there are manyontologies, and many of them partially overlap, it is a non-trivial task toactually make the mappings between their concepts.

Even though concept A inontology one and concept B in ontology two may have the same names, and evensome of the same properties, in the context of the rest of the concepts intheir respective ontologies they may imply very different meanings. So simplymapping them as equivalent on the basis of their names is not adequate, theirconnections to all the other concepts in their respective ontologies have to beconsidered as well. It quickly becomes complex. There are some potential waysto automate the construction of mappings between ontologies however – but theyare still experimental. Today, integrating ontologies requires the help ofexpert ontologists, and to be honest, I’m not sure even the experts have itfigured out. It’s more of an art than a science at this point.

Darwinian Selection of Ontologies

All that is needed for mainstream adoption to begin is for a largebody of mainstream content to become semantically tagged andaccessible. This will cause whatever ontology is behind that content to become popular.

When developers see that there is significant content andtraction around aparticular ontology, they will use that ontology for their ownapplicationsabout similar concepts, or at least they will do the work of mappingtheir ownontology to it, and in this way the world will converge in a Darwinianfashionaround a few main ontologies over time.

These main ontologies will then beworth thetime and effort necessary to integrate them on a semantic level,resulting in acohesive Semantic Web. We may in fact see Darwinian natural selection take place not just at the ontology level, but at the level of pieces of ontologies.

A certain ontology may do a good job of defining what a person is, while another may do a good job of defining what a company is. These definitions may be used for a lot of content, and gradually they will become common parts of an emergent meta-ontology comprised of the most-popular pieces from thousands of ontologies. This could be great or it could be a total mess. Nobody knows yet. It’s a subject for further research.

Making Sense of Ontologies

Since ontologies are so important,it is helpful to actually understand what an ontology really is, and what itlooks like. An ontology is a system of formally defined related concepts. Forexample, a simple ontology is this set of statements such as this:

A human is a living thing.

A person is a human.

A person may have a first name.

A person may have a last name.

A person must have one and only onedate of birth.

A person must have a gender.

A person may be socially related toanother person.

A friendship is a kind of socialrelationship.

A romantic relationship is a kindof friendship.

A marriage is a kind of romanticrelationship.

A person may be in a marriage withonly one other person at a time.

A person may be employed by anemployer.

An employer may be a person or anorganization.

An organization is a group ofpeople.

An organization may have a productor a service.

A company is a type organization.

We’ve just built a simple ontologyabout a few concepts: humans, living things, persons, names, socialrelationships, marriages, employment, employers, organizations, groups,products and services. Within this system of concepts there is particular logic,some constraints, and some structure. It may or may not correspond to yourworldview, but it is a worldview that is unambiguously defined, can becommunicated, and is internally logically consistent, and that is what isimportant.

The Semantic Web approach providesan open-standard language, OWL, for defining ontologies. OWL also provides fora way to define instances of ontologies. Instances are assertions within theworldview that a given ontology provides. In other words OWL provides a meansto make statements that connect information to the ontology so that softwarecan understand its meaning unambiguously. For example, below is a set ofstatements based on the above ontology:

There exists a person x.

Person x has a first name “Sue”

Person x  has a last name “Smith”

Person x has a full name “Sue Smith”

Sue Smith was born on June 1, 2005

Sue Smith has a gender: female

Sue Smith has a friend: Jane, who isanother person.

Sue Smith is married to: Bob, anotherperson.

Sue Smith is employed by Acme, Inc, a company

Acme Inc. has a product, Widget2.0.

The set of statements above, plusthe ontology they are connected to, collectively comprise a knowledge basethat, if represented formally in the OWL markup language, could be understoodby any application that speaks OWL in the precise manner that it was intendedto be understood.

Making Metadata

The OWL language provides a way tomarkup any information such as a data record, an email message or a Web pagewith metadata in the form of statements that link particular words or phrasesto concepts in the ontology. When software applications that understand OWLencounter the information they can then reference the ontology and figure outexactly what the information means – or at least what the ontology says that itmeans.

But something has to add thesesemantic metadata statements to the information – and if it doesn’t add them or adds thewrong ones, then software applications that look at the information will getthe wrong idea. And this is another challenge – how will all this metadata getcreated and added into content? People certainly aren’t going to add it all byhand!

Fortunately there are many ways tomake this easier. The best approach is to automate it using special softwarethat goes through information, analyzes the meaning and adds semantic metadataautomatically. This works today, but the software has to be trained or providedwith rules and that takes some time. It also doesn’t scale cost-effectively tovast data-sets.

Alternatively, individuals can beprovided with ways to add semantics themselves as they author information. Whenyou post your resume in a semantically-aware job board, you could fill out aform about each of your past jobs, and the job board would connect that data toappropriate semantic concepts in an underlying employment ontology. As anend-user you would just fill out a form like you are used to doing;under-the-hood the job board would add the semantics for you.

Another approach is to leveragecommunities to get the semantics. We already see communities that are addingbasic metadata “tags” to photos, news articles and maps. Already a few simpletypes of tags are being used pseudo-semantically: subject tags and geographicaltags. These are primitive forms of semantic metadata. Although they are notexpressed in OWL or connected to formal ontologies, they are at leastsemantically typed with prefixes or by being entered into fields or specificnamespaces that define their types.

Tagging by Example

There may also be another solution to the problem of how to add semantics to content in the not to distant future. Once asuitable amount of content has been marked up with semantic metadata,it may be possible, through purely statistical forms of machinelearning, for software to begin to learn how to do a pretty good job ofmarking up new content with semantic metadata.

For example, if thestring “Nova Spivack” is often marked up with semantic metadata statingthat it indicates a person, and not just any person but a specificperson that is abstractly represented in a knowledge base somewhere,then when software applications encounter a new non-semanticallyenhanced document containing strings such as “Nova Spivack” or”Spivack, Nova” they can make a reasonably good guess that thisindicates that same specific person, and they can add the necessarysemantic metadata to that effect automatically.

As more and more semanticmetadata is added to the Web and made accessible it constitutes a statisticaltraining set that can be learned and generalized from. Although humansmay need to jump-start the process with some manually semantic tagging,it might not be long before software could assist them and eventuallydo all the tagging for them. Only in special cases would software needto ask a human for assistance — for example when totally new terms orexpressions were encountered for the first several times.

The technology for doing this learning already exists — and actually it’s not very different from how search engines like Google measure the community sentiment around web pages. Each time something is semantically tagged with a certain meaning that constitutes a “vote” for it having that meaning. The meaning that gets the most votes wins. It’s an elegant, Darwinian, emergent approach to learning how to automatically tag the Web.

One this is certain, if communities were able to tagthings with more types of tags, and these tags were connected to ontologies andknowledge bases, that would result in a lot of semantic metadata being added tocontent in a completely bottom-up, grassroots manner, and this in turn would enable this process to start to become automated or at least machine-augmented.

Getting the Process Started

But making the userexperience of semantic tagging easy (and immediately beneficial) enough that regular people will do it, is a challenge that has yet to be solved.However, it will be solved shortly. It has to be. And many companies andresearchers know this and are working on it right now. This does have to be solved to get the process of jump-starting the Semantic Web started.

I believe that the Tools Problem – the lack of commercial grade tools forbuilding semantic applications – is essentially solved already (although theproducts have not hit the market yet; they will within a few years at most).The Ontology Problem is further from being solved. I think the way this problemwill be solved is through a few “killer apps” that result in the building up ofa large amount of content around particular ontologies within particular onlineservices.

Where might we see this content initially arising? In my opinion it will most likely be within vertical communities of interest, communities of practice, and communities of purpose. Within such communities there is a need to create a common body of knowledge and to make that knowledge more accessible, connected and useful.

The Semantic Web can really improve the quality of knowledge and user-experience within these domains. Because they are communities, not just static content services, these organizations are driven by user-contributed content — users play a key role in building content and tagging it. We already see this process starting to take place in communities such as Flickr, del.icio.us, the Wikipedia and Digg. We know that communities of people do tag content, and consume tagged content, if it is easy and beneficial enough for to them to do so.

In the near future we may see miniature Semantic Webs arising around particular places, topics and subject areas, projects, and other organizations. Or perhaps, like almost every form of new media in recent times, we may see early adoption of the Semantic Web around online porn — what might be called “the sementic web.”

Whether you like it or not, it is a fact that pornography was one of the biggest drivers of early mainstream adoption of personal video technology, CD-ROMs, and also of the Internet and the Web.

But I think it probably is not necessary this time around. While, I’m sure that the so-called “sementic web” could become better from the Semantic Web, it isn’t going to be the primary driver of adoption of the Semantic Web. That’s probably a good thing — the world can just skip over that phase of development and benefit from this technology with both hands so to speak.

The World Wide Database

In some ways one could think of theSemantic Web as “the world wide database” – it does for the meaning of data records what theWeb did for the formatting documents. But that’s just the beginning. It actually turnsdocuments into richer data records. It turns unstructured data into structureddata. All data becomes structured data in fact. The structure is not merelydefined structurally, but it is defined semantically.

In other words, it’s notmerely that for example, a data record or document can be defined in such a wayas to specify that it contains a certain field of data with a certain label ata certain location – it defines what that field of data actually means in anunambiguous, machine understandable way. If all you want is a Web of data,XML is good enough. But if you want to make that data interoperable and machineunderstandable then you need RDF and OWL – the Semantic Web.

Like any database,the Semantic Web, or rather the myriad mini-semantic-webs that will comprise it,have to overcome the challenge of data integration. Ontologies provide a betterway to describe and map data, but the data still has to be described andmapped, and this does take some work. It’s not a magic bullet.

The Semantic Webmakes it easier to integrate data, but it doesn’t completely remove the dataintegration problem altogether. I think the eventual solution to this problemwill combine technology and community folksonomy oriented approaches.

The Semantic Web in HistoricalContext

Let’s transition now and zoom out to see the bigger picture. The Semantic Webprovides technologies for representing and sharing knowledge in new ways. Inparticular, it makes knowledge more accessible to software, and thus to otherpeople. Another way of saying this is that it liberates knowledge fromparticular human minds and organizations – it provides a way to make knowledgeexplicit, in a standardized format that any application can understand. This isquite significant. Let’s put this in historical perspective.

Before the invention of the printing press, there were two ways to spreadknowledge – one was orally, the other was in some symbolic form such as art orwritten manuscripts. The oral transmission of knowledge had limited range and ahigh error-rate, and the only way to learn something was to meet someone whoknew it and get them to tell you. The other option, symbolic communicationthrough art and writing, provided a means to communicate knowledgeindependently of particular people – but it was only feasible to produce a fewcopies of any given artwork or manuscript because they had to be copied byhand. So the transmission of knowledge was limited to small groups or at leastsmall audiences. Basically, the only way to get access to this knowledge was tobe one of the lucky few who could acquire one of its rare physical copies.

The invention of the printing press changed this – for the first timeknowledge could be rapidly and cost-effectively mass-produced and mass-distributed.Printing made it possible to share knowledge with ever-larger audiences. Thisenabled a huge transformation for human knowledge, society, government,technology – really every area of human life was transformed by thisinnovation.

The World Wide Web made the replication and distribution of knowledge eveneasier – With the Web you don’t even have to physically print or distributeknowledge anymore, the cost of distribution is effectively zero, and everyonehas instant access to everything from anywhere, anytime. That’s a lot betterthan having to lug around a stack of physical books. Everyone potentially haswhatever knowledge they need with no physical barriers. This has been anotherhuge transformation for humanity – and it has affected every area of humanlife. Like the printing press, the Web fundamentally changed the economics ofknowledge.

The Semantic Web is the next big step in this process – it will make all theknowledge of the human race accessible to software. For the first time,non-human things (software applications) will be able to start working withhuman knowledge to do things (for humans) on their own. This is a big leap – aleap like the emergence of a new species, or the symbiosis of two existingspecies into a new form of life.

The printing press and the Web changed the economics of replicating,distributing and accessing knowledge. The Semantic Web changes the economics ofprocessing knowledge. Unlike the printing press and the Web, the Semantic Webenables knowledge to be processed by non-human things.

In other words, humans don’t have to do all the thinking on their own, theycan be assisted by software. Of course we humans have to at least first createthe software (until we someday learn to create software that is smart enough tocreate software too), and we have to create the ontologies necessary for thesoftware to actually understand anything (until we learn to create software thatis smart enough to create ontologies too), and we have to add the semanticmetadata to our content in various ways (until our software is smart enough todo this for us, which it almost is already). But once we do the initial work ofmaking the ontologies and software, and adding semantic metadata, the systemstarts to pick up speed on its own, and over time the amount of work we humanshave to do to make it all function decreases. Eventually, once the system hasencoded enough knowledge and intelligence, it starts to function withoutneeding much help, and when it does need our help, it will simply ask us andlearn from our answers.

This may sound like science-fiction today, but in fact it a lot of this isalready built and working in the lab. The big hurdle is figuring out how to getthis technology to mass-market. That is probably as hard as inventing thetechnology in the first place. But I’m confident that someone will solve iteventually.

Once this happens the economics of processing knowledge will truly bedifferent than it is today. Instead of needing an actual real-live expert, theknowledge of that expert will be accessible to software that can act as theirproxy – and anyone will be able to access this virtual expert, anywhere,anytime. It will be like the Web – but instead of just information beingaccessible, the combined knowledge and expertise of all of humanity will alsobe accessible, and not just to people but also to software applications.

The Question of Consciousness

The Semantic Web literally enables humans to share their knowledge with eachother and with machines. It enables the virtualization of human knowledge andintelligence. With respect to machines, in doing this, it will lend machines“minds” in a certain sense – namely in that they will at least be able tocorrectly interpret the meaning of information and replicate the expertise ofexperts.

But will these machine-minds be conscious? Will they be aware of themeanings they interpret, or will they just be automatons that are simplyfollowing instructions without any awareness of the meanings they areprocessing? I doubt that software will ever be conscious, because from what Ican tell consciousness — or what might be called the sentient awareness ofawareness itself as well as other things that are sensed — is an immaterialphenomena that is as fundamental as space, time and energy — or perhaps evenmore fundamental. But this is just my personal opinion after having searchedfor consciousness through every means possible for decades. It just cannot befound to be something, yet it is definitely and undeniably taking place.

Consciousness can be exemplified through the analogy of space (but unlikespace, consciousness has this property of being aware, it’s not a mere lifelessvoid). We all agree space is there, but nobody can actually point to itsomewhere, and nobody can synthesize space. Space is immaterial andfundamental. It is primordial. So is electricity. Nobody really knows whatelectricity is ultimately, but if you build the right kind of circuit you canchannel it and we’ve learned a lot about how to do that.

Perhaps we may figure out how to channel consciousness like we channelelectricity with some sort of synthetic device someday, but I think that ishighly unlikely. I think if you really want to create consciousness it’s mucheasier and more effective to just have children. That’s something ordinarymortals can do today with the technology they were born with. Of course whenyou have children you don’t really “create” their consciousness, it seems to bethere on its own. We don’t really know what it is or where it comes from, orwhen it arises there. We know very little about consciousness today.Considering that it is the most fundamental human experience of all, it isactually surprising how little we know about it!

In any case, until we truly delve far more deeply into the nature of themind, consciousness will be barely understood or recognized, let aloneexplained or synthesized by anyone. In many eastern civilizations there aremulti-thousand year traditions that focus quite precisely on the nature ofconsciousness. The major religions have all universally concluded thatconsciousness is beyond the reach of science, beyond the reach of concepts,beyond the mind entirely. All those smart people analyzing consciousness for solong, and with such precision, and so many methods of inquiry, may have a pointworth listening to.

Whether or not machines will ever actually “know” or be capable of beingconscious of that meaning or expertise is a big debate, but at least we can allagree that they will be able to interpret the meaning of information and rulesif given the right instructions. Without having to be conscious, software willbe able to process semantics quite well — this has already been proven. It’sworking today.

While consciousness is and may always be a mystery that we cannot synthesize– the ability for software to follow instructions is an established fact. Inits most reduced form, the Semantic Web just makes it possible to providericher kinds of instructions. There’s no magic to it. Just a lot of details. Infact, to play on a famous line, “it’s semantics all the way down.”

The Semantic Web does not require that we make conscious software. It justprovides a way to make slightly more intelligent software. There’s a bigdifference. Intelligence is simply a form of information processing, for themost part. It does not require consciousness — the actual awareness of what isgoing on — which is something else altogether.

While highly intelligentsoftware may need to sense its environment and its own internal state andreason about these, it does not actually have to be conscious to do this. Theseoperations are for the most part simple procedures applied vast numbers of timeand in complex patterns. Nowhere in them is there any consciousness nor doesconsciousness suddenly emerge when suitable levels of complexity are reached.

Consciousness is something quite special and mysterious. And fortunately forhumans, it is not necessary for the creation of more intelligent software, noris it a byproduct of the creation of more intelligent software, in my opinion.

The Intelligence of the Web

So the real point of the Semantic Web is that it enables the Web to becomemore intelligent. At first this may seem like a rather outlandish statement,but in fact the Web is already becoming intelligent, even without the SemanticWeb.

Although the intelligence of the Web is not very evident at first glance,nonetheless it can be found if you look for it. This intelligence doesn’t existacross the entire Web yet, it only exists in islands that are few and farbetween compared to the vast amount of information on the Web as a whole. Butthese islands are growing, and more are appearing every year, and they arestarting to connect together. And as this happens the collective intelligenceof the Web is increasing.

Perhaps the premier example of an “island of intelligence” is theWikipedia, but there are many others: The Open Directory, portals such as Yahooand Google, vertical content providers such as CNET and WebMD, commercecommunities such as Craigslist and Amazon, content oriented communities such asLiveJournal, Slashdot, Flickr and Digg and of course the millions of discussionboards scattered around the Web, and social communities such as MySpace andFacebook. There are also large numbers of private islands of intelligence onthe Web within enterprises — for example the many online knowledge andcollaboration portals that exist within businesses, non-profits, andgovernments.

What makes these islands “intelligent” is that they are places where people(and sometimes applications as well) are able to interact with each other tohelp grow and evolve collections of knowledge. When you look at them close-upthey appear to be just like any other Web site, but when you look at what theyare doing as a whole – these services are thinking.They are learning, self-organizing, sensing their environments, interpreting,reasoning, understanding, introspecting, and building knowledge. These are theactivities of minds, of intelligent systems.

The intelligence of a system such as the Wikipedia exists on several levels– the individuals who author and edit it are intelligent, the groups that helpto manage it are intelligent, and the community as a whole – which isconstantly growing, changing, and learning – is intelligent.

Flickr and Digg also exhibit intelligence. Flickr’s growing system of tagsis the beginnings of something resembling a collective visual sense organ onthe Web. Images are perceived, stored, interpreted, and connected to conceptsand other images. This is what the human visual system does. Similarly, Digg isa community that collectively detects, focuses attention on, and interpretscurrent news. It’s not unlike a primitive collective analogue to the humanfacility for situational awareness.

There are many other examples of collective intelligence emerging on theWeb. The Semantic Web will add one more form of intelligent actor to the mix –intelligent applications. In the future, after the Wikipedia is connected tothe Semantic Web, as well as humans, it will be authored and edited by smartapplications that constantly look for new information, new connections, and newinferences to add to it.

Although the knowledge on the Web today is still mostly organized withindifferent islands of intelligence, these islands are starting to reach out andconnect together. They are forming trade-routes, connecting their economies,and learning each other’s languages and cultures. The next-step will be forthese islands of knowledge to begin to share not just content and services, butalso their knowledge — what they know about their content and services. The SemanticWeb will make this possible, by providing an open format for the representationand exchange of knowledge and expertise.

When applications integrate their content using the Semantic Web they willalso be able to integrate their context, their knowledge – this will make thecontent much more useful and the integration much deeper. For example, when anapplication imports photos from another application it will also be able toimport semantic metadata about the meaning and connections of those photos.Everything that the community and application know about the photos in theservice that provides the content (the photos) can be shared with the servicethat receives the content. Better yet, there will be no need for customapplication integration in order for this to happen: as long as both servicesconform to the open standards of the Semantic Web the knowledge is instantlyportable and reusable.

Freeing Intelligence from Silos

Today much of the real value of the Web (and in the world) is still lockedaway in the minds of individuals, the cultures of groups and organizations, andapplication-specific data-silos. The emerging Semantic Web will begin to unlockthe intelligence in these silos by making the knowledge and expertise theyrepresent more accessible and understandable.

It will free knowledge and expertise from the narrow confines of individualminds, groups and organizations, and applications, and make them not only moreinteroperable, but more portable. It will be possible for example for a personor an application to share everything they know about a subject of interest aseasily as we share documents today. In essence the Semantic Web provides acommon language (or at least a common set of languages) for sharing knowledgeand intelligence as easily as we share content today.

The Semantic Web also provides standards for searching and reasoning moreintelligently. The SPARQL query language enables any application to ask forknowledge from any other application that speaks SPARQL. Instead of merekeyword search, this enables semantic search. Applications can search forspecific types of things that have particular attributes and relationships toother things.

In addition, standards such as SWRL provide formalisms for representing andsharing axioms, or rules, as well. Rules are a particular kind of knowledge –and there is a lot of it to represent and share, for example proceduralknowledge, and logical structures about the world. An ontology provides a meansto describe the basic entities, their attributes and relations, but rulesenable you to also make logical assertions and inferences about them. Withoutgoing into a lot of detail about rules and how they work here, the importantpoint to realize is that they are also included in the framework. All forms ofknowledge can be represented by the Semantic Web.

Zooming Way, Waaaay Out

So far in this article, I’ve spenta lot of time talking about plumbing – the pipes, fluids, valves, fixtures,specifications and tools of the Semantic Web. I’ve also spent some time onillustrations of how it might be useful in the very near future to individuals,groups and organizations. But where is it heading after this? What is thelong-term potential of this and what might it mean for the human race on ahistorical time-scale?

For those of you who would prefer not to speculate, stop reading here. Forthe rest of you, I believe that the true significance of the Semantic Web, on along-term timescale is that it provides an infrastructure that will enable theevolution of increasingly sophisticated forms of collective intelligence. Ultimatelythis will result in the Web itself becoming more and more intelligent, untilone day the entire human species together with all of its software andknowledge will function as something like a single worldwide distributed mind –a global mind.

Just the like the mind of a single human individual, the global mind will bevery chaotic, yet out of that chaos will emerge cohesive patterns of thoughtand decision. Just like in an individual human mind, there will be feedbackbetween different levels of order – from individuals to groups to systems ofgroups and back down from systems of groups to groups to individuals. Becauseof these feedback loops the system will adapt to its environment, and to itsown internal state.

The coming global mind will collectively exhibit forms of cognition andbehavior that are the signs of higher-forms of intelligence. It will form andreact to concepts about its “self” – just like an individual human mind. Itwill learn and introspect and explore the universe. The thoughts it thinks maysometimes be too big for any one person to understand or even recognize them –they will be comprised of shifting patterns of millions of pieces of knowledge.

The Role of Humanity

Every person on the Internet will be a part of the global mind. Andcollectively they will function as its consciousness. I do not believe some newform of consciousness will suddenly emerge when the Web passes some thresholdof complexity. I believe that humanity IS the consciousness of the Web anduntil and unless we ever find a way to connect other lifeforms to the Web, orwe build conscious machines, humans will be the only form of consciousness ofthe Web.

When I say that humans will function as the consciousness of the Web I meanthat we will be the things in the system that know. The knowledge of theSemantic Web is what is known, but what knows that knowledge has to besomething other than knowledge. A thought is knowledge, but what knows thatthought is not knowledge, it is consciousness, whatever that is. We can figureout how to enable machines to represent and use knowledge, but we don’t knowhow to make them conscious, and we don’t have to. Because we are alreadyconscious.

As we’ve discussed earlier in this article, we don’t need conscious machines, we just need more intelligent machines.Intelligence – at least basic forms of it – does not require consciousness. It may be the case that the very highest forms of intelligence require or are capable of consciousness. This may mean that software will never achieve the highest levels of intelligence and probably guaranteesthat humans (and other conscious things) will always play a special role in theworld; a role that no computer system will be able to compete with. We providethe consciousness to the system. There may be all sorts of other intelligent,non-conscious software applications and communities on the Web; in fact therealready are, with varying degrees of intelligence. But individual humans, andgroups of humans, will be the only consciousness on the Web.

The Collective Self

Although the software of the Semantic Web will not be conscious we can say that system as a whole contains or is conscious to the extent that human consciousnesses are part of it. And like most conscious entities, it may also start to be self-conscious.

If the Web ever becomes a global mind as I am predicting, will it have a“self?” Will there be a part of the Web that functions as its central self-representation?Perhaps someone will build something like that someday, or perhaps it will evolve.Perhaps it will function by collecting reports from applications and people inreal-time – a giant collective zeitgeist.

In the early days of the Web portals such as Yahoo! provided this function — they were almost real-time maps of the Web and what was happening. Today making such a map is nearly impossible, but services such as Google Zeitgeist at least attempt to provide approximations of it. Perhaps through random sampling it can be done on a broader scale.

My guess is that the global mind will need a self-representation at somepoint. All forms of higher intelligence seem to have one. It’s necessary forunderstanding, learning and planning. It may evolve at first as a bunch ofcompeting self-representations within particular services or subsystems withinthe collective. Eventually they will converge or at least narrow down to just afew major perspectives. There may also be millions of minor perspectives thatcan be drilled down into for particular viewpoints from these top-level “portals.”

The collective self, will function much like the individual self – as amirror of sorts. Its function is simply to reflect. As soon as it exists theentire system will make a shift to a greater form of intelligence – because forthe first time it will be able to see itself, to measure itself, as a whole. Itis at this phase transition when the first truly global collective self-mirroring function evolves, that we can say that the transition from a bunch of cooperating intelligent parts toa new intelligent whole in its own right has taken place.

I think that the collective self, even if it converges on a few majorperspectives that group and summarize millions of minor perspectives, will becommunity-driven and highly decentralized. At least I hope so – because theself-concept is the most important part of any mind and it should be designedin a way that protects it from being manipulated for nefarious ends. At least Ihope that is how it is designed.

Programming the Global Mind

On the other hand, there are times when a little bit of adjustment or guidance iswarranted – just as in the case of an individual mind, the collective selfdoesn’t merely reflect, it effectively guides the interpretation of the pastand present, and planning for the future.

One way to change the direction ofthe collective mind, is to change what is appearing in the mirror of thecollective self. This is a form of programming on a vast scale – When thisprogramming is dishonest or used for negative purposes it is called “propaganda,” but there are cases whereit can be done for beneficial purposes as well. An example of this today ispublic service advertising and educational public television programming. Allforms of mass-media today are in fact collective social programming. When yourealize this it is not surprising that our present culture is violent andmessed up – just look at our mass-media!

In terms of the global mind, ideally one would hope that it would be able tolearn and improve over time. One would hope that it would not have the collective equivalent of psycho-social disorders. To facilitate this, just like any form of higherintelligence, it may need to be taught, and even parented a bit. It also mayneed a form of therapy now and then. These functions could be provided by thepeople who participate in it. Again, I believe that humans serve a vital and irreplaceablerole in this process.

How It All Might Unfold

Now how is this all going to unfold? I believe that there are a number ofkey evolutionary steps that Semantic Web will go through as the Web evolvestowards a true global mind:

1. Representing individual knowledge. The first step is to make individuals’knowledge accessible to themselves. As individuals become inundated withincreasing amounts of information, they will need better ways of managing it,keeping track of it, and re-using it. They will (or already do) need”personal knowledge management.”

2. Connecting individual knowledge. Next, once individual knowledge isrepresented, it becomes possible to start connecting it and sharing it acrossindividuals. This stage could be called “interpersonal knowledgemanagement.”

3. Representing group knowledge. Groups of individuals also need ways ofcollectively representing their knowledge, making sense of it, and growing itover time. Wikis and community portals are just the beginning. The Semantic Webwill take these “group minds” to the next level — it will make the collective knowledge ofgroups far richer and more re-usable.

4. Connecting group knowledge. This step is analogous to connectingindividual knowledge. Here, groups become able to connect their knowledge togetherto form larger collectives, and it becomes possible to more easily access andshare knowledge between different groups in very different areas of interest.

5. Representing the knowledge of the entire Web. This stage — what might becalled “the global mind” — is still in the distant future, but atthis point in the future we will begin to be able to view, search, and navigatethe knowledge of the entire Web as a whole. The distinction here is thatinstead of a collection of interoperating but separate intelligentapplications, individuals and groups, the entire Web itself will begin tofunction as one cohesive intelligent system. The crucial step that enables thisto happen is the formation of a collective self-representation. This enablesthe system to see itself as a whole for the first time.

How it May be Organized

I believe the global mind will be organized mainly in the form of bottom-up and lateral, distributed emergent computation andcommunity — but it will be facilitated by certain key top-down services thathelp to organize and make sense of it as a whole. I think this future Web willbe highly distributed, but will have certain large services within it as well– much like the human brain itself, which is organized into functionalsub-systems for processes like vision, hearing, language, planning, memory,learning, etc.

As the Web gets more complex there will come a day when nobody understandsit anymore – after that point we will probably learn more about how the Web isorganized by learning about the human mind and brain – they will be quitesimilar in my opinion. Likewise we will probably learn a tremendous amountabout the functioning of the human brain and mind by observing how the Webfunctions, grows and evolves over time, because they really are quite similarin at least an abstract sense.

The internet and its software and content is like a brain, and the state ofits software and the content is like its mind. The people on the Internet arelike its consciousness. Although these are just analogies, they are actuallyuseful, at least in helping us to envision and understand this complex system. Asthe field of general systems theory has shown us in the past, systems at verydifferent levels of scale tend to share the same basic characteristics and obeythe same basic laws of behavior. Not only that, but evolution tends to convergeon similar solutions for similar problems. So these analogies may be more thanjust rough approximations, they may be quite accurate in fact.

The future global brain will require tremendous computing and storageresources — far beyond even what Google provides today. Fortunately as Moore’s Law advances thecost of computing and storage will eventually be low enough to do thiscost-effectively. However even with much cheaper and more powerful computingresources it will still have to be a distributed system. I doubt that therewill be any central node because quite simply no central solution will be ableto keep up with all the distributed change taking place. Highly distributed problemsrequire distributed solutions and that is probably what will eventually emergeon the future Web.

Someday perhaps it will be more like a peer-to-peer network, comprised ofapplications and people who function sort of like the neurons in the human brain.Perhaps they will be connected and organized by higher-level super-peers orsuper-nodes which bring things together, make sense of what is going on andcoordinate mass collective activities. But even these higher-level serviceswill probably have to be highly distributed as well. It really will bedifficult to draw boundaries between parts of this system, they will all beconnected as an integral whole.

In fact it may look very much like a grid computing architecture – in whichall the services are dynamically distributed across all the nodes such that atany one time any node might be working on a variety of tasks for differentservices. My guess is that because this is the simplest, most fault-tolerant,and most efficient way to do mass computation, it is probably what will evolvehere on Earth.

The Ecology of Mind

Where we are today in this evolutionary process is perhaps equivalent to therise of early forms of hominids. Perhaps Austrolapithecus or Cro-Magnon, ormaybe the first Homo Sapiens. Compared to early man, the global mind is like the rise of 21^stcentury mega-cities. A lot of evolution has to happen to get there. But itprobably will happen, unless humanity self-destructs first,which I sincerely hope we somehow manage to avoid. And this brings me to afinal point. This vision of the future global mind is highly technological;however I don’t think we’ll ever accomplish it without a new focus on ecology.

Ecology probably conjures up images of hippies and biologists, or maybehippies who are biologists, or at least organic farmers, for most people, but infact it is really the science of living systems and how they work. And anysystem that includes living things is a living system. This means that the Webis a living system and the global mind will be a living system too. As a living system, the Web is an ecosystem and is alsoconnected to other ecosystems. In short, ecology is absolutely essential tomaking sense of the Web, let alone helping to grow and evolve it.

In many ways the Semantic Web and the collective minds, and the global mind,that it enables, can be seen as an ecosystem of people, applications,information and knowledge. This ecosystem is very complex, much like naturalecosystems in the physical world. An ecosystem isn’t built, it’s grown, andevolved. And similarly the Semantic Web, and the coming global mind, will notreally be built, they will be grown and evolved. The people and organizationsthat end up playing a leading role in this process will be the ones thatunderstand and adapt to the ecology most effectively.

In my opinion ecology is going to be the most important science anddiscipline of the 21^st century – it is the science of healthysystems. What nature teaches us about complex systems can be applied to everykind of system – and especially the systems we are evolving on the Web. Inorder to ever have a hope of evolving a global mind, and all the wonderfullevels of species-level collective intelligence that it will enable, we have tonot destroy the planet before we get there. Ecology is the science that cansave us, not the Semantic Web (although perhaps by improving collectiveintelligence, it can help).

Ecology is essentially the science of community – whether biological,technological or social. And community is a key part of the Semantic Web atevery level: communities of software, communities of people, and communities ofgroups. In the end the global mind is the ultimate human community. It is thereward we get for finally learning how to live together in peace and balancewith our environment.

The Necessity of Sustainability

The point of this discussion of the relevance of ecology to the future ofthe Web, and my vision for the global mind, is that I think that it is clearthat if the global mind ever emerges it will not be in a world that is anythinglike what we might imagine. It won’t be like the Borg in Star Trek, it won’t belike living inside of a machine. Humans won’t be relegated to the roles ofslaves or drones. Robots won’t be doing all the work. The entire world won’t becoated with silicon. We won’t all live in a virtual reality. It won’t be one ofthese technological dystopias.

In fact, I think the global mind can only come to pass in a much greener,more organic, healthier, more balanced and sustainable world. Because it willtake a long time for the global mind to emerge, if humanity doesn’t figure outhow to create that sort of a world, it will wipe itself out sooner or later,but certainly long before the global mind really happens. Not only that, butthe global mind will be smart by definition, and hopefully this intelligencewill extend to helping humanity manage its resources, civilizations andrelationships to the natural environment.

The Smart Environment

The global mind also needs a global body so to speak. It’s not going to bean isolated homunculus floating in a vat of liquid that replaces the physicalworld! It will be a smart environment that ubiquitously integrates with ourphysical world. We won’t have to sit in front of computers or deliberatelylogon to the network to interact with the global mind. It will be everywhere.

The global mind will be physically integrated into furniture, houses,vehicles, devices, artworks, and even the natural environment. It will sensethe state of the world and different ecosystems in real-time and alert humansand applications to emerging threats. It will also be able to allocateresources intelligently to compensate for natural disasters, storms, andenvironmental damage – much in the way that the air traffic control systemsallocates and manages airplane traffic. It won’t do it all on its own, humansand organizations will be a key part of the process.

Someday the global mind may even be physically integrated into our bodiesand brains, even down the level of our DNA. It may in fact learn how to curediseases and improve the design of the human body, extending our lives, sensorycapabilities, and cognitive abilities. We may be able to interact with it bythought alone. At that point it will become indistinguishable from a limitedfrom of omniscience, and everyone may have access to it. Although it will onlyextend to wherever humanity has a presence in the universe, within thatboundary it will know everything there is to know, and everyone will be able toknow any of it they are interested in.

Enabling a Better World

By enabling greater forms of collective intelligence to emerge we really arehelping to make a better world, a world that learns and hopefully understandsitself well enough to find a way to survive. We’re building something thatsomeday will be wonderful – far greater than any of us can imagine. We’re helpingto make the species and the whole planet more intelligent. We’re building thetools for the future of human community. And that future community, if it ever arrives,will be better, more self-aware, more sustainable than the one we live intoday.

I should also mention that knowledge is power, and power can be used forgood or evil. The Semantic Web makes knowledge more accessible. This puts more power in the hands of the many, not just the few. As long as we stick to this vision — we stick to making knowledge open and accessible, using open standards, in as distributed a fashion as we can devise, then the potential power of the Semantic Web will be protected against being coopted or controlled by the few at the expense of the many. This is where technologists really have to be socially responsible when making development decisions. It’s important that we build a more open world, not a less open world. It’s important that we build a world where knowledge, integration and unification are balanced with respect for privacy, individuality, diversity and freedom of opinion.

But I am not particularly worried that the Semantic Web and the future globalmind will be the ultimate evil – I don’t think it is likely that we will end upwith a system of total control dominated by evil masterminds with powerfulSemantic Web computer systems to do their dirty work. Statistically speaking, criminal empires don’t last very long because theyare run by criminals who tend to be very short-sighted and who also surroundthemselves with other criminals who eventually unseat them, or theyself-destruct. It’s possible that the Semantic Web, like any other technology,may be used by the bad guys to spy on citizens, manipulate the world, and doevil things. But only in the short-term.

In the long-term either our civilization will get tired of endlesssuccessions of criminal empires and realize that the only way to actuallysurvive as a species is to invent a form of government that is immune to beingtaken over by evil people and organizations, or it will self-destruct. Eitherway, that is a hurdle we have to cross before the global mind that I envisioncan ever come about. Many civilizations came before ours, and it is likely thatours will not be the last one on this planet. It may in fact be the case that adifferent form of civilization is necessary for the global mind to emerge, andis the natural byproduct of the emergence of the global mind.

We know that the global mind cannot emerge anytime soon, and therefore, ifit ever emerges then by definition it must be in the context of a civilizationthat has learned to become sustainable. A long-term sustainable civilization is a non-evil civilization. And that is why I think it is a safebet to be so optimistic about the long-term future of this trend.

The next SFWIN (San Francisco Web Innovators) monthly networking event is happening this Thursday at 6PM in downtown San Francisco at the offices of Orrick, a law firm with a very nice event space overlooking the skyline. We usually have around 100 people or so and delicious food and an open bar. You can get details about the event and RSVP here. Please come, I look forward to seeing you there!

Hi everyone, I am trying to generate some specific stats about the size of the Blogosphere. I couldn’t find the answer in Dave Sifry’s excellent State of the Blogosphere reports. Do any of you know of any studies or reports that answer the following:

• Average number of post per blog
• Average size per blog
  post
• Average number of comments per post
• Average size per comment
• Distribution of numbers of posts per
  blog across all blogs
• Distribution of size of posts per
  blog across all blogs

Today our product team met with Shel Isreal to show him the alpha version of what we are building here at Radar Networks and get his feedback. Shel had a lot of good insights. We showed him our full product and explained the vision, and gave him a tour of the new dimension of the Web that we are building. We also showed him how content providers such as bloggers and other site creators, and content consumers, can benefit by joining this system. Then we asked him how he would describe it.

Shel suggested that one way to express the benefit of our product is that it helps content creators, like bloggers, become part of more conversations. "Conversation" is a key word for Shel, as many of you know. He views the Web as a network of conversations, not just a network of content. In a sense, content is a means to an end — conversation — rather than an end in itself. So from that perspective we are advancing the state-of-the-art in conversations (broadly speaking, not just in the sense of discussions, but in the sense of connecting people and information together in smarter ways). That’s an interesting take on what we are doing that I hadn’t really thought about.

Shel also suggested that even though we are still a ways from being
ready to launch the beta, he thought what we had was "so much better than anything he has seen" that we should start talking about it more — without getting into the
actual details of how we are doing it (gotta save something for later,
after all!).

I’ll explain more in future posts.

My company, Radar Networks, is building a very large dataset by crawling and mining the Web. We then apply a range of new algorithms to the data (part of our secret sauce) to generate some very interesting and useful new information about the Web. We are looking for a few experienced search engineers to join our team — specifically people with hands-on experience designing and building large-scale, high-performance Web crawling and text-mining systems. If you are interested, or you know anyone who is interested or might be qualified for this, please send them our way. This is your chance to help architect and build a really large and potentially important new system. You can read more specifics abour our open jobs here.

This study is interesting — it seems to miss the point that many blogs are loaded with content that is actually USEFUL for work — for example in-house blogs, blogs from competitors, blogs from industry pundits, blogs from software developers, blogs from users and customers … and the list goes on. Simply reading blogs cannot be equated with "wasting time" — in fact it could be very productive market research, product research, etc. The article also mentions that some companies are (insanely) filtering out content containing the word "blog" — talk about shooting their workers in the foot (or the head)! But despite the simplistic bias of the analysis, the stats are quite interesting. Clearly blogging and blog-reading are a big part of many professionals’ workday. And that’s interesting to me, and others, who are interested in pushing the envelope of what a blog can be used for…

That
co-worker staring, eyes scrunched up, at his computer monitor may look
like he’s sweating through another hard day’s work. But he just might
be one of the growing number of office jockeys who, according to new
research, have their minds not on their jobs — but on a blog.
Trade paper AdAge.com reported this week that US workers would waste
the equivalent of 551,000 years during 2005 reading blogs, online web
diaries and gossip sheets, which have exploded in numbers in recent
years.

Around 35 million workers — one in four of the labour force in the
United States — spend three-and-a-half hours, or nine percent of their
working week on blogs, the survey found.

Blogs, which range in tone and quality from scandal sheets to
semi-professional news sites to in-depth "geek" technology forums, are
often seen as the ultimate expression of online freedom.

"Forget lunch breaks — blog readers essentially take a daily 40
minute blog break," AdAge quipped, presenting its survey as a
best-guess extrapolation based on blog related data.

The AdAge survey mirrors a poll conducted by America Online and
Salary.com in July, which found that American workers were goofing off
for two hours a day on the Internet, costing their employers 759
billion dollars a year.

But some blog and Internet experts argue that reading a blog in
itself does not necessarily equate to wasted time — and may replace
time when workers could be idling away their boss’s time doing
something else.

"I think it is a little broad brush to turn around and say ‘oh,
they are reading blogs and it’s a waste of time,’" said Steve Ferrer,
head of sales and marketing firm The Propaganda House which specializes
in the Internet, e-commerce and technology.

"If they weren’t reading a blog they might be doing something else
not necessarily productive either," said Ferrer, pointing out that some
jobs require workers to use blogs and the Internet for research.

Lee Rainie, a researcher at the Pew Internet and American Life
Project, said not all blogs were trashy journals — many are now put
out by reputable media firms, and used increasingly by corporations.

"It is not the case that a blog, is a blog, is a blog — blogs run
the spectrum from being ridiculous to the sublime," he said, but
admitted : "the notion that some people might not be optimising their
time is probably legitimate."

Pew earlier this year released research that suggested that eight
million Americans have created blogs, while blog readership jumped 58
percent in 2004 and stood at 27 percent of Internet users.

The AdAge survey coincided with new reports that America’s
companies may be waking up to lost productivity as desk-bound workers
surf the net.

Fred Wilson has an intersting post about how to keep founders engaged in the companies they started after they step out of CEO roles. He says:

I’d like to find a formula (like the one Yahoo! has found) and bottle it. 
Because I believe companies that can keep their founders engaged and motivated
are so much better off than those that cannot.

I think the key to this is to understand the mentality of founders. We are people who choose to start things instead of join things that already exist. We thrive on invention and the opportunity to disrupt existing systems. We are evangelists and communicators — we get the most satisfaction from being able to transmit our excitement to others. We are more motivated by the slight chance of huge upside than a guaranteed but limited win. We have no fear of personal financial risk — perhaps even irrationally so — we are eternal optimists and believe we will always prevail. We look to the future more than the present or the past. We are highly competitive and need to be in leadership roles but we hate beaurocracy and the inefficiencies of large organizations, which is why we start small ones. We are more interested in what hasn’t been built yet, than what is already working. We strive to be successful, but not merely in financial terms — acknowledgement for our ideas and creations from our peers is even more satisfying than making money.

Generally we are workaholics and we are comfortable wearing many hats — and in fact we often wear our many hats better than specialists who only wear one hat. Rather than wait for others to things, we tend to just get them done ourselves — a skill which is great for small companies but perhaps disruptive in large ones. We are generally not top-down managers and we don’t like to treat others as non-equals — another reason why we like startups where everyone is collaborating as a team.

What does all this mean? To me it means that VC’s and companies that wish to keep their founders involved, after they are no longer in the CEO role, need to find ways that their founders can do what they do best for the company, rather than somewhere else. In other words, they have to give founders the ability to invent and incubate new business, or lines of business, for the company. They also have to make sure that founders never feel sidelined our overshadowed by the hired management teams that come in when companies start growing.

I believe that it is often a good thing to bring in professional CEO’s — for example, when companies get large enough in people and revenues to require managers with large-enterprise management skills. But it’s also vital not to bring in hired leadership until the company is really large enough, and focused enough, to warrant it. If done to early, bringing outsiders in to run a company, can destroy the company’s DNA rather than replicate it.

I think the formula for managing this transition successfully is:

• Only bring in outside CEO’s to take over leadership when a company has grown up (or is about to) — when it is large enough in people and revenues to need a new level of structure and management.
• Keep founders motivated by giving them the freedom to innovate and incubate new businesses within the framework of the existing venture.
• Utilize the founders as evangelists, keep them in the spotlight — don’t marginalize them internally or externally.
• VC’s should make sure the founders have the last word, and veto power, in choosing the new leadership — even if they technically don’t have an equity majority in the company anymore. Additionally the choice of a new CEO should be carefully tailored to fit the personality of the founders. Some founders don’t like to be in the spotlight, others do. It’s important that the new CEO’s ego is compatible with their egos, or lack thereof.
• Make sure the founders are made a part of the new leadership team so that they continue to feel a sense of ownership and control in their companies.
• Instead of the founders reporting to the new management team, it should be the reverse. The new management team should report to the founders (not on a day-to-level — but perhaps on a quarterly level).
• The transition from leadership by the Founders to leadership by a new CEO and management team has to be handled carefully. Often there is a strong bond of loyalty between the Founders and key employees who were there from the early days. In order for key employees to accept the new leadership, and not see it as a negative sign, there has to be an unambiguous communication to key employees and staff about the benefits, and support of the Founders, of the change. If not managed well such transitions come across as "management shakeups" rather than positive developments for the business.
• Make sure the founders still have as great or greater opportunities for huge upside within the venture, as they might have by starting something new outside the venture.

I think companies that follow these principles make a successful transition to professional management while continuing to harness the tremendous energy, inspiration and initiative that their founders can provide. The best combination, in my opinon, is when the new CEO is less of a star and more of a manager. Founders usually provide the charisma and media savvy. What they need is someone who can build the structure and discipline to back them up.

I think the case of Google is a great example. Larry and Sergey get to be the guys in front of the cameras. Eric, who has always been a speak-softly-but-carry-a-big-stick guy, is the man making things run. They don’t compete — it’s very complementary. In the case of Yahoo, it’s a different arrangement. I rarely ever see the original Yahoo founders in print or elsewhere — they seem to have vanished — yet they are still there it turns out. In Yahoo — which has become a media company — it’s Terry Semel who is the media star in the spotlight. It seems to be working, but clearly the personal goals of the Yahoo founders are quite different from the Google founders because they were willing to take more of a backseat role.

This is cool Click to see why.  I think this idea has great value for viral, meme-based Web advertising. Just imagine: Advertisers could release really cool animations to add to sites, and site owners could add them into their sites for entertainment or humor. The animations could run ads within them as well. It’s fun. Everyone wins, everyone’s happy. And of course users can aim these animations at any other site so visitors who like it can spread it to their own sites. Very smart!!! Very Web 2.0.

Great news! Radar Networks, the venture I’ve been building, has received its first round of outside funding from Vulcan Capital. We are heavily in stealth mode.

Tristan, has written an important article on the emerging RSS standards war, in which he suggests some solutions to the divergent format specs that are popping up right now.

Marc has developed an interesting new service that provides a universal "one-stop shop" for posting microcontent to various blogs. It’s a sort of universal "blog this" button that anyone can use. Nice idea. Marc explains it better than I can, so here it is in his own words.

This article provides some very compelling and useful statistics about the growth of the Weblog tools market.

First of all I know Clay Shirky, and he’s a good fellow. But he’s simply wrong about his claim that "tagging" (of the flavor that is appearing on del.icio.us — what I call "social tagging") is inherently better than the use of formal ontologies. Clay favors the tagging approach because it is bottom-up and emergent in nature, and he argues against ontologies because pre-specification cannot anticipate the future. But this is a simplistic view of both approaches. One could just as easily argue against tagging systems because they don’t anticipate the future — they are shortsighted, now-oriented systems that fail to capture the "big picture" or to optimally organize resources for the long-term. Their saving grace is that over time they do (hopefully) self-organize and prune out the chaff, but that depends both on the level of participation and the quality of that participation.

Tagging is certainly useful — and indeed collaborative authoring,
editing and filtering are powerful paradigms — but folksonomies (at
least present day ones) suffer from having too little formal structure
– tagging systems easily result in "metadata soup."  Ontologies are on
the other end of the spectrum — they are particulary useful for
accurately modeling the actual structure of the world, or of conceptual
domains — but admittedly in some cases their formal structure can be
overly rigid and specific. The benefit of tagging is primarily the
adaptive nature of the resulting taxonomies. The benefit of ontologies
is the rich, and unambiguous, semantics they define. Tagging systems
are useful when all that is needed is the ability to link items to
topics; ontologies are useful when what is needed is to rigorously
define or understand what is meant, or not meant, by particular
classes, fields and relationships — something that is essential for
good machine-processing of data.

One point that Clay makes, which I think is very interesting, is his
view that perhaps the world is moving from a graph-theory information
model (ontologies) to a set-theory model  (folksonomies) — but in
fact, under the surface this argument falls apart. OWL is nothing other
than a language for enabling extremely sophisticated set-theoretic
operations on information. In fact, if you actually look at the OWL
language itself, it is primarily comprised of set-theoretic statements.
I don’t really view graph-theory and set-theory as mutually exclusive
– in fact, they are highly connected, if not equivalent at a deep
level. But expressing information in graph form or set form does have
different benefits for certain types of information processing. In
particular, graphs can be beneficial when associative reasoning is
important — for example, when traversing links or networks between
nodes is key. Sets on the other hand are useful when relevance or
mutual membership are most important.

Clay discounts ontologies for many reasons. He has many arguments,
most of which have some merit, but fall short of convincing me (or
anyone in the field of knowledge representation). Indeed, tagging
systems are just special, highly simplistic cases of ontologies –
namely, they are ontologies with extremely basic semantics and almost
no constraints — they are even lower on the spectrum than taxonomies.
In fact, we could graph the spectrum of knowledge management as follows:

<—————————————————————>

Tags   Folders   Taxonomies   Databases   Ontologies

One of Clay’s early arguments against ontologies was that they are
merely systems for syllogistic logic — but in fact, that is simply not
the case. While the formal semantics of OWL doe support logical
inferencing and reasoning, that is not the only value of ontologies. In
fact, I think a much more important benefit of ontologies is simply
that they make the semantics of data structures explicit — which makes
it much easier to both process information, and integrate information
across different applications and representations. Ontologies are, in
my opinion, simply the next evolution of database schemas. Surely, Clay
would not argue that database schemas have no place in the world!

Another way of looking at ontologies and the semantic web is that
they do for the meaning of data what other markup languages have done
for the layout and structure of data. HTML provided a way to markup the
formatting of content. XML provided a way to markup the structure of
content. RDF and OWL provide a way to markup the meaning of
information. This is a logical progression, and it is something that
will really make the Web, desktop and enterprise easier to cope with.
Ontologies are not panaceas — but they are incredibly powerful when
used appropriately. And that is the operative word — they are not for
everything. Indeed, in cases where social tagging is sufficient,
ontologies may simply be overkill. But there are many, many cases where
social tagging simply does not, and cannot, have the semantic rigour
that is needed.

So what’s next? I think that ultimately we will see a synthesis of
these two approaches emerge. Imagine a folksonomy combined with an
ontology — a "folktology." In a folktology, users could
instantly propose or modify ontological classes and properties in the
same manner that they do with tags in tagging systems. The most popular
ontological constructs (the most-instantiated classes, or  slots on
classes, for example) would "rise to the top" and self-amplify, while
the less-instantiated ones would "fall to the bottom" over time. In
this way an emergent, self-organizing, and self-pruning ontology could
emerge within a community. Such a system would have the ease and
adaptability of a folksonomy plus the semantic richness and formal
structure of an ontology. I think ultimately a
<i>folktology</i> approach will be better than either
folksonomies or ontolgoies on their own.

Rohit Gupta, a Bombay-based writer, who also reads this blog, is writing a blog-novel. He has come up with an innovative way to promote it — by letting readers choose quotes from his text to “own” — by choosing a quote and linking to his blog-novel from it, he will in return link back to your blog from that quote in his novel. It’s similar to my earlier GoMeme experiments, except in this case his novel is the meme that is spreading via a cooperative linking incentive.

Good idea, Rohit! I choose this quote from your novel:

“The other article, an interesting one, is a 2000-word piece on the history of mathematical heretics known as the Circlesquarers, and the transcendental nature of the number Π.“

Greg Tyrell, a PhD student with a strong interest in bioinformatics, has put together a detailed analysis and report on the GoMeme 1.0 experiment, containing several visualizations and results of the survey. Nice work Greg!

Also in other news, Google has started indexing the results. Currently there are 733 results when searching for sites with original, super-long GUID. There are 867 results when searching for the unique string “To add your blog to this experiment, copy this entire posting to your blog, and fill out the info below, substituting your own information in your posting, where appropriate” which was in the instructions — this number should include sites that did not put the whole GUID in. Technorati, which seems to be working better today, finds 58 sites with the long GUID, and none for the instructions text above. So I guess Google wins so far. But I am glad that Technorati is starting to get their bugs fixed! I noticed that blog stats are starting to be updated again.

I also got an interesting link to another Meme visualization, which although having nothing to do with our experiment as far as I can tell, is a nice concept. It takes forever to build out the full visualization and the tree appears to be almost white on my white background making it hard to see, but still worth a look — Meme Tree

This article provides a good overview of the Weblog tools market, products, and market share.

Note: This experiment is now finished.

GoMeme 2.0 — Copy This GoMeme From This Line to The End of this article, and paste into your blog. Then follow the instructions below to fill it out for your site.

Steal This Post!!!! This is a GoMeme– a new way to spread an idea along social networks. This is the second generation meme in our experiment in spreading ideas. To find out what a GoMeme is, and how this experiment works, or just to see how this GoMeme is growing and discuss it with others, visit the Root Posting and FAQ for this GoMeme at www.mindingtheplanet.net .

By adding this GoMeme to your Weblog you can get higher Google rankings for your site, and help your friends get higher Google rankings too. Your blog will be linked from every other blog that discovers this GoMeme downstream from your blog (from your readers, their readers, and so on). And that will raise your Google rankings in proportion to the number of downstream bloggers that get this GoMeme from you and post it to their blogs. The more people who blog the GoMeme from your blog, the better your Google rankings will get.

By hosting this meme on your blog, you will also be participating in an experiment to generate a distributed Blog survey and test how memes spread through social networks. The dataset from this experiment is public, open and decentralized — every blog that participates hosts their own data about their own blog. Anyone can then get the whole dataset by just searching Google for this unique string: 98818912959q This code is the “global unique identifier,” or GUID for this GoMeme — it marks every web page that participates in this GoMeme so that it can later be found with all the others. (Note it may take a week or longer before Google indexes your blog, so be patient).

Disclaimer

This is purely an experiment and is just for fun. We are really just curious to see what will happen and this is not a commercial project. Participation is voluntary. We don’t mean to annoy anyone. However, if you don’t have much curiosity, or at least a sense of humor, you may find this experiment to be upsetting. In that case, you might try drinking a good strong cup of coffee. If after that you are still unhappy with us, just don’t read any further and have a great day! (If you don’t want your blog to get better Google rankings, that’s purely your choice!) On the other hand, if you are interested in exploring new technologies and pushing the envelope, then keep reading and we look forward to your participation in this experiment. We also request that participants in this experiment refrain from spamming anyone with this GoMeme. To spread it, just put it on your blog; that should be enough.

INSTRUCTIONS FOR ADDING THIS GOMEME TO YOUR OWN SITE

Step 1 First, to add your site to this experiment, copy the GoMeme to your site from the “Copy This GoMeme From Here” heading above to the End of this article. Please copy this whole article and try not to alter the text so that it is authentic for the people who get it from your blog. If you would like to come up with your own catchy headline, or anything else to help your GoMeme spread, feel free! Let’s see what works best.

Step 2: Now, fill in your answers to these Required Survey Fields (Note: Replace the answers below with your own answers). These will later be automatically data-mined by bots to compile the survey results.

(1) I found this GoMeme at URL: http://www.mindingtheplanet.com

(2) I found this GoMeme on date (day/month/year):03/08/04

(3) I found this GoMeme at time (in GMT format): 01:00:00

(4) I foundit via “Newsreader Software” or “Browsing the Web” or “Searching the Web” or “An E-Mail Message”: Browsing the Web

(5) I posted this GoMeme at my URL (use a hyperlink): Minding the Planet

(6) I posted this on date (day/month/year): 03/08/04

(7) I posted this at time (in GMT format): 01:00:00

(8) My posting location is (city, state, country): San Francisco, California, USA

Step 3: If you’re feeling very altruistic today, also fill in these optional survery fields (Replace the answers below with your own answers):

(9) My Weblog is hosted by: Typepad

(10) My age is: 35

(11) My gender is: Male

(12) My occupation is: Internet Entrepreneur, Ontologist, Writer

(13) I use the following RSS/Atom reader software: Typepad, FeedDemon

(14) I use the following software to post to my blog: Typepad, Zempt

(15) I have been blogging since (day, month, year): 05/08/03

(16) My web browser is: IE

(17) My operating system is: Windows XP

Step 4:Now add an entry for your site after the last entry in the PATH LIST below:
Your entry should be of the form: line number, URL, hyperlink, optional personal GUID for your blog.

(Note: If you would like to track all postings of the Meme that result from your posting of it, once Google has indexed them, you may add your own optional GUID after your hyperlink on your line of the Path List — just make sure it is short, unique, and doesn’t return any results on Google — for example “mysitename137a2r28″. Also note, if the path list gets too long, you should still try to include the whole path in your blog — even if you have to put the list on a continuation page rather than the excerpt for your posting — and make sure others copy the whole GoMeme along with your Path List when they get the GoMeme from you — If they don’t copy it, your blog and your upstream blogs won’t be linked from their blogs).

PATH LIST

1. http://www.mindingtheplanet.net Minding The Planet, mindingtheplanet14798
2. (your Path List entry goes here in the form URL, hyperlink, GUID. Also, please add a new line after this one, for the next person.)

The End

You did it! Now spread it! If all goes well and others find this GoMeme from your blog, you should see some interesting results. Please comment back on the original post and tell us how you’re doing or what you observe, if anything noteworthy happens.

I wonder if anyone from MoveOn.Org or the Republicans will notice our GoMeme experiments? (Not that I’m taking sides — I’ll simply be happy if somebody wins the election!) Grassroots political campaigns could potentially really benefit from the techniques we’re testing here. For example, imagine a “blog meme” for a political campaign — a meme that states some useful facts about a candidate and their opponent, perhaps has some survey questions and a GUID, and has the added benefit of a cool Improve-Your-Google-Ranking-By-Hosting-This-Meme candy coating? Wow — it could spread the message to a lot of blogs pretty quickly if done right. That might actually work. But I try to stay out of politics, so I’m not taking sides here or endorsing anyone. If you read this and know the “right people” — feel free to suggest the idea to them.

This posting is the FAQ and introduction for a new, improved, second-generation meme experiment that is designed to spread faster and more broadly than the first meme experiment. We call this kind of meme a “GoMeme” (pronounced Go-Meem), because it is a meme that is designed to Go. The actual GoMeme, which you can add to your Website is located, here. Before you do this, please read this FAQ so you know how it works.

Introduction

This new GoMeme is better than the first design because it’s more beneficial to you to participate. Why? Because by participating in this GoMeme, you may be able to raise the Google rank and visibility of your blog. In other words, this GoMeme rewards your blog for hosting it.

In a nutshell, by following the instructions below, your blog will be linked from every other blog that discovers this GoMeme downstream from your blog. And that will raise your Google rankings.

How well does it work? Well, in the first experiment, www.mindingtheplanet.net, made it from not being in the list, all the way up to the number 3 position in the www.daypop.com Top 40 blogs index in just 2 days, even beating Matt Drudge, the New York Times, John Kerry, numerous cool movie trailers, and many other hot topics of the day. Now, in this new experiment, everyone can benefit in a similar way, by leveraging the power of their social networks. For instructions, keep reading…

This new version is also shorter and easier to participate in. For starters, you don’t have to copy all of this text into your blog, you just need the text from the “Copy This GoMeme From This Line” heading below to the end.

Is this Good or Evil?

Before we go much further, let’s clear up one burning question you might have: Is this evil? No, in fact it’s good, it’s altruistic and grassroots — you are helping to promote your friends’ weblogs, while pioneering the use of memes for marketing and pushing the envelope of how Weblogs and social networks can be used. Is this GoMeme a chain-letter? No, it is not a chain-letter, although it may seem like one at first glance. Chain letters are mailed to people, usually without the recipients asking for them. This GoMeme is voluntarily posted by you on your weblog and then voluntarily read and voluntarily spread by your visitors. It is really a vector for an idea — and for your weblog — just like any Weblog posting in fact. (Note: We do not condone chain-letters!)

What is a GoMeme?

So what is this GoMeme thing then? It is a new way to help your friends and get helped by them. It is a new way to grow your blogroll (the list of blogs that you link to from your blog) and a new way to get your blog listed in the blogrolls of other blogs in your social network. By participating in this GoMeme, you, and everyone in your social network, can then get higher Google rankings. Think of it as a much smarter social-network-based blogrolling community. You could actually use this beyond just Weblogs — you could use it to promote any site, or anything in fact. But Weblogs are the perfect medium because they are a form of “social software” — they naturally spread ideas, that’s the whole point of Weblogs.

You may also wonder, what is the actual “meme” being spread by this GoMeme? Well, looking at it one way, it is this entire posting. Looking at it another way, there are many memes within this posting, such as the concept of a “GoMeme” and the many other ideas here, the concept of growing a blogroll via a social network, and the concept of a blog, all of which are memes in their own right — and your weblog URL could soon be one of these memes, if you participate.

A Collaborative, Distributed, Emergent Blogroll

This GoMeme is effectively a collaborative, distributed, emergent blogroll. It is no different really than any blogroll (any list of other blogs you add to your blog) — it just forms in a different way. Instead of you adding all the links to it, your social network adds them and then you add yours at the end and send it on to others in your social network. There’s no top-down control or guidance of the process. Every blog that participates is equal. Nobody knows what the result of this experiment will be.

Why Are We Doing This?

OK, so why are we doing this? The short answer is, “Because we can!!!” But seriously, we’re also doing this because it is an interesting way to generate a dataset that we and others may study to analyze how ideas move across social relationships on the Web, and how communities can emerge and self-organize. It’s fun and it’s research, and anyway, it’s harmless and it helps bloggers get better visibility, so we figured we’d just try it and just see what happens! We hope you’ll join us!

How Does it Work?

Just follow the instructions to fill out your blog’s answers to the GoMeme survey and add your blog’s URL to the “PATH LIST” at the bottom of the GoMeme. The path list is the history of all the blogs that the meme traveled through to reach you. The last URL before yours in the path list should be the URL for the blog you discovered the GoMeme on. By adding your URL after it, your blog URL becomes part of the path for the GoMeme.

Everyone who gets the GoMeme downstream from you will then include your URL on their blog. And by doing that, they are in effect linking to your blog from their blog, which in turn raises your blog’s Google rank. By posting this GoMeme to your blog, you help raise the rankings of every blog in the path before yours, and every blog that later posts it as a result of your blog is then helping to raise your Google ranking. Kinda cool, huh?

Can Your Blog Out-Rank the A-List Blogs?

If the new GoMeme design works as we hypothesize it might, it could help a lot of lesser known blogs get better rankings than even the “A-List” blogs. In other words, it’s kind of like unionizing to beat the big guys. There is strength in numbers, after all. Let’s see if this works! If it does work, we should find lots of lesser-known blogs that participate in this experiment appearing in the “top lists” of the major blog indexes. Who knows, maybe we can even take over the top lists? For some proof, just look at the results of the first meme experiment which launched the Minding The Planet weblog to the number 3 slot of the Daypop Top 40 blog posting index in just two days! Who knows, maybe it will be your blog up there next?

OK, so do you want to add your Weblog to the GoMeme experiment??? Great, then Get the GoMeme!