I know, Stevan wants to keep this listserve focuses on open access.
But at the same time, the article below from the today’s New York
Time is a very best argument for open access.
Essentially, all this new development, what they call Web3.0 (not 2.0)
only flies well, if the scientific information is open access. There
might be otherwise a danger, that scientific information becomes less
relevant if Web3.0 would start to build up insights based on the numerous
wikis, newsfeeds and other sources.
Donat
http://www.nytimes.com/2006/11/12/business/12web.html?ei=5094&en=a34a6306f48166
b&hp=&ex=1163394000&partner=homepage&pagewanted=print
November 12, 2006
Entrepreneurs See a Web Guided by Common Sense
By JOHN MARKOFF
SAN FRANCISCO, Nov. 11 — From the billions of documents that form
the World Wide Web and the links that weave them together, computer
scientists and a growing collection of start-up companies are finding new
ways to mine human intelligence.
Their goal is to add a layer of meaning on top of the existing Web that
would make it less of a catalog and more of a guide — and even
provide the foundation for systems that can reason in a human fashion.
That level of artificial intelligence, with machines doing the thinking
instead of simply following commands, has eluded researchers for more
than half a century.
Referred to as Web 3.0, the effort is in its infancy, and the very idea
has given rise to skeptics who have called it an unobtainable vision. But
the underlying technologies are rapidly gaining adherents, at big
companies like I.B.M. and Google as well as small ones. Their projects
often center on simple, practical uses, from producing vacation
recommendations to predicting the next hit song.
But in the future, more powerful systems could act as personal advisers
in areas as diverse as financial planning, with an intelligent system
mapping out a retirement plan for a couple, for instance, or educational
consulting, with the Web helping a high school student identify the right
college.
The projects aimed at creating Web 3.0 all take advantage of increasingly
powerful computers that can quickly and completely scour the Web.
“I call it the World Wide Database,” said Nova Spivack, the
founder of a start-up firm whose technology detects relationships between
nuggets of information by mining the World Wide Web. “We are going
from a Web of connected documents to a Web of connected data.”
Web 2.0, which describes the ability to seamlessly connect applications
(like geographic mapping) and services (like photo-sharing) over the
Internet, has in recent months become the focus of dot-com-style hype in
Silicon Valley. But commercial interest in Web 3.0 — or the
“semantic Web,” for the idea of adding meaning — is
only now emerging.
The classic example of the Web 2.0 era is the “mash-up”
— for example, connecting a rental-housing Web site with Google
Maps to create a new, more useful service that automatically shows the
location of each rental listing.
In contrast, the Holy Grail for developers of the semantic Web is to
build a system that can give a reasonable and complete response to a
simple question like: “I’m looking for a warm place to
vacation and I have a budget of $3,000. Oh, and I have an 11-year-old
child.”
Under today’s system, such a query can lead to hours of sifting
— through lists of flights, hotel, car rentals — and the
options are often at odds with one another. Under Web 3.0, the same
search would ideally call up a complete vacation package that was planned
as meticulously as if it had been assembled by a human travel agent.
How such systems will be built, and how soon they will begin providing
meaningful answers, is now a matter of vigorous debate both among
academic researchers and commercial technologists. Some are focused on
creating a vast new structure to supplant the existing Web; others are
developing pragmatic tools that extract meaning from the existing Web.
But all agree that if such systems emerge, they will instantly become
more commercially valuable than today’s search engines, which
return thousands or even millions of documents but as a rule do not
answer questions directly.
Underscoring the potential of mining human knowledge is an
extraordinarily profitable example: the basic technology that made Google
possible, known as “Page Rank,” systematically exploits human
knowledge and decisions about what is significant to order search
results. (It interprets a link from one page to another as a
“vote,” but votes cast by pages considered popular are
weighted more heavily.)
Today researchers are pushing further. Mr. Spivack’s company, Radar
Networks, for example, is one of several working to exploit the content
of social computing sites, which allow users to collaborate in gathering
and adding their thoughts to a wide array of content, from travel to
movies.
Radar’s technology is based on a next-generation database system
that stores associations, such as one person’s relationship to
another (colleague, friend, brother), rather than specific items like
text or numbers.
One example that hints at the potential of such systems is KnowItAll, a
project by a group of University of Washington faculty members and
students that has been financed by Google. One sample system created
using the technology is Opine, which is designed to extract and aggregate
user-posted information from product and review sites.
One demonstration project focusing on hotels “understands”
concepts like room temperature, bed comfort and hotel price, and can
distinguish between concepts like “great,” “almost
great” and “mostly O.K.” to provide useful direct
answers. Whereas today’s travel recommendation sites force people
to weed through long lists of comments and observations left by others,
the Web. 3.0 system would weigh and rank all of the comments and find, by
cognitive deduction, just the right hotel for a particular user.
“The system will know that spotless is better than clean,”
said Oren Etzioni, an artificial-intelligence researcher at the
University of Washington who is a leader of the project. “There is
the growing realization that text on the Web is a tremendous
resource.”
In its current state, the Web is often described as being in the Lego
phase, with all of its different parts capable of connecting to one
another. Those who envision the next phase, Web 3.0, see it as an era
when machines will start to do seemingly intelligent things.
Researchers and entrepreneurs say that while it is unlikely that there
will be complete artificial-intelligence systems any time soon, if ever,
the content of the Web is already growing more intelligent. Smart Webcams
watch for intruders, while Web-based e-mail programs recognize dates and
locations. Such programs, the researchers say, may signal the impending
birth of Web 3.0.
“It’s a hot topic, and people haven’t realized this
spooky thing about how much they are depending on A.I.,” said W.
Daniel Hillis, a veteran artificial-intelligence researcher who founded
Metaweb Technologies here last year.
Like Radar Networks, Metaweb is still not publicly describing what its
service or product will be, though the company’s Web site states
that Metaweb intends to “build a better infrastructure for the
Web.”
“It is pretty clear that human knowledge is out there and more
exposed to machines than it ever was before,” Mr. Hillis said.
Both Radar Networks and Metaweb have their roots in part in technology
development done originally for the military and intelligence agencies.
Early research financed by the National Security Agency, the Central
Intelligence Agency and the Defense Advanced Research Projects Agency
predated a pioneering call for a semantic Web made in 1999 by Tim
Berners-Lee, the creator of the World Wide Web a decade earlier.
Intelligence agencies also helped underwrite the work of Doug Lenat, a
computer scientist whose company, Cycorp of Austin, Tex., sells systems
and services to the government and large corporations. For the last
quarter-century Mr. Lenat has labored on an artificial-intelligence
system named Cyc that he claimed would some day be able to answer
questions posed in spoken or written language — and to reason.
Cyc was originally built by entering millions of common-sense facts that
the computer system would “learn.” But in a lecture given at
Google earlier this year, Mr. Lenat said, Cyc is now learning by mining
the World Wide Web — a process that is part of how Web 3.0 is being
built.
During his talk, he implied that Cyc is now capable of answering a
sophisticated natural-language query like: “Which American city
would be most vulnerable to an anthrax attack during summer?”
Separately, I.B.M. researchers say they are now routinely using a digital
snapshot of the six billion documents that make up the non-pornographic
World Wide Web to do survey research and answer questions for corporate
customers on diverse topics, such as market research and corporate
branding.
Daniel Gruhl, a staff scientist at I.B.M.’s Almaden Research Center
in San Jose, Calif., said the data mining system, known as Web Fountain,
has been used to determine the attitudes of young people on death for a
insurance company and was able to choose between the terms “utility
computing” and “grid computing,” for an I.B.M. branding
effort.
“It turned out that only geeks liked the term ‘grid
computing,’ ” he said.
I.B.M. has used the system to do market research for television networks
on the popularity of shows by mining a popular online community site, he
said. Additionally, by mining the “buzz” on college music Web
sites, the researchers were able to predict songs that would hit the top
of the pop charts in the next two weeks — a capability more
impressive than today’s market research predictions.
There is debate over whether systems like Cyc will be the driving force
behind Web 3.0 or whether intelligence will emerge in a more organic
fashion, from technologies that systematically extract meaning from the
existing Web. Those in the latter camp say they see early examples in
services like del.icio.us and Flickr, the bookmarking and photo-sharing
systems acquired by Yahoo, and Digg, a news service that relies on
aggregating the opinions of readers to find stories of interest.
In Flickr, for example, users “tag” photos, making it simple
to identify images in ways that have eluded scientists in the past.
“With Flickr you can find images that a computer could never
find,” said Prabhakar Raghavan, head of research at Yahoo.
“Something that defied us for 50 years suddenly became trivial. It
wouldn’t have become trivial without the Web.”
Dr. Donat Agosti
Science Consultant
Research Associate, American Museum of Natural History and Naturmuseum
der Burgergemeinde Bern
Email: agosti_at_amnh.org
Web:
http://antbase.org
Blog:
http://biodivcontext.blogspot.com/
Skype: agostileu
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Received on Tue Nov 14 2006 - 11:12:06 GMT