Explosion of content on the Internet
Currently, a lot of information is
being published in the Internet as blogs, which are rich in content, frequently
published and scattered across numerous sites. MSDN
Blogs alone hosts around 2000 blogs. It is very difficult to aggregate
this information and get a consolidated view of the same. RSS readers and
content aggregators have tried to help us achieve this to some extent, but
these tools cannot scale up to handle the voluminous and widespread content in
the Internet.
The brain as a better model for
describing the Internet
The Internet in its current form represents the collective intelligence of
humanity and it has many characteristics that are similar to the human brain.
Just like new connections are made between neurons in our brain as we learn new
things, as new concepts emerge on the Internet, the links between the documents
that describe the concept gets stronger – quite similar to the organic growth
that we see in the brain. Also in the brain the connections between the neuron
are more important than the individual neuron (though the neuron forms an
integral part of the whole, they are far too many to be considered
individually). Similarly in the web the concepts that emerge out of connected
documents are more interesting than the individual document itself. One might
argue that a document(s) authored by a few authoritative person(s) on a subject
might be a better representation than the collection of documents made by the
whole crowd. Though it might sound counter intuitive, in his work titled 'the
wisdom of crowds' James Suriowecki explains that a better
representation and a more accurate picture emerges out of the collective
decision of the crowd than the work of a selected few. This is also probably
one of the factors behind the success of Wikipedia as an accurate encyclopedia.
Currently the most prominent means of getting information from the Internet is
through search. This approach is good enough if we already know what we are
looking for – or if we know the right question to ask. But if we visit the
Internet with the intension of finding something new, a better approach would
be to navigate the Internet directory or taxonomy.
Benefit of Folksonomy in favor of
Taxonomy
Lets take the previous use-case of browsing through MSDN blogs, looking for
something 'new’ and ‘interesting’ – this is a good example of a situation where
I wouldn’t know what exactly to search for. Instead of individually going
through each blog, I can extract the statistically unique terms to form a
taxonomy. My intension in doing this exercise is to distill the contents of
more than 2000 blogs into a few words and then pick out (from the resultant
set) those terms that I find to be interesting. This can be easily done using
TagCloud.
You can see the original cloud
here.
Is this auto-generated taxonomy good enough representation of what is published
through MSDN blogs? In my opinion-No. This result is purely statistical in
nature and I would compare it to the result of Google index with out 'page
rank'. It does not take into account the collaborative content selection and
filtering that happens usually on the Internet. It is this additional data that
makes the data more relevant. A better approximation would be to use the
celebrative tagging also referred to as 'Folksonomy'.
The term folksonomy is defined in wikipedia as "a neologism for a practice of
collaborative categorization using freely chosen keywords. More colloquially,
this refers to a group of people cooperating spontaneously to organize
information into categories, typically using categories or tags on pages, or
semantic links with types that evolve without much central control."
This kind of tagging allows for the kind of multiple, overlapping associations
that the brain itself uses, rather than using rigid categories. Such
flexibility in using tags is both good and bad. On one hand we have tags like
'blog' and 'blogs' appearing as different tags. On the positive side, a photo
of a smiling baby might be tagged 'baby', 'happy' and 'cute'. So in effect
folksonomy produces results that more accurately reflect the population's
conceptual model of the information.
The need for better tooling
If the brain is a better representative model of how the Internet works then we
need different kind of tools to navigate and retrieve information from it. To
be able to cope up with the vast amount of information, it should be capable of
navigating across concepts instead of across documents. And once we locate our
exact match, we should be able to drill down to it. To explain this new UI,
lets take the example of Google Earth.
To be able to locate a particular spot on earth (which is not previously tagged
by Google - hence not available to search), we can take two approaches. The
brute force approach would be to hunt through all the locatable points on the
surface, until we reach our point. A more efficient strategy would be to zoom
out (in other words elevate our self to a higher altitude), where we get an
over all picture and then drill down to our point of interest. So to handle
more complex problems, we need to create better abstractions. Another benefit
of higher abstractions is that, at higher level we can easily spot associations
and connections between locations (or concepts) that are hard to find at ground
level. In the analogy, just as we are able to navigate across continents,
countries and states, we should be able to navigate across concepts that emerge
out of the Internet. Another vital feature that is missing in the tools that
are currently available is the ability to discover and make connections between
concepts. It is this lack of tooling that led me to envision FolkMind.
The vision of FolkMind
To me the new killer app for the Internet should help me in working at any
levels of abstraction. The higher the abstraction, the more volume of
complexity and data I can handle. Also at any level of abstraction, I should be
able to navigate between concepts that are visible at that level and observe
new connections that were not apparent to me at a different abstraction. And
when I want to dig deeper, it should help me in exploring more on that subject.
At the lowest level of abstraction, it would resemble a browser. The mass of
the content that is on the Internet will still be on HTML, which is doing a
good job of capturing presentation information, and a browser is suitable to
view this. In short this application should act as a seamless extension to mind
and help me in generating ideas by creating new connection between concepts
about which I have little or no previous knowledge by leveraging the collective
intelligence of humanity. A 'mind map' would be a good UI (an example of such a
UI is shown below) for representing the above-mentioned vision. Wikipedia
defines the term 'mind map' as 'a pictorial representation of how a central
concept is linked to other concepts and issues'.
As a start we can create a mind map of the existing folksonomy that already
exists on the Internet (with data from sites like del.icio.us) and then add new
content and nodes to it. In his article entitled "Using
Wikipedia and the Yahoo API to give structure to flat lists",
Matt Biddulph explains a simple method for automatically converting a
set of terms into a connected graph. To me the idea of linking together
concepts is quite powerful. Once we reach a critical mass of concepts defined
in such a mind map, it can transform itself from a concept management tool to
an idea generation tool.
A new person who logs into FolkMind can start with the most popular folksonomy
terms and from that point browse related concepts or he can start by searching
for a particular concept. Each node in the mind map can be tagged with
additional information like a short description, its relevance (based on
algorithms similar in principle to the one used by Google page rank), and
additional information. This is the highest level of abstraction and at this
level the user is more concerned with the connections between concepts than the
individual documents that contributed to that concept. With usage the
folksonomy gets richer and more concepts and connections between concepts
emerge. Once the relevant concepts are identified, the next step is to drill
down to the individual documents that pertain to that subject. If the Internet
can be considered as the virtual brain that represents the collective
intelligence of humanity, then FolkMind is the pictorial representation on the
same expressed as a mind map – hence the name.
How does FolkMind fit in as a Web 2.0
application
Let me explain how FolkMind application demonstrates the traits that are
commonly observed in Web 2.0 applications. FolkMind can be a thick client that
connects to the FolkMind server to retrieve its content but it uses the client
side processing power for rich interactive UI and for local cache. As the user
interacts with the UI, any change is reflected back to the server (this is
similar to how Google Earth works). Though a user is given the option of
marking certain connections as private, all other new connections and nodes
that are created by the user will be stored on the server and will be visible
to other users. This action is similar to a person creating a bookmark and
tagging it using del.icio.us. Thus a user pursuing selfish interests (the
motive behind creating a new connection or node is for his own benefit) build
collective value for the rest of the users as a side effect. This phenomenon
(also referred to, as the network effect) is critical to the success of a Web
2.0 application. As more content gets added to the system and as more users
join in, the value of existing users will grow.
Summary
As we have seen above, the vision behind FolkMind is to be a powerful
application with an intuitive, interactive UI that can harness the power of
Internet by being capable of handing huge volume of data. Eventually, this will
become the virtual brain of humanity!
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