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[ /Author (Tim Berners-Lee and Lalana Kagal)
/Title (Semantic Web: Engineering for a Fractal space)
/Keywords (AAAI, artificial intelligence, web, semantic web, ontology)
/DOCINFO pdfmark}

\documentclass[letterpaper]{article}
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\begin{document}

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\title{Semantic Web: Engineering for a Fractal space}

\author{Tim Berners-Lee and Lalana Kagal\\
Massachusetts Institute of Technology\\
Computer Science and Artificial Intelligence Lab \\
Cambridge, MA 02139 \\
\{lkagal, timbl\}@csail.mit.edu
}

\maketitle  

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\comment{
http://www.w3.org/DesignIssues/Fractal.html#Berners-Le

http://www.w3.org/2006/Talks/0718-aaai-tbl/Overview.html#(5)

http://bigfractaltangle.com/archive/2003/11/23.jsp

http://www.assumption.edu/ahc/1920s/demotic%20art/6jan18Krazy.gif

}

\begin{abstract}

Many knowledge representation systems in the past failed to scale
because they were too monolithic, whereas other systems failed to have
an impact because they were small and isolated. There is also a
constant tension between the cost involved in building a larger
community that can interoperate through common terms, and the cost of
the lack of interoperability when this is not done.The Semantic Web is
a set of standards for knowledge exchange that is aimed at providing
interoperability across applications and organizations. The Semantic
Web achieves wide-scale communication and interoperability using
finite effort per person. The gathering success of Semantic Web
technology is not derived from the particular choice of logic or
syntax. The main contribution is that the technology recognizes that
scalable systems on the Web are composed of many overlapping
communities that have internal (but not global) consistency, where
those communities are of all sizes ranging from 1 to the entire
population.  Communication between agents will contain some terms from
a global ontology and some from local ontologies. The amount of data
that can be understood and reused by the interacting agents will
depend on how many communities they have in common and how many
ontologies they share. The fractal patterns found in nature seem to
present themselves as a good compromise between large, monolithic
systems and a set of isolated systems leading us to expect a fractal
distribution of ontologies on the Semantic Web. In this paper we
describe how Semantic Web technologies were designed in order to meet
the fractal nature of the Web.

\comment{We should use knowledge of the fractal nature of the Semantic
  Web to build an effective society on top of it.}


\end{abstract}


\section{Introduction}

Many patterns in Nature including clouds, mountains, leaves, and even
languages are fractal in that they have repeating structures at every
scale and cannot be modeled with classical geometry \cite{Mandelbrot,
  "Fractals," 1977}. \comment{These patterns are also irregular and
  are self-similar i.e. they repeat at every scale.} Fractals provide
solutions to capture and think about complex and irregular
patterns. They can be used to predict weather, to design antennae, and
even to characterize metal. Identifying that a pattern is fractal
helps us model and analyze it appropriately. The democracy of the Web
where everyone can create their own data, link to or reuse (parts of)
existing data causes the Web to demonstrate the self-similar patterns
of fractals. \comment{that lead to a ``big fractal tangle''} 

Classical knowledge representation theory lead to the development of
large monolithic ontologies such as Suggested Upper Merged Ontology
(SUMO) \cite{sumo} and Cyc \cite{lenat95cyc}. These large ontologies
are usually developed by a small group of people with a lot of time
and effort and try to meet the requirements of a much larger group of
users. On the other end of the scale are small, isolated (stove pipe)
systems that are developed by larger sets of software
engineers. Desktop applications are an example of this. Each
application usually has a specific purpose such as scheduling
appointments or developing spreadsheets and cannot re-use information
produced by other applications. It is not possible to have a calendar
view of your bank statements or to put your pictures into your
scheduler. \comment{Another example is of organization-specific
  applications such as} From these two extremes, it is clear that
there is a tradeoff between size and effort versus re-use. However,
neither of these approaches are useful on the Web.  It appears that
human groups are stable when they have a set of peers and when they
have a substructure. Neither the set of peers nor the substructure
must involve huge numbers, as groups cannot "scale". That is groups
cannot work effectively with a very large number of liaisons with
peers, or when they are composed of a set of a very large number of
parts. Then by induction there must be a continuum of group sizes from
the very largest to the very smallest. Similarly, we recognize that
scalable systems on the Web are/will be composed of many overlapping
communities that have internal (but not global) consistency, where
those communities are of all sizes ranging from 1 to the entire
population. Ontology use will also be fractal. Each community will
have its own ontology but also use global ontologies. Communication
between agents in the same community will contain some terms from a
global ontology and some from local ontologies. The amount of data
that can be understood and reused by the interacting agents will
depend on how many communities they have in common and how many
ontologies they share.

In order to allow for this fractal growth of the Semantic Web we
observe that Semantic Web technologies should (i) allow use of terms
from different ontologies, (ii) allow extensibility so individuals can
create new terms or ontologies without waiting for consensus from a
governing body, and (iii) allow portions of ontologies/data to be
dropped/ignored without affecting the meaning of the other concepts.

In this article we describe how the fractal nature of the Web affected
the development of Semantic Web technologies and how we can exploit
this behavior while designing effective systems over the Web.

\section{Fractal-ness In Human Societies}

Lesson: fractal ness occurs in nature


\section{Example of fractal ontologies}

Label on coke can - one part is required and used by feds, one by
store, one by Coke, one by consumer, one by FDA, etc. Every
communication/document refers to several namespaces. Also, even though
there is info that fda cannot understand on the label doesn't make the
whole label wrong or unusable for fda.


\section{Engineering for a fractal space}

Given the fractal ness of the real world, we tried to engineer s/w
technologies so that they could be useful in a fractal space.

can use terms from different ontologies (namespaces)

drop triples: if someone doesn't understand a portion of an RDF graph,
it can be ignored/dropped easily. Triples are conjuncted only, having
both conjunction and disjunction would have made it difficult to drop
irrelevant portions.

communities can come up with local ontologies and work w/o
standardization. Standardization is a way to take norm/ontology from a
local group to a larger sized group. ... taking things to a global
scale ?

role of standardization

\section{Current Exciting Work}

dbpedia with its link to the genome info

examples of web 

examples of sw


\cite{bl04delta}

\section{Future Work}
While editing in the tabulator
What else

\section{Conclusion}

The world is fractal ! SW technologies were designed for that. Don't
try to create a global ontology, do try to (i)....

\bibliography{fractal-paper}
\bibliographystyle{aaai}


\end{document}


