We bring fidelity
to Knowledge solution
issues .
OntologyStream
Three-Year Plan
Version: February 5, 2003
Version September 15, 2002 is archived
http://www.ontologystream.com/threeYearPlan/plan.htm
Executive Summary
OntologyStream
Inc (OSI) was founded (2001) to serve as an incubator for emerging technologies
that contribute to human information production and the management of private
and social knowledge. Our strategy is
to establish a business econiche based on results from experimental cognitive
neuroscience, systems theory and logio-mathematical foundations; as appropriate
to computer science.
OntologyStream’s primary business is to assist
scientists, innovators and software developers in the rapid development of
computer science around a specific set of first principles of knowledge
experience and knowledge propagation in communities.
The OntologyStream envisions a process that (1) specifies basic innovation,
(2) assists in reducing to practice these innovations into a common software
development framework, (3) maps this IP within a representation of emerging IP
centered on the knowledge technologies, (4) properly files for patents with
PTO, and (5) provides a curriculum for knowledge management certification
programs.
Mission
Statement
In recent years a community of scientists have focused
more and more on why there seems to be a considerable separation between new
advances in cultural / human science and what is called information
technology. An economic opportunity
emerges that will reduce this separation.
Within our community of scientists a proposal has been
developed over a period of a decade. With the definition of first principles we
go back to the beginning of computer science and into the history of logic and
mathematics. We are concerned over the
nature of abstraction and theories of logical and causal entailment
(causes). The proposal is that, by
using more of the biological and social models of intelligence and behavior,
society might step away from some specific intractable problems that are rooted
in information technology and computer science.
We are concerned that information technology must give up
the artificial intelligence myth, e.g., that computers can have cognition of
the type experienced by human.
Dispelling this myth is the key to entering the “knowledge age”, since
as long as the myth persists society cannot see what is possible given a theory
of natural computing.
In order that a science of knowledge is
established, we believe that a technology of knowledge sharing must be
developed and demonstrated in the marketplace. Scientists have long recognized
that economic power provides a path to the proper establishment of
university-based departments of knowledge science. We have looked long and hard for a means to establish this
economic power, and have found this means in (1) a proper response to the
current crisis in intelligence vetting, (2) the growing awareness of the
intractability of certain social, medical and environmental problems, (3) a new
paradigm in business-to-business transactions, and (4) intellectual property.
Overview of OntologyStream Intentions
Intentions
This white paper examines the
cultural, scientific and technical issues that we as a society face in the
establishment of a new computer technology that is properly grounded in the
natural sciences. We address rationale
for why OntologyStream Inc is in a position to participate in distributed
computation infrastructure now available to the science and technology
communities. Our value proposition is
being advanced to certain types of venture capitalists and to the rank and file
of those parts of society most affected by the limited success of information
technology in the production of knowledge systems.
We expect to raise at least $3,400,000
from a stock issue over the next three years (2003 – 2005). A total capitalization will use an
authorization of not more than 1,000,000 shares of OSI stock. These shares will not be available
for public purchase and will be handled under the Rule 504 of the Blue Sky
Laws, and Virginia Commonwealth law.
We seek investment from established technology companies. Ideally we would find OntologyStream stock
owned by a consortium of between 5 - 10 companies, with each company owning not
more than 5%.
This income will serve to provide
stability to a process that has wide support, in the universities, but which
has not been able to reach a critical mass needed to deploy a proof of
principle in the form of the Knowledge Sharing
Foundation.
The Problem and Opportunity
As individual scientists, who have
worked in industry for decades, we have often experienced a long process of
advocating advanced technology systems based on sound scientific
principles. Often, after funding is
awarded, information scientists are told that management views the
core-unsolved problems as “mere engineering”.
We have case study after case study detailing this ubiquitous behavior
by management in the IT firms. The
viewpoint, and economic dominance by management, points to the well recognized
“impedance mismatch” between science and management. But this mismatch has become more and more obvious to policy
makers and business leaders.
One feature of the current business
practices in the area of information technology infrastructure development is
the effect of marketing when there is no product, or when the product has very
few of the actual properties that are characterized in the marketing
process. With PowerPoint presentations
and nice pictures one can talk as if the current personnel management and
information technology systems provide predictiveness and prevention of
terrorism, for example. And it is big
business to do this. Everyone
knows. Likewise, one can talk as if the
current personnel management and information technology systems provide
enterprise productivity via compliance models.
But the sense making that occurs during these marketing sessions are
largely, but of course not completely, illusions.
Our small science community observes
that the natural development of the knowledge technology and science has been
inhibited by several factors.
Reductionism exists in science as a separate and long-standing problem
for science, but just happens to be involved in the defense of existing
information technology systems.
Artificial Intelligence over-sells the capacity of the computer program to
think and do other human like cognitive functions, while accounting-type
thinking under-sells the human ability to act in responsive ways to common
needs and challenges.
We expect that community-based
collaboration can only occur if there is a healthy technical and business community
that is dedicated to the proper development of knowledge technology systems.
The architecture of “stratified
knowledge management” technology is presented in Prueitt’s book, “Foundations
of Knowledge Science”, and in this book the theoretical and notational linkage
between Pribram’s cognitive neuroscience and stratified knowledge management
systems is described. The holonomic
model of perception and cognition was expressed in Pribram’s 1971 book, “Languages
of the Brain”, and then again in the 1991 book “Brain and Perception”.
What has been absent is the economic engine required to
develop knowledge technology based on the natural sciences. By natural science we mean specifically
Pribram’s work and other work that develops the science of knowledge experience
by individual humans and by social systems.
As this economic engine is finally put into place, the power and simplicity
of stratified knowledge technology will maintain the viability of the
engine.
During the recent year, Prueitt has
developed new innovations related to an Ontology Lens, and has been
appointed as a Research Professor at The George Washington University.
How will this work?
We have developing a community-based
financial engine, called the Knowledge Sharing Foundation, that
compensates individuals and companies for innovative work. The engine depends on the protection
provided by well-developed and properly cited patent applications.
OntologyStream
Inc will provide low cost community-based patent application and maintenance services.
A stream of revenue is directed at
profit making by OntologyStream (a private company having investors who expect
a Return On Investments).
A stream of revenue will establish the
BCNGroup (a not for profit corporation) in-support of the knowledge science and
technology communities.
i)
BCNGroup Charter provides for curriculum and educational
programs.
ii)
BCNGroup Charter provides for prizes by comprehensive peer
review of innovative work by a Science Committee.
iii) The BCNGroup
has a small but growing open membership.
A stream of revenue directed at
creating individual small companies based on some selected portion of the
acquired IP.
i)
Several models have been under development for the optimal
development of a simple company based on a specific innovation. These models include the model of
innovation adoption as technology from the Cambridge Group (Donald Campbell),
and a model being developed by a group at Stanford University.
ii)
Companies to be created in this way are to be governed, during
the creation process, by principles from the BCNGroup Charter.
OntologyStream has no debt at this
point, and Dr. Prueitt currently, February 5, 2003, owns 100% of the OSI
stock.
Overview of our research on
Intelligent Systems
A stratified
paradigm, related to physical science, is seen in the research
literatures. Stratification is viewed
as an essential element to information agility and real time interaction
between humans and various machine representations of structural patterns in
data sets.
We see
physical stratification of organizational levels as an essential element in the
proper science of human perception and cognition.
In the formalism of stratified theory,
"small formative ontology" appears from a tri-level architecture
using a dynamic and evolving ontology.
The lower level of this architecture contains the elements that are the
invariance (occurring more than once) across many instances. The upper level is environmental context and
the middle level is the small formative ontology.
Small formative ontology is (1)
consistent with what the scientists know about memory, awareness and
anticipation, (2) has agility and responsiveness to human information
interactions and (3) leads to eventChemistry and categoricalAbstraction as
rendered visually in existing software.
We currently offer several significant
contributions in massive data structuring/organization. We provide a new method for recognizing and
using regularity in data structures.
The regularity in observed data sets simplify the computer science. Second, we provide a method for visualizing
the substance of data invariance, as category, and relationships between categories. Human aid is then enrolled to provide
meaning to the visualized structure. We
are able to offer mutually beneficial interfaces to other technologies and
research teams, and to control economic benefits for the community because of
patent protection. Third, we provide an
ontology lens.
We begin with the following design
principles for a human information interaction system that supports perception
of pattern novelty within massive data flow.
·
Patterns of expression in data allow for a simplifying bypass of
computational complexity.
·
Categorical abstractions serve as the ‘atoms’ of cognition.
·
Cognitive graphs represent knowledge within a community of
practice.
The natural capabilities of human cognition
and perception are put to use. These
capabilities include anticipation, memory, and awareness as experienced by
humans in iterative action perception cycles.
·
Generation of top down expectancy based on measures of
informational coherence, opponent processing, and frames of reference
·
Generation of bottom-up aggregation of perceived invariance and
patterns.
·
The representation and use of regularity in data structures.
·
Visualization of the structure of invariance as shaped by
expectancy.
SI technology brings computer-based
knowledge aids closer to the human perceptual-linguistic experience. Successful human and social learning is
derived from a cyclic process of action followed by perception. This naturally involves an immersion in the
experience and in the native use of community language.
We believe that a new and productive
line of human information interaction (HII) scholarship will open with the
creation of SI systems. Within the
intelligence setting, for example, we expect to show how SI overcomes negative
behavioral characteristics commonly found in human analysis of business or
national intelligence.
Need
for OntologyStream Capitalization (3.4 Million over three years)
The need for investment is based on
our need to (1) protect the new market against those who are committed to a
status quo, (2) develop a patent protection infrastructure and community, (3)
provide the Knowledge Sharing Foundation and (4) provide a infrastructure to
compensate innovation implemented within the Knowledge Sharing Foundation.
Economic and Business Plan
Our business plan is quite
simple.
Drs Arthur Murray, Robert Shaw and
Paul Prueitt created OntologyStream in 2001.
100,000 shares of stock are authorized. We propose to extend this authorization to 1,000,000
shares. Of the 1,000,000 shares,
200,000 of these are conveyed to the BCNGroup as a means to establish a
long-term relationship between the BCNGroup and OntologyStream. 100,000 shares are conveyed to the
OntologyStream founder, Dr. Prueitt.
The remaining 700,000 shares are to be sold in stages over a three-year
period. Dr. Prueitt will hold the
voting proxy on the unsold shares and on the BCNGroup shares.
OntologyStream is committed to the following.
1. Obligate
itself to a legally binding agreement to not authorize any additional shares of
stock (beyond 1,000,000).
2.
Sell the first 100,000 shares of at $4 per share (under Rule 504
of the Blue skies laws) to a single sophisticated investor in order to
establish the legal and management staff needed to protect the business. This investment carries the highest
risk.
3.
Hire and manage a management team.
4.
Make available for 504 Rule purchase no more that 200,000 shares
of stock per year.
5.
Raise at least $3,000,000 over the next three years at a rate of
$1,000,000 per year with a stock price of at least $5 per share.
6.
Derive income from consulting in the knowledge technologies and
from contracts with the federal government.