Investment Template

OntologyStream Inc Chantilly, Virginia

and

Behavioral Computational Neuroscience Group

Point of Contract: Dr. Paul Prueitt, CEO OntologyStream Inc

Executive Summary

The Behavioral Computational Neuroscience Group (BCNGroup) is a Not-For-Profit Organization based in Virginia. Our mission directives are;

· To create an international communications forum for the understanding, discovery and dissemination of knowledge for the common good.

· To create new technologies that synergistically applies computational systems to the automated investigation of artificial and natural systems.

· To provide protection for knowledge wealth created by primary scientific investigation.

· To hold in trust intellectual property for the common benefit of BCNGroup members and third party developers.

Under the auspices of the BCNGroup, the collective efforts of a diverse group of scientists, engineers and practitioners are promoting a National Project to ignite the Knowledge Technologies business sector. Our effort is expressed through sponsorship, directed initiatives, scientific conferences, educational presentations to government agency and commercial entities as well as featuring a tightly disciplined investment model to launch products derived from decades of research and development.

The BCNGroup supports public discussion leading to a nationally recognized accredited curriculum for scholarly investigation, education and training in the knowledge sciences.

We have created a template that is designed to reward investment and to allow investors to share in profits from emerging markets based on the knowledge technologies. The template is used in specific cases to bring a new product into existence and offer the product to a market.

InOrb Technologies is the first of these templates.

The problem (and the solution)

BCNGroup is formally seeking a single investor.

Phase 1: Based on the amount of work required to integrate the science and technology into a complete product package.

The following is a break down of the components required to build this system:

· Integrate Ontology Referential Base (Orb) and In-memory Referential Information Base (I-RIB) components.

· Design presentation software that demonstrates a method for using co-occurrence of terms in text as a high precision – recall mechanism

· Complete coding for and documentation of an InOrb Software Developer's Kit (SDK), that exposes the underlying functions and efficiency of processes.

The result of this effort is two fold. First, the SDK represents an “Unexpected Software Capability”. By putting together complimentary engineering techniques supported by proved science, InOrb invents something highly desirable and useful. The capability binds social science, linguistics, category theory, and computer science together in a simple and elegant manifestation of the knowledge technologies.

Second, the convergence of the technology will realize some portion of its real abstract value or net worth. The further capitalization of the company will build on this worth.

The remainder of this proposal will focus upon the following:

1. The technical details surrounding the product.

2. The Investor's Value Proposition.

3. The Investment Model Opportunity Characteristics.

4. The Investment Model Risk factors.

5. Structuring InOrb Technologies, Inc. and birth.

6. Buyer's Value Proposition.

7. General Community of Scientific discussion.

8. Investor Profile.

TECHNICAL REQUIREMENTS

The InOrb product is a horizontal technology enabling conceptual search, subject matter taxonomy development, and the structural analysis of data.

InOrb Tech contains two primary innovations that provide an unexpected capability that drives the value of this project and ultimately excellent return on the investment projections. These two features are:

· very high conceptual fidelity in subject indicator retrieval, and

· a fractal compression of ontology representation of co-variation of words in text

Fractal compression forms small, fast and platform independent bit maps. Fractal compression is established when new information is placed into the ontology encoding at much less cost than old information, due to the similarity that the new information has to old information when the structure of natural linguistic variation is properly recorded.

Product design and testing is based on social and cognitive science. Application of the product in a highly visible environment lets the product speak for itself in terms of both efficient execution and knowledge discovery output.

Extraction and manipulation of concepts, and structural ontology, becomes an expected new capability appearing in all types of applications.

Orb technology is consistent with the spirit of the OASIS Topic Maps standard 1.0. Orb technology supersedes the current generation of machine ontology standards such as OWL (Ontology Reference Language), RDF (Resource Description Framework), and KIF (Knowledge Interchange Framework); as well as proprietary ontology systems such as developed by Cycorp Inc. and Knowledge Foundations Inc. Orbs are many orders of magnitude simpler to encode.

THE INVESTOR'S VALUE PROPOSITION

InOrb Technology LLP is a valuable Intellectual Property asset. As is typical of most short-term investments containing elements of risk, a better than average return is expected.

We have created a type of template that meets the needs of inventors of computer innovations while making the investment attractive and safe.

THE INVESTMENT MODEL OPPORTUNITY CHARACTERISTICS

1. An excellent return on a short-term investment.

2. The Investor is not required to perform any oversight over the duration of the development period.

3. The Investor will be authorized after 60 days to manage, control and preside over the sale of the asset.

4. The Investor will be the most informed participant in the event said investor wishes to purchase the company.

5. The design of the investment model reduces the importance of promotional communications during the period that the product is being developed and tested.

6. The development life cycle and architecture and design characteristics are already completed for the development process to commence.

THE INVESTMENT MODEL RISK FACTORS

1. The Investment Template has never been tested. The Template depends on factors larger in scope that this single company.

2. Software development project crept and out of scope factors.

3. A critical factor will be the future cost of internal software licenses. The negotiated agreements will require mutual agreement by the Investor and OntologyStream Inc. Ontologystream is a third party, whose interests have to be accounted for.

KEY DIFFERENTIATORS

InOrb applications will outperform on clear measures of conceptual recall, especially in small collections that are difficult for most other tools. The technology is language independent. The InOrb technology is also data source independent so one can apply the core technology to the analysis of invariance in streams of scientific data.

There are precision/recall measures that are commonly recognized and used by TREC and in Trilogy evolutions, but OntologyStream has criticisms of these measures and will offer others that are fair and well reasoned. The measure that matters most, however, is the judgment of analysts who compare the leading systems. The web site will support this measure.

(a) Faster processing in all phases, without recourse to special hardware.

(b) Simple purchase and installation.

(c) Potentially very inexpensive.

(d) A scientific foundation (and potentially continuing program).

STRUCTURING INORB TECHNOLOGIES, INC. AND BIRTH

1. OntologyStream Inc has reserved the name InOrb Technologies Inc and InOrb LLP.

2. OntologyStream Inc has also filed a provisional patent on a method for using co-occurrence of terms in text as a high precision – recall mechanism.

3. InOrb Technologies is organized as a limited liability partnership.

4. The Investor will be a Managing Partner. OntologyStream Inc contributes technology and labor.

5. OntologyStream Inc has secured the InOrb Corporate identity, Domain Name, Web Site, Trademark and associated logos for the birth.

6. The LLP STATEMENT OF WORK has 3 tasks:

1. Negotiate licensing agreements with innovators.

2. Develop the SDK, refine it's public interface or developer APIs and document features.

3. Quality Assurance through standard functional, unit and system testing.

4. Sell the company and compensate the stakeholders.

BUYER'S VALUE PROPOSITION

The buyer will have a fully refined and tested product, a backlog of sales leads, unencumbered ownership, and a highly skilled and willing staff to support future requirements or customer deployments. The product is easily packaged in several ways, including integration within other environments or standalone sites to which subscriptions could be sold.

The most important proposition attribute is an immediate ability to get to market and achieve the shortest “Time To Revenue” after purchasing the InOrb assets.

Many SBIRs may be written to use the InOrb technology in specific application areas, including bio-informatics, text understanding, the analysis of scientific data, and homeland security applications.

The buyer will be wary of potential conflicts regarding underlying licenses and patents and the long-term programs of the participating technology companies. InOrb Technologies feels that these concerns will be easily laid to rest in the terms of the sale.

The sales price not only reflects the cost of the development, but the incremental margin realized by the sale to the highest bidder represents the value added and codified research of over ten years of collaborative research that can justifiably be depreciated.

The buyer of InOrb Technologies Inc will decide how to proceed in a profitable manner, according to his or her own vision with foundational business and marketing plans to drive income opportunities.

INVESTOR PROFILE

BCNGroup Investor Profile would be a person who is patrons of the Arts & Sciences with a strong ethical commitment for personal achievement and a socially conscientious frame of mind. Investors should be well enough healed with a diversified portfolio that can statistically take on some risk with the proposed investment model.

Investors should have some magnitude of entrepreneurial spirit and not be afraid of advanced business analytics, strategic goals and objectives within the context of rapid technological change.

CONCLUSIONS

The admirable efforts of the scientific community working within the Knowledge Sciences is reflected by the BCNGroup organization. The Investment Model encompassing the development process to move research from the laboratory into production and commercialization is at best a bumpy road. However, the effort is worth the exoteric empowerment it will give people throughout the world as opposed to esoteric groups and perhaps play a role in the survival of our own species. The Investor will be recognized as a key contributor and should have a profound sense of philanthropy in support of the ideals of the BCNGroup and the National Project..

Supplement statement

GENERAL COMMUNITY OF SCIENTIFIC DISCUSSION

Players in market segment

One significant future market for the InOrb technology is the new company dataRenewal LLP. dataRenewal LLP is patterned after this Investment Model and designed to develop a public infrastructure that allows citizens and interest groups to produce information about all State and Federal public document repositories. The dataRenewal Inc business plan is to deploy the InOrb technology as a means to enhance citizen centric government by providing a publicly accessible Orb indexing of all Federal public document repositories. The investment model used by InOrb LLP is also used by dataRenewal Inc, except the term of the investment is nine months.

Promotional communications

The design of the investment model reduces the importance of promotional communications during the period that the product is being developed and tested. Application of the product in a highly visible environment allows the product to speak for itself. Product design and testing is based on social and cognitive science.

Business & technology trends & tipping points

There is very widespread interest in semantic technology. Our expectation is that semantic technology will become visible early in 2004, and that government policy makers will pressure agencies to adopt it. Early semantic technology vendors have found sales to be very slow. At a recent vendor-dominated meeting on the 'semantic web', the vendors all found this situation somewhat mysterious. It may be that the semantic function is too unfamiliar, and IT staff won't take the risk if they are unsure whether users will adopt it. However, because of the nature and technology sector down turn over the 30 months, we feel the next economic upturn and capital expenditures for 2004 will be with Knowledge Technologies.

The federal market will standardize on a single product. A consensus on the standard will not form until the Department of Homeland Security begins to mature. This may take most of 2004.

Given public access to highly visible trial environments being developed by dataRenewal Inc, it may be that agency IT staff will put Orb technology in place. If agencies, like the FCC and FTC, see that user needs are solved by external web based services they may simply ratify this solution. When institutions get around to purchasing semantic search functions, which most will in the next year or two, they will adopt the simplest and least expensive solution. There will be pressure, from those who have tried it, to make the right choice.

Why InOrb Technologies, and why now?

Users will give up old habits if they have had an opportunity to EXPERIENCE the benefits of a new and more useful tool. IT staff will eventually give in to popular will and performance needs.

True, many people are content with conventional searches. But they were also content with paper libraries before that, and either did or did not use available search helps, and we all survived. Today, however, there are many situations where there is an expectation that one's "due diligence" must in fact be an objective due diligence, not some haphazard effort.

Lives are at stake in the intelligence field, where vast stores of relevant text are now merely sampled. The categorical abstraction and subject indicator representation will provide transparency to social communications. Privacy is addressed from the ground up, and oversight will have to be refined to protect individual privacy while also knowing where asymmetric threats are developing.

GLOSSARY

ANSI X12 - A protocol from the American National Standards Institute (ANSI) for electronic data interchange (EDI). EDIFACT merged with ANSI X12 in 1997. See EDI, EDIFACT, and http://www.x12.org/

DAML (DARPA Agent Markup Language) - A language, built on XML and RDF, for the expression of ontologies. The latest version incorporates OIL and is called DAML+OIL. DAML+OIL together are the basis of OWL, and are expected to be superseded by OWL when it is is formally accepted. See DARPA, XML, RDF, OIL, OWL, and http://www.daml.org.

DARPA (Defense Advanced Research Projects Agency) -See DAML and http://www.darpa.mil.

Data Dictionary -A collection of descriptions of the entities in a data model or schema. Data Dictionaries are usually written in natural language, as opposed to rationalizations.

DCMI (Dublin Core Metadata Initiative) - An open forum engaged in the development of interoperable online metadata standards. See Metadata and http://dublincore.org.

DTD (Document Type Definition) - A specific language for describing the structure of a class of structured documents, such as SGML of XML documents – now superseded by XML Schema. See SGML, and XML

Dublin Core – see DCMI

EAI (Enterprise Application Integration) - The term used for information systems that bind together many applications within an enterprise, typically dealing with the scheduling and control of flow of information between them. Often classified as middleware.

EDI (Electronic Data Interchange) - The electronic interchange of business transactions between organizations according to a specific pre-defined standard. Generally uses a flat file structure. See ANSI X12, and EDIFACT.

EDIFACT (Electronic Data Interchange for Administration Commerce and Transport) - A standard for EDI. See EDI, ANSI X12, http://www.edifact-wg.org and http://www.xml-edifact.org/.

ERD (Entity Relationship Diagram) – A data modeling technique used primarily in database design. It models entities, their relationships, and the cardinalities of those relationships.

Knowledge Representation – The study of the representation of knowledge in machine understandable form. See Ontology and http://www.jfsowa.com/.

Mapping – The process of associating elements of one set with elements of another set, or the set of associations that come out of such a process. Often refers to the formally described relationship between two schemas, or between a schema and a central model. See Rationalization.

Messaging - Creating, storing, exchanging, and managing data messages across a communications network. The two main messaging architectures are publish-subscribe and point-to-point.

Metadata - Data that describes other data. Often deals with the format or authorship of the underlying data. See Dublin Core and http://www.w3.org/Metadata/Activity.html.

MOF (Meta Object Facility) – A facility for the definition of modeling systems, to facilitate interoperability between them. See OMG, XMI, and http://www.omg.org/cwm/

Namespace - A way of qualifying element and attribute names used in XML documents. See XML, XML Schema, URI, and http://www.xmlinfo.com/namespaces/.

ODBMS (Object-Oriented Database Management System) - A DB Management System that supports data modeling and the creation of data in the form of objects.

OIL (Ontology Inference Language or the Ontology Interchange Layer) - A declarative ontology language built on RDF. Often used in conjunction with DAML, and called DAML+OIL. See DAML, DARPA, and http://www.ontoknowledge.org/oil/.

Ontology – Originally a term for the branch of philosophy concerned with defining what exists, this has been appropriated by the technical world to mean a conceptual representation of the entities, meanings, and relationships within a specific domain of knowledge. See RDF, W3C, Metadata, OIL, Semantic Web, DAML, and OWL.

OMG (Object Management Group) – A consortium producing and maintaining important industry specifications, including CORBA, MOF, UML, and XMI. See MOF, UML, XMI, and http://www.omg.org

ORDBMS (Object-Relational Database Management System) - The result of object-oriented database concepts being superimposed on relational databases. See RDBMS and ODBMS.

OWL (Ontology Web Language) – The ontology language, built on RDF and RDFS and inspired by DAML+OIL, that is being developed by the W3C Web Ontology working group, and is currently in "Last Call" status. See W3C, DAML, OIL, Ontology, and http://www.w3c.org/2001/sw/WebOnt/

Rationalization – The process of associating the entities of a data model or schema with an agreed upon ontology or language. Also refers to the results of such a process. See mapping.

RDBMS (Relational Database Management System) - A program that lets you create, update, and administer a relational database, usually by utilizing SQL statements and storing data in related tables.

RDF (Resource Description Framework) - RDF is an assertional language intended to be used to express propositions using precise formal vocabularies, and as a basic foundation for more advanced assertional languages. From the perspective of RDF, nearly everything is considered a resource, so the language purports to have the ability to describe anything. RDF is an application of XML being developed by the World Wide Web consortium. It is the language underlying OWL, the W3C's ontology web language. Reference RDFS, OWL, and http://www.w3.org/RDF

RDFS (RDF Schema) - RDF provides a way to express simple statements about resources, using named properties and values. However, RDF users also need the ability to indicate that they are describing specific kinds or classes of resources, and will use specific properties in describing those resources. RDF Schema is intended to provide the mechanisms needed to specify classes and properties as part of a vocabulary, and to indicate which classes and properties are expected to be used together. In other words, RDF Schema provides a type system for RDF.

RosettaNet - An organization set up by industry-leading technology companies to define a common set of standards for e-commerce communication in the high technology supply chain. See http://www.rosettanet.org.

Schema – The structure of a database, a collection of structured documents, or other data storage or transfer mechanism. A schema can expressed in a diagram form, such as UML or ERD, or in a text based form, such as XSD.

Semantics - The meaning of something, as opposed to the way it is expressed, which is its syntax. See Syntax and Semantic Web.

Semantic Web - A conceptual web built on top of the World Wide Web in which all identified resources will be machine-processable. See RDF, W3C, Metadata, OIL, Ontology, DAML, http://www.semanticweb.org/, and [Tim Berners-Lee’s Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web.

SGML (Standard Generalized Markup Language) - A standard constructed by the International Organization for Standardization (ISO) for defining a text document’s format. It is a superset of the XML standard. See HTML and http://www.w3.org/MarkUp/SGML/.

Syntax - The structure or form of something, as opposed to it’s meaning, which is its semantics. See Semantics.

Taxonomy – The science or technique of classification. The following terms; classification schemes, taxonomies and categorization schemes are often used interchangeably.

Transformation - The conversion of structured data from one format to another. See XSLT.

UDDI (Universal Description, Discovery, and Integration) - A standard for the registry of web services. See Web Services and http://www.uddi.org.

UML (Unified Modeling Language) – a standard diagrammatic language, defined by the OMG, for recording models. See XMI, OMG, MOF, and http://www.omg.org/technology/uml/index.htm.

URI (Uniform Resource Identifier) - Short strings that identify resources. See http://www.w3.org/Addressing/.

URL (Uniform Resource Locator) – Strings that identify the precise location of a file on the Internet. See http://www.w3.org/Addressing/.

URN (Uniform Resource Name) - A persistent identifier for an information resource. See http://www.ietf.org/html.charters/urn-charter.html.

W3C (The World Wide Web Consortium) - The international consortium spearheading open standardization, interoperability, and coordination efforts regarding the Internet and the Web. See http://www.w3.org.

Web Services – Functions or services available remotely over the Internet. Generally, they use SOAP as a transport mechanism, are defined in WSDL, and may be registered with UDDI. See SOAP, WSDL, and UDDI

WSDL (Web Services Description Language) – A language for the description of web services, see Web Services

XMI (XML Metadata Interchange) – An XML standard for the exchange of metadata. It was developed by the OMG for the serialization and exchange of UML and MOF. See OMG, UML, MOF, and http://www.omg.org/technology/xml/index.htm

XML (Extensible Markup Language) - A standard for formatting data. Standardized by the W3C, XML defines a Web site’s data elements by using a tree structure. See http://www.w3.org/XML/.

XML Schema - A specification for defining the content type of an XML document or file. See XML, XSLT, DTD, and http://www.w3.org/XML/Schema.

XSL (Extensible Stylesheet Language) - A language for expressing stylesheets. An XSL stylesheet describes how an XML document of a particular type should be displayed. Although XSL formally includes XSLT, XSL is used for primarily for describing how XML documents are to be presented, where XSLT has become the standard language for transforming XML documents. See XML, XSLT, and http://www.w3.org/Style/XSL/.

XSLT (XML Stylesheet Language: Transformations) – Formally a part of XSL, and originally created for complex formatting tasks, XSLT has become the standard language for transforming XML documents. See XML, XSL, and http://www.w3.org/TR/xslt.