The Brain: ZenUniverse: Seven Senses


  1. GREEN: EYE: OCCIPITAL LOBE: visual center of the brain
  2. YELLOW: EAR: TEMPORAL LOBE: sensory center of hearing in the brain.
  3. SKY: NOSE: BRAINSTEM: control of reflexes and such essential internal mechanisms as respiration and heartbeat.
  4. BLUE: TONGUE: PARIETAL LOBE: Complex sensory information from the body is processed in the parietal lobe, which also controls the ability to understand language.
  5. RED:  JAW: FRONTAL LOBE: control of skilled motor activity, including speech, mood and the ability to think.
  6. ORANGE: BODY:  CEREBELLUM: regulation and coordination of complex voluntary muscular movement as well as the maintenance of posture and balance.
  7. GREY: SELF: CORPUS CALLOSUM: The arched bridge of nervous tissue that connects the two cerebral hemispheres, allowing communication between the right and left sides of the brain.


If you look at my first ZenUniverse post, you will see a six column model.  However, the System International Units require seven columns.

Here is a table of two hemisphere intersections.  I am using Latin roots, but you will recognize many of the terms:


Here is a blank table you can print out and experiment with correlations and intersections of your own:





The Zen of Systems and Networks


My own work with Enterprise Frameworks and Networks has led me to come up with the following table.  It describes the Nodes and Links in a Complete System Network.  I am saying that the Nodes representing Goals, People, Time, Locations, Code, Data, Qualities and Quantities can all be represented as Scale-free Networks and that each of these Node Networks require only one datatype.  I am also saying that there are only three types of links in networks: recursive links within a set, multiple links between sets, single links between sets.  I know of no case where this has been attempted in the manner I am attempting to represent it.


If you have been following my blog you are aware that I have been struggling for a long time to come up with a framework and a clean terminological set to describe systems.  I think I have come one step closer to that goal today.  The table above describes a Fact composed of eight Nodes (first white row illustrating entities) and the Links (last three white rows illustrating recursive, multiple and singular relationships) for each of the System Networks (Interrogative columns).  One of the interesting aspects of this System Network Model is every Fact is composed of a Unique Set of all eight Nodes.  However, all the Nodes in one Fact do not have to have Links to all the Nodes in another Fact.  Each Node within a Fact is independent regarding its Links.  Therefore you have a single set of System Facts with each Fact containing a single set of Interrogative Nodes each connected by their respective Link Networks.

I have recently been writing with the intent to challenge centrism on any one of these networks and advocate a more integrated view. I still remember dealing with data centrism, event centrism, user centrism, goal centrism, program centrism and schedule centrism over the course of my career. All of them have a role to play. My insight into all of these Nouns being Linked by Verbs in only three ways required me to look at all of the Enterprise Architectures and disengtangle the Nouns, Links and Verbs from the reasoning and representations that extend back beyond computing itself.

The Data Model below is a hybrid of Relational Models and Dimensional Models.  I call this an Associational Model.  It is using Relational Architecture to represent it.  However, I think that an alternate Entity-Attribute-Value (EAV) architecture called the Associative Model of Data would be better suited to the task.  I am using relational representation as I am still trying to communicate with a community only familiar with Relational technology.

The first thing to note about this model is Links are represented by Associations.  Associations link two Nouns using a Verb.  What is interesting about this model is every Verb, Association, Noun and Fact is unique.  The vertical connections are Many to Many relationships which allow two vertically adjacent Verbs, Associations or Nouns to have multiple unique relationships between each other.  What this means is there are no integrity problems (duplicate values) as the system network would enforce uniqueness.


The premise of this model is that the Nodes are not dimensions at all.  I am rejecting the traditional concept of dimensionality instead I am saying that there are three dimensions of Links: recursive, multiple and singular.  All we perceive are Facts, Nodes and the Links between them.

So you could come away with the following Zen koan:

entity without entity,

source without source,

path without path,

target without target,

size without size,

dimension without dimension.

Databases: Structured Associative Model


For years now I have been struggling with Relational DBMS technology and Associative DBMS technology attempting to get them to do what I want.  In my first efforts, Relational models were structurally restrictive, Dimensional models were unable to grow organically, EAV models are incompatible with relational architecture.  I came upon Simon Williams Associative Model of Data and although enthralled with its potential I found it too had limitations.  It was semi-structured and allowed for too much flexibility.  25 years in Information Technology had taught me that there was a single standard classification system for setting up databases not a plethora of ontologies.  I was determined to find the theoretical structure and was not concerned with hardware limitations, database architecture, abilties of current query languages or any other constraints.

The Associative Model of Data had made the difference in liberating me from Relational and Dimensional thinking.  A traditional ERD of the Associative Model of Data I at first thought would look like the following:


Basically what you have is a Schema composed of Nodes with Node Associations through Verbs and Associations with Nodes Attributions through Verbs. The range of Node Entities, Verb Entities, Association Entities and Attribution Entities are endless.  As well the population of the Schema has an unlimited dataset of natural key values.  I have been challenged by Relational database specialists and SQL experts regarding the viability of this model within current limitations, however their arguments are irrelevant.  What is important is the logical validity of the model, not the physical validity.

After receiving the criticism I decided to revisit the model in order to simplify it.  I went over Simon William’s explanations of his model and its application and found I could reduce it to the following:


This was profoundly simpler and better reflected the Associative Model of Data’s Architecture.  But even with this simpler architecture I was not satisfied.  I felt that the Associatve Model although giving the benefit of explicitly defining the associations was a tabula rasa.  Research has shown that tabula rasa’s are contrary to the behavior of the finite physical universe.  There is an intermediate level of nature and nuture.  And this is what I sought to model.


When I first encountered the Zachman Framework, something about it struck me in a very profound way.  I could see there was something fundamental in its description of systems, however I felt that the metaphors that John Zachman used were wrong because they themselves lacked a fundamental simplicity.  The consequences of this were that those who studied under Zachman ultimately could not agree on what he was talking about.  Also the “disciplines” that Zachman’s Framework generated were continually reinventing the wheel.  Zachman had created a world of vertical and horizontal stovepipes.  To further the confusion Zachman refused to conceive of a methodology based upon his framework.  Consequently, there was no way to determine what the priorities were in creating a system.  I call this the Zachman Clusterfuck.

Zachman’s work spawned years of work for me.  I could see that systems had a fundamental structure, but I could not agree with Zachman.  Focuses and Perspectives were useless terms.  The construction metaphor was useless.  I read anything I could get my hands on dealing with systems, methodologies, modeling, networks and a broad range of other literature across the disciplines.  Out of this came a set of conclusions:

  1. There were a fundamental set of Noun Entities
  2. There were a fundamental set of Verb Entities
  3. There were a fundamental set of Association Entities
  4. There was a clear order in which the Nouns were addressed
  5. There was a clear order in which the Verbs were executed
  6. The structure was fractal
  7. The content was a scale-free network

I made some attempts at creating the vocabulary and experimented with this new Structured Thinking Language.  However, the real break came when I worked with John Boyd’s OODA Loop:


The OODA Loop revealed a governing structure for the methodology and guided my way into the following hybrid relational/dimensional/associational model I call the Structured Associative Model of Data:


One of the key things this model demonstrates is the sequence followed by the OODA Loop.  Starting from the top, each dimension set spawns the next.  Choices are created from the dimensions.  There is no centrism to this model which is an inherent flaw in Service Oriented Architecture (SOA), Event based architecture, Data centric architecture, Goal-Directed Design, Rule based systems among others.  The stove pipes of Focuses and Pespectives disappear by reasserting a clear order of priorities and dependencies for achieving success.  The model also supports bottom up inductive as well as top down deductive sequencing.  This will make the system able to reconfigure to handle exceptions.

Some of the things I have learned in designing this model include the realization that unit defines datatype and that all measures are variable character string text.  This is because any displayed value is only a symbolic representation of the actual quantity.  If operations are to be performed on measures they are converted to the correct type as part of the operation.  I also recognized that Unit was necessary to define the scale and scalability of the system.  Further, it became apparent that analog calculations should not be practiced.  Every value should be treated as discrete and aggregated.

Another aspect of this system is the inclusion of currency and amount.  I have been critical of Zachman and academics for their hypocrisy regarding the economics of systems.  All systems have a cost and a benefit and they are measurable in currency.  Contrary to the reasoning of the majority, every decision is ultimately economic.

Tim Brown of IDEO has coined the term “Design Thinking” and has been toying with the concept for some time.  Many designers dwell on the two dimensional concept of divergence and convergence as modes of thought.  If we look at my model, divergence is the creation of choice while convergence is selection of choice.  There is no alteration or deletion of choice in my model as history is preserved.

Now what you have is a unencumbered framework with a clear methodological sequence.


Welcome to the Cognitary Universe.

Cognitary Stratus


trivergent, divergent, univergent, convergent.

“History does not repeat itself, but sometimes it rhymes.” –Mark Twain

Cognitary, Inc.


to Found

foresought and fidel,

forethought and factual,

familiar and friendly,

fair and full

to Fiat

seer and leader,

feeler and finder,

giver and taker,

seller and buyer


to Future

principle and power,

understanding and knowing,

safety and health,

prosperity and wealth

to Flow

vessel and berth,

heaven and earth,

table and hearth,

market and dearth


to Function

designing and engineering,

plotting and navigating,

crafting and smithing,

profiting and possessing

to Form

goal and person,

event and location,

service and product,

price and metric


to Fashion

control and command,

climate and terrain,

training and discipline,

currency and commodity

to Foot

sanctity and dignity,

certainty and verity,

testity and pacity,

quality and quantity

The above outline is the evolving strategic framework of my company Cognitary, Inc.  I am working to build a community of generalists to tackle client problems across the disciplines.


Universe: Interrogative Spaces


In my previous post I gave thought to Tim Brown of IDEO’s “design thinking”, Clayton Christensen’s “Innovator’s Dilemma”, Malcolm Gladwell’s “Tipping Point”, and Buckminster Fuller’s “Synergetics” concepts.  What emerged was the above Czerepak Framework.  My claim is this framework is fundamental to designing a system.

The thing that the above table shows is interaction within what I am now going to call the “Interrogative Spaces”: HowSpace, WhatSpace, WhySpace, WhoSpace, WhenSpace, WhereSpace, HowMuchSpace, HowManySpace.  Each ellipse I call a “vortice”.  The Interrogative Spaces are composed of one or more vortices.  The Framework above shows how Spaces are composed within the Interrogatives,  but what about interactions between the Interrogative Spaces?   A good example is speed or velocity.  Speed is the intersection of WhenSpace and WhereSpace:

v = r / t

Where v is velocity, r is radius and t is time.

If you are increasing Speed, which is acceleration, you have one dimension of WhereSpace and two dimensions of WhenSpace:

a = r / t’ * t”

Where a is acceleration, r is radius, t’ is the first clock and t” is the second clock.  You cannot measure acceleration with one clock. This uniqueness of every vortice applies to all the Interrogative Spaces and all inter-relationships between all of the Spaces.  .

Another way to look at the Interrogative Spaces is as sets and subsets.  The first row are the complete Space vortice sets.  The second row are the first Space vortice subsets.  The third row is the intersect between the row two and row three Space vortice subsets. And the fourth row are the intersects between the row two and row three and row four Space vortice subsets.

I do not believe that anything is constant.  Not the speed of light, not gravity, not cosmology.  Every intersection of dimensions creates a vortex in Universe and every one is unique.  We are simply unable to measure and manage the uniqueness of everything, therefore we make generalizations which create models that can always be falsified.

Universe: The Czerepak Framework

I just visited the archive of Tim Brown’s Design Thinking Blog and came across the following post:

Definitions of design thinking

Tim Brown » 07 September 2008 » In design thinking »

In my HBR article I gave a ‘definition’ of design thinking. It was:

Design thinking can be described as a discipline that uses the designer’s sensibility and methods to match people’s needs with what is technologically feasible and what a viable business strategy can convert into customer value and market opportunity.

On reflection this is a narrow description that focuses on design thinking’s role within business. The next sentence that I wrote.“….design thinking converts need into demand” , which I borrowed from Peter Drucker, broadens things out a bit but still assumes an economic motivation.

I am grappling with two questions as I think about this.

1. Is there a general definition of design thinking?

2. Is it useful to have one?

I think Tim has something very good here and suggest that the following would be a further breakdown of his classification:

  • Viable: Business
    • How Much: Quality
    • How Many: Quanitity
  • Feasible: Technology
    • What: Material
    • How: Process
  • Desirable: Human
    • Why: Goal
    • Who: People

Obviously, if you have been following my blog, you can see the same pattern appearing and reappearing as we explore other’s concepts.  The six interrogatives continue to reassert themselves.  However, I think I finally nailed one more aspect on the head.  I hate to say it, but it came to me in a dream about working on a programming project:

  • Reliable:
    • Where: Location
    • When: Timing

Quantity and Quality are two aspects of design/system thinking that are continually overlooked by academics and specialists, but not business people.

Interestingly enough this perspective is not new.  Clayton M. Christensen in his book The Innovator’s Dilemma discusses a four part model that fits nicely with this:

  1. Availability
  2. Compatibility
  3. Reliability
  4. Cost

I consider, Clayton’s the most empirical ordering.  Consequently, I would like to mesh Tim’s, Clayton’s and my perspective into the following:

  1. Feasibility: Technology
    1. How
    2. What
  2. Compatibility: Personality
    1. Why
    2. Who
  3. Availability: Market
    1. Where
    2. When
  4. Viability:  Business
    1. How Much
    2. How Many

Now, looking at this I am reminded of Malcolm Gladwell’s book, Tipping Point, and it adds the following character to the model:

  1. Feasability: Mavin
    1. How: Processes
    2. What: Materials
  2. Compatibility: Connector
    1. Why: Goals
    2. Who: People
  3. Availability: Salesman
    1. Where: Locations
    2. When: Schedules
  4. Viability: Customer
    1. How Much: Costs
    2. How Many: Units

Universe: A Multi-Dimensional Medium

Let’s do a thought experiment.  I want to take design thinking and abstract it to a system.


Imagine that there are no solids, liquids, gases or plasmas or particles.  That the Universe is a fluid medium swirling between equilibrium and non-equilibrium in multiple dimensions.  What we perceive to be solid, liquid, gas or plasma are not states, but intersections of dimensions that describe interdimensional vortices.  Energy is the intensity of a vortice.  Mass is a vortice of a set of dimensions.  Light is a vortice of a set of dimensions.  All of the particles are vortices of sets of dimensions.  Each influence the other based upon which dimensions they are composed of.

R. Buckminster Fuller clearly states in his work that we should perceive the systems as finite four dimensional spheres.

There are only four fundamental states:  vortice verge, vortice converge, vortice emerge, vortice diverge.


Everything we perceive are combinations of these vortice states.  The states are +/- vortice yaw, +/- vortice pitch, +/- vortice roll.

If any vortice is spiraling toward you it is positive, if any vortice is spiraling away from you it is negative.  By definition, no vortice can be stationary with respect to you.

There are only eight fundamental vortices: How, What, Why, Who, When, Where, How Much, How Many.

This gives us the following eight vortice, four state table:


Take the time to look at the terms defining each of the white cells in the table.  Each row is the addition of a dimensional vortice.  For example: Each additional “when” vortice is another separate clock.  Each additional “where” vortice is another separate radius.  All of them are factors in a system or a design.

And even this representation is inaccurate.  If we consider fractal geometry and chaos theory, there are no points, no straight lines, no arcs, no planes, no circles, no polygons, no polyhedrons, no spheres, only vortices that are above, within or below our range of perception.  Space cannot be filled with any geometric shape.  Everything is composed of vortices–spirals.

We have to abandon the flat world, flat space models we currently cling to.  The world and the universe are not infinite planes.  The world is a finite island of non-equilibrium in a predominantly equilibrium universe.

And that is it, the Czerepak (Chair-eh-pak) Framework.

Copyright (c) 2008 Grant Czerepak.  All rights reserved.


Systema: Operation, Tactic, Strategy