COA: Change Oriented Architecture


The problem of this decade is the information technology platform. We have to switch to scale-free networks and abandon tabular lattice networks. It isn’t SOA that we need, it’s Change Oriented Architecture (COA).

I highly recommend rejecting Larry Ellison’s Oracle Relational Database and Sun’s MySQL and adopting Simon Williams’ Sentences Associational Database at which provides a schema and interface you can completely change on the fly.  No data loss, no null values, no normalization.  The lazy developer is the efficient developer.

When the Board of Directors says “Change!” the CIO can say “Immediately!”

And have you ever heard of “Hyperbolic Data”?  Sentences can do it easily and dynamically.  Click on the image to learn more:



The Brain: ZenUniverse 1.0


“Tao can Tao not Tao”

Lao Tzu

Since reading the work of Clare W. Graves of Spiral Dynamics fame, reflecting on the work of all the people mentioned in my Blogroll as well as my recent foray into Zen I attempted to review and revise my work on the assortment of frameworks I had come up with. As I was making revisions it dawned on me that nature had done all the work already.

“Outside this office, Business as Usual;

Inside this office, Thunder and Lightning.”

Colonel John Boyd

I decided to take another angle of attack.  I realized I was dealing with entities, hierarchies, attributes and relationships and one thing Boyd overlooked, results, in two dimensions not one.  You may remember this graphic:


I realized I would have to take the Boyd Pyramid a bit more seriously.  And I have.  I compared Boyd’s work to Einstein’s, saw the correlations and what I think is a flaw.


“The only real valuable thing is intuition.”

Albert Einstein


The first thing I want to address is a misconception regarding solids.  It was one Plato made as well as R. Buckminster Fuller.  There are not five stable solids.  There are six.

The mistake Plato and R. Buckminster Fuller made was to demonstrate the stability of a triangle composed of three rods to their students while saying that the simplest solid in three dimensional space is the tetrahedron.  He didn’t realize the triangle in his hand was the simplest solid.  The triangle is a two sided three vertex solid that is the simplest enclosure of space.  Our eyes use two of them to locate an object and calculate distance.

Considering the above solid and the Platonic Solids we have six three dimensional closed network structures as illustrated below:


Take note of the stability of each of the solids.  What this means is that the triangulated solids are able to support themselves structurally, while the non-triangulated solids collapse.

What I realized regarding the work of Einstein and other physicists is they did not regard the various phases of matter as important.  However the states of matter are important.  Each state from the triangle up to the icosahedron as illustrated above are higher states of order.  Yet, each state of order is fundamental to the universe in which we live.  And all are simply phases of what I call the “ZenEntity”.


I decided after looking at what I had found regarding the solids to reject contemporary empirical conventions and simply address one thing.  We have six fundamental ordered states.  After several billion years of evolution would not all organisms have what they require to function in response to all of the six states in their niche?

My next question was, “How do I represent the phenomena I had encountered as a network?”

In my profession there are data architects, database designers, data modelers, database administrators, data entrists, data analysts, database developers, database programmers database analysts, data warehouse architects, data warehouse analysts, data warehouse developers, Extract-Transform-Load architects, ETL analysts, ETL designers, ETL developers, ETL programmers, Business Intelligence architects, BI analysts, BI designers, BI developers and so on.  However, I was never satisfied with any of these position titles.  So, I coined one myself: data designer.  I was of the opinion no matter how much data was out there, it was finite.  Zero and Infinity were very useful, but they violated the laws of thermodynamics.  I saw seven distinct phases of order in the universe and only saw transitions from one state to another.  I could design according to those states.

This led me to explore how I could represent the six states.  I studied and applied a variety of project lifecycles such as System Development Lifecycle, Extreme Programming and Rapid Application Development, joint application development.  I had learned various enterprise frameworks such as Zachman and TOGAF, modeling techniques like UML, the various generations of programming languages, data structures, network topologies, organizational concepts, rule based systems, event based systems, data based systems, user centered design, goal directed design, location based services, pattern languages, service oriented architecture, hardware architectures and many more.  I studied English, Greek, Latin, Anglo-Saxon, German and French to see how I could develop a consistent taxonomy as well.

Ultimately I concluded that a majority of the people out there working on these problems had abandoned the basics for pet concepts.  They had no idea how many entities there were.  They had no idea how those entities should be related.  So I took it upon myself to identify all the relations that were applicable and came up with the following:


The associations are as follows:

  1. Pattribute: a triangle entity
  2. Battribute: a one to many relationship describing the association between a triangle and an tetrahedron
  3. Attribute: a one to one relationship describing the association between a triangle and a hexahedron
  4. Nattribute: a many to one relationship describing the association between a triangle and a octahedron
  5. Lattribute: a recursive many to one relationship describing the association between two icosahedrons and one icosahedron
  6. Mattribute: a recursive one to one relationship describing the association between two dodecahedrons

As you can see, the network is asymmetrical and allows for Node, Lattice, Tabular, Lattice, Linear; Lattice arrangements.  Note that since all of the entities are simply states of a single “ZenEntity” none of the states are independent from each other in the network.


Now, that we have established the solids and how they are interconnected we can look at what the actual phases of the ZenEntity are.  Each of these phases are recognized in physics, however I have not come across any discussion of the possibility that they are together a set of fundamental phases.


Usually, we see Space, Time, Energy and Mass described in Einsteinian classical physics.  We also have discussions of Ions, Gases, Liquids and Solids as states of matter.  But we don’t see them together.

  1. Energy: a three dimensional coordinate system
  2. Time: a connection between one three dimensional coordinate system and two four dimensional coordinate systems
  3. Ion: a connection between one three dimensional coordinate system and one six dimensional coordinate system
  4. Gas: a connection between two three dimensional coordinate systems and one eight dimensional coordinate system
  5. Liquid: a connection between two twelve dimensional coordinate system and one twelve dimensional coordinate system
  6. Solid: a connection between two twenty dimensional coordinate systems

Next, we will see how these states are all very important to our sensory systems.


As well as the phases there is another way to look at the six solids.  This is in the Latinate language of the six states.  The states differ from  the phases in that they deal with the essence or source of each of the states.


The essence of each of the states is as follows:

  1. Pattern: Father
  2. Battern:  Hold
  3. Attern: Give
  4. Nattern: Birth
  5. Lattern: Milk
  6. Mattern: Mother


Now, I am going to introduce you to some friends of mine.  I call them “Zen Sensors”


As you can see each ZenEntity State has a coresponding human sensory organ:

  1. Eye: detect events
  2. Ear: detect pressures
  3. Nose: detect plasmas
  4. Throat: detect molecules
  5. Jaw: detect organics
  6. Body: detect inorganics


Next, we have for your viewing pleasure the standard interrogatives and how they correlate:


I found this interesting, because I spent a great deal of time resisting the order of these interrogatives.  Finally, I just went along and found ultimately the order does make perfect sense.  It is an acquired taste.

  1. Eye: Who: Identification
  2. Ear: What: Objectification
  3. Nose: Where: Location
  4. Throat: When: Chronation
  5. Jaw: Why: Rationation
  6. Body: How: Function

If you read enough Anglo-Saxon it makes sense.


Having considered the Entities, Associations, States and Sensory Organs, let us now look at how this relates to a hemisphere of the brain:


The above illustration shows the left hemisphere of the brain and the major regions.  They are color coded to correspond to the fundamental states I have described.  You can also see the corresponding sensory organ as well as the corresponding network structure in the region:

  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.


Everything is great so far, but there is the fact that there are two hemispheres to the brain and they interact through the Corpus Callosum which I claim is where the self resides.  One of the interesting things about my study of Latin is that I discovered most questions actually required a two part answer.  This answer would be composed of an Archetype and a Type.  After reading Jill Bolte Taylor’s book, My Stroke of Insight and listening to her account of her perceptions while the left hemisphere of her brain was being shut down by an exploded blood vessel, it became apparent to me that the left hemisphere of the brain contained the Types the Latin language required and the right hemisphere of the brain contained the Archetypes.  It was necessary to create a two axis model to accomodate a brain with two hemispheres:


Each of the light colored cells in this table represent a connection between one coordinate system association (row) and another coordinate system association (column).  This accounts for the broad variety of properties we encounter making the states we experience.

There are actually not one or two, but four directions you can take on the above table.    Top to Bottom is right hemisphere deduction.  Bottom to Top is right hemisphere induction. Left to Right is left hemisphere deduction.  Right to Left is left hemisphere induction.

This is a physiological model of human perception that I have arrived at.  Our current definitions of dimensionality are incorrect.  Each state has its own dimensionality, its own associations, its own sense organs, its own region of the brain and the brain two hemispheres connected by the corpus callosum.  If the work of Dr. David Bryson on Physical, Decisional and Perceptual Learning is right, then deduction happens during waking and induction happens during sleeping.

This is not a complete model by any means as it does not deal with scale-free networks.  Or does it?

But to this point, that is the Zen Universe.


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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.