logo jabes

Shape fractal: 6x6 Reference frames


📚 Reference Frames 6d Info logic types info tech flows 📚
👐 C-Steer C-Serve C-Shape 👁 I-C6isr I-Jabes I-Know👐
👐 r-steer r-serve r-shape 👁 r-c6isr r-jabes r-know👐
🔰 Contents Frame-ref ZarfTopo ZarfRegu SmartSystem ReLearn 🔰
  
🚧  MDM2int SHouse VPossess Fame-int Honour-int Learn-I 🚧
  
🎯 MDM2ext SLife VWealth Fame-ext Honour-ext Learn-@2 🎯

AK-1 Basics getting adaptive using the 6*6 reference framework


A-1.1 Contents

⚙ AK-1.1.1 Looking forward - paths by seeing directions
A reference frame in mediation innovation
details systems life shift logframe back design sdlc design data infotypes logframe technology logframe When the image link fails, 🔰 click here.
There is a revert to main topic in a shifting frame.
Contexts:
◎ C-Shape mediation communication
↖ C-Serve technology, models
↗ I-C6isr organisational control
↙ infotypes
↘ techflows
Fractal focus in mediation innovation
The cosmos is full of systems and we are not good in understanding what is going on. In a ever more complex and fast changing world we are searching for more certainties and predictabilities were we would better off in understanding the choices in uncertainties and unpredictability's.
Combining:
  1. Systems Thinking, decisions, ViSM (Viable Systems Model) good regulator
  2. Lean as the instantiation of identification systems
  3. The Zachman 6*6 reference frame principles
  1. Value Stream (VaSM) Pull-Push cycle
  2. Improvement cycles : PDCA DMAIC SIAR OODA
  3. Risks and uncertainties for decisions in the now near and far future, VUCA BANI
The additional challenge with all complexities is that this is full of dualities - dichotomies.
⚙ AK-1.1.2 Local content
Reference Squad Abbrevation
AK-1 Basics getting adaptive using the 6*6 reference framework
AK-1.1 Contents contents Contents
AK-1.1.1 Looking forward - paths by seeing directions
AK-1.1.2 Local content
AK-1.1.3 Guide reading this page
AK-1.1.4 Progress
AK-1.2 Knowledge shoulders for the 6x6 RFW base6x6_02 Frame-ref
AK-1.2.1 Starting in understanding by asking the right questions
AK-1.2.2 Using a reference frame for questions and replies
AK-1.2.3 The human value drivers: safety, wealth, fame, honor
AK-1.2.4 System drivers: Antipodes, dualities and dichotomies
AK-1.3 Augmented axioms: Anatomy Physiology ZARF base6x6_03 ZarfTopo
AK-1.3.1 Understanding & changing the reference frame
AK-1.3.2 Duality dichotomy Anatomy - physiology: 1* dimensions
AK-1.3.3 ZARF: Anatomy axioma's rationale & implications
AK-1.3.4 ZARF: Physiology axioma's rationale & implications
AK-1.4 Augmented axioms: Neurology Sociology ZARF base6x6_04 ZarfRegu
AK-1.4.1 DIKW Closed loops - good regulators
AK-1.4.2 Duality dichotomy Neurology - Sociology: 1* dimensions
AK-1.4.3 ZARF: Neurology axioma's rationale & implications
AK-1.4.4 ZARF: Sociology axioma's rationale & implications
AK-1.5 Insight for intelligence in viable systems base6x6_05 SmartSystem
AK-1.5.1 Dualities, dichotomies in the flow context
AK-1.5.2 Vision, Wisdom, knowledge Intelligence - good regulator
AK-1.5.3 Intelligence Duality, dichotomy: context-abstraction
AK-1.5.4 Confusing cycles by contexts, abstractions to clear
AK-1.6 Learning systems maturity from 6x6 RFW's base6x6_06 ReLearn
AK-1.6.1 Evaluating the pattern of four layers, the 3D model
AK-1.6.2 Systemic distractors in systems causing failures
AK-1.6.3 Vision Wisdom Knowledge into knowledge management
AK-1.6.4 Smart systems, out of the information systems crisis
AK-2 Details systems ZARF tactical 6x6 reference framework
AK-2.1 Enabling the internal understanding continuum syst6x6_01 MDM2int
AK-2.1.1 Information semantics for contexts and abstractions
AK-2.1.2 Example: Stakeholders - roles and tasks (People)
AK-2.1.3 Example: SER, DevOps - decisions (Technology)
AK-2.1.4 Example: Portfolio - budget (Processes)
AK-2.2 Creating a information system as purpose: how to start syst6x6_02 SHouse
AK-2.2.1 ...
AK-2.2.2 ...
AK-2.2.3 ...
AK-2.2.4 ...
AK-2.3 Value streams in Systems & components on their own syst6x6_03 VPossess
AK-2.3.1 ...
AK-2.3.2 ...
AK-2.3.3 ...
AK-2.3.4 ...
AK-2.4 Choices by systems for capabilities in uncertainties syst6x6_04 Fame-int
AK-2.4.1 ...
AK-2.4.2 ...
AK-2.4.3 ...
AK-2.4.4 ...
AK-2.5 Resource alignments for the system as a whole syst6x6_05 Honour-int
AK-2.5.1 ...
AK-2.5.2 ...
AK-2.5.3 ...
AK-2.5.4 ...
AK-2.6 Learning maturity from details at systems internals syst6x6_06 Learn-I
AK-2.6.1 ...
AK-2.6.2 ...
AK-2.6.3 Learning from AI understanding complex frameworks
AK-2.6.4 ...
AK-3 Details systems ZARF practical 6x6 reference framework
AK-3.1 Enabling the practical undertstanding continuum agil6x6_01 MDM2ext
AK-3.1.1 Explanation model example: Adaptive Transit Planning
AK-3.1.2 Practice Example: Information FLow from Supply to Delivery
AK-3.1.3 Practice Example: Platform Engineering
AK-3.1.4 ...
AK-3.2 The Purpose of defending against external threats agil6x6_02 SLife
AK-3.2.1 ...
AK-3.2.2 ...
AK-3.2.3 ...
AK-3.2.4 ...
AK-3.3 Value streams by systems the subsystems in a universe agil6x6_03 VWealth
AK-3.3.1 Model example: Adaptive Transit Planning
AK-3.3.2 ...
AK-3.3.3 ...
AK-3.3.4 ...
AK-3.4 Choices by systems as capabilities by uncertainties agil6x6_04 Fame-ext
AK-3.4.1 ...
AK-3.4.2 ...
AK-3.4.3 ...
AK-3.4.4 ...
AK-3.5 Resource continuity of the system in a universe agil6x6_05 Honour-ext
AK-3.5.1 ...
AK-3.5.2 ...
AK-3.5.3 ...
AK-3.5.4 ...
AK-3.6 Learning maturity from details by systems practical's agil6x6_06 Learn-@2
AK-3.6.1 Systems adding value, what are the values?
AK-3.6.2 Systems thinkning and lean: duality not a dichotomy
AK-3.6.3 Learning from AI trying to improve complex frameworks
AK-3.6.4 Learning from AI trying to understand complex systems
⚖ AK-1.1.3 Guide reading this page
The quest for methodlogies and practices
This page is about a mindset framework for undertanding and managing complex systems. The type of complex systems that is focussed on are the ones were humans are part of the systems and build the systems they are part of.
When a holistic approach for organisational missions and organisational improvements is wanted, starting at the technology pillar is what is commonly done. Knowing what is going on on the shop-floor (Gemba). Working into an approach for optimized systems, there is a gap in knowledge and tools.
👁 💡 The proposal to solve those gaps is "Jabes". It is About: Seeing "Jabes" as a system supporting systems the question is what system is driving jabes? The system driving Jabes must have similarities to the one that is driving it.
👁 💡 ZARF (Zachman-Augmented Reference Frame) is a streamlined upgrade to the classic Zachman matrix. It turns a static grid into a practical, multidimensional map that guides choices, enforces clear boundaries, and adds a sense of time, so teams move methodically from idea to reality
Business intelligence - Artificial intelligence
The world of BI and Analytics is a challenging one. It is not the long-used methodology of producing administrative reports. A lot needs to get solved, it is about information for shaping change:
The issue is that is technology driven situation, where it should be:
  1. ⚙ Operational Lean processing, design thinking
  2. 📚 Doing the right things, organisation & public.
  3. 🎭 Help in underpinning decisions boardroom usage.
  4. ⚖ Being in control, being compliant in missions.
Dashboarding reporting for closed loops used in good-regulators are approaches in the attempts solving those in systems.
❗ ⚠ The fractalness in systems make it unclear who the stakeholder for some dashboarding really is. The technology drive by the market is hiding the question for who and what in the why in variety and fractals of systems.
A recurring parabal for methodlogies and practices
An often used similarity is going to the life at and on ships. The simplification is that is a clear boundary for the internal and external systems of the ship.
There are nice clear three vertical rows:
  1. The executives deciding over what to happen on the ship and the direction it should go.
  2. Space for the product - service whether it are passengers or cargo.
    How this is manged needing dedicated staff.
  3. The engines for the structure (data centre) out of sight below visibility.
    Dedicated staff operating informing and advising on decisions.
This can be set in a perspective of: Strategy, Tactical, Operational.
Another perspective could be: Far future, near future and the now.
For each of them there are however dualities and dichotomies.
There are nice clear three horizontal columns:
  1. The structure for the goal and purpose what the ship does (BPM)
  2. Managing the structure for the technology the engines (SDLC)
  3. Getting the information for informed decisisons (Analytics)
Interacting with the external systems in some controlled alignment:
  1. Information resources for getting better decisions (Data).
  2. Improving the knowledge by what is known (Meta). e.g. de product - service handling in cargo and passengers
  3. Changing the knowledge in what is not already known (Math).
    e.g. new product -service opportunities or a complete different ship.
Triangle BPM SDLC BIANL - unequal improvement lines
In a figure,
see right side

The allegory for using a ship goes on into how to mange that. Your business is a boat navigating the river of waste. (S.Angad, 2025)
What you see above water are symptoms. What's hidden below are the real problems.
what's visible real problems
Machine downtime Untrained workforce
Quality defects Forecast inaccuracy
Long changeovers Poor communication
Schedule delays Outdated processes

Most leaders focus on what's visible, but these are just rocks breaking the surface. The real problems are underwater.
Here's what I've learned after years of helping manufacturers:
👉🏾 You can't steer around every rock.
👉🏾 You have to lower the water level.

When you reduce the waste in your system, problems that were hidden suddenly become visible. That's uncomfortable. But it's necessary. Most improvement efforts fail because they treat symptoms. Real improvement lowers the water level.
treat symptoms Real improvement
Hire more inspectors for quality issues Train people to prevent quality issues
Add buffer inventory for supply problems Fix forecasting to reduce inventory needs
Work overtime for capacity constraints Improve flow to eliminate capacity constraints
Buy faster machines for throughput gaps Standardize work to reduce variation


The goal isn't to avoid problems. The goal is to see them clearly so you can solve them permanently. Your biggest competitive advantage isn't having fewer problems. It's solving problems faster than your competition. Lower the water level. Expose the rocks. Remove them one by one.
⚒ AK-1.1.4 Progress
done and currently working on:
The topics that are unique on this page
👉🏾 Rules Axioms for the Zachman augmented reference framework (ZARF). 👉🏾 Connecting ZARF to systems thinking in the analogy of: 👉🏾 Explaining the patterns that are repeating seen in this.
👉🏾 use cases using the patterns for Zarf and by Zarf. Highly related in the domain context for information processing are:
Archive of knowledge

AK-1.2 Knowledge shoulders for the 6x6 RFW

Consolidating what is existing for needing knowledge into simplified knowledge is hard. How is that process done? There are several stages in this.
  1. Collect and sort what is assumed to be relevant.
  2. Cleaning and transforming the knowledge so
    all that knowledge is ready to map to each other.
  3. Mapping the collected knowledge and
    evaluate the result on for new value.
  4. Communicating the results using adjusted perspectives for the audience.
There is no need to do this in sequential approach, a disordered iterative one makes far more sense. In an iterative approach there is the option to do a continious feed-back loop, improving the actvities for improving the result(s). Reflections in perspectives are inward journeys.
⟲ AK-1.2.1 Starting in understanding by asking the right questions
The classical eference framework of questions
"the-six-socratic-questions" (Charles Leon)
  1. What? Questions for clarification.
    1. What is the problem you are trying to solve?
    2. Can you give me an example?
    3. Can you explain further?
    4. Are you saying ... ?
  2. How? Questions that probe assumptions.
    1. What could we assume instead?
    2. Are you assuming ... ?
    3. How can you verify or disprove that assumption?
    4. Is that always the case?
    5. What would happen if ... ?
  3. Where? Questions that probe reason and evidence.
    1. What would an example be?
    2. What is this analogous to?
    3. Why do you say that?
    4. How do you know?
    5. Why? 5x
    6. What evidence is there that supports ... ?
  4. Who? Considering alternative perspectives
    1. Are there any alternatives?
    2. What is the other side of the argument?
    3. What makes your viewpoint better?
    4. What is another way to look at it? What is the counter-argument?
    5. Who benefits and who would be affected by this?
    6. What are the strengths and weaknesses of ... ?
  5. When? Consideration of implications & consequences.
    1. What generalizations are being made?
    2. What are the implications and consequences of the assumption?
    3. How does that affect ... ?
    4. What if you're wrong?
    5. What does our experience tell us might happen?
  6. Why? / Which? Meta-questions. questions about the question.
    1. What is the point of the question?
    2. What does ... mean?
    3. Why do you think I asked this question?
    4. How does ... apply to everyday life, objectives/mission statement etc.?
🤔 Adding the 5W1h from the engineering order is a novel and unexpected idea. It gives the impression of an objective technical approach but going from a what to why/which, but this this classical approach is heavy weighting on the Were and Who.
Too far narrowing: Just limiting into three Why ... What
A very inspiring statement is: Start with Why (Simon Sinek, 2009) Sinek says people are inspired by a sense of purpose (or "Why"), and that this should come first when communicating, before "How" and "What".
🤔 The issue in this: it is too far narrowing: only the scope of a purpose for engineering. For the sense of purpose there is an important choice option to make.
👁 Another issue is the Where and Who: Creating the options might be the technical enabler for these activities that are the not mentioned intentions. There is a duality and dichotomy in expectations and the intentions by communication.
⇅ More ambiguous is the "How" of Sinek. That seems to be anything in between. For a high level expectation it will do, but when there are more details asked, it gets quickly confusing.
⚠ Just changing words but not the intention is a recipe for a lot of confusion as is using the same words for other intentions. There is that everlasting challenge in communicating the intentions.
⟲ AK-1.2.2 Using a reference frame for questions and replies
Decoupling Zachman reference context abstraction
🤔 Zachman got a synonym for Enterprise Architecting, that is a far too lmited scope. The intention was a very generic systemic approach. But how is that intention got in a state of understanding, it got a question what is it really about. Discussions:
Understanding the intention in Zachman
👁 A Zachman framework is a more abstracted version, is decoupling the limited enterprise architecture context. That decoupling however is a root-cause for difficulties in the understanding of the intentions in classifications and relations by transformations.
⚠ Without a specific understandable example (use case) the intention is har to get, but using an example has the unwanted effect of narrowing it down to that example.
"Enterprise architecture defined" (lucid.com)
Lucid Zachman
⇅ It has left out the special EA content, but:
Named for its creator, John Zachman, this framework uses a structured matrix as a means to view and categorize an enterprise. The framework consists of a 36-cell matrix, with each cell focusing on a different perspective (such as business owner, planner, designer, and so on).
This matrix gives EA professional insights into the company's assets and how various components of the enterprise are related. This information can help companies be more agile and help to make better decisions.
Basic Issues for a Zachman reference framework
🤔 Issue 1 what: limited unclear set of Zachman rules.
➡ The framework doesn't have a clear set of rules axioma's. Only this:
  1. Columns have no order, are interchangeable but cannot be reduced or created
  2. Each column has a simple generic model, every column can have its own meta-model
  3. The basic model of each column is unique, relationship by objects, structure are unique
  4. Each row describes a distinct, unique perspective.
  5. Each cell is unique for its intend, content
  6. The composite or integration of all cells in one row constitutes a complete model from the perspective of that row.
  7. The logic is recursive
👁 This is full of uncertainties and ambiguity's.
⚠ Any innovation in this will get resistance for the resistance of change by systems.
⇅ Changes might result in too much complexity blocking acceptance.
🤔 Issue 2 how: limited unclear set of Zachman axis.
The Zachman 6*6 reference frame has two axis: ➡ This is incomplete because there is more by systems than only engineering.
👁 In the engineering perspective there already multiple perspectives in the kind of activities. ⚠ A fractal mindset switching the disciplines context is a hard concept.
⇅ The change in disciplines when there is a fractal is obvious but the consequence is needing the knowledge of those in a different type of context.
🤔 Issue 3 where: Aside the technology reference frame there is (should be):
➡ the counterpart in administration to help in the interactions relations and resources.
In the old historical eras, first wave, the administration was already inseparable from technology. Expectations, result and legal rights had to be ordered.
👁 The duality & dichotomy in doing the work and supporting the work in the system.
⚠ Switching the mindset with no context change between these two disciplines is a hard concept.
⇅ Misunderstandings are the root causes for conflicts between these two disciplines.
Extended Issues for a Zachman reference framework
🤔 Issue 4 who: Another perspective is trading justice and power.
➡ Near and far future directions, solving internal conflicts in the system and a vision for external conflicts for the system as a whole.
The change in concepts extends for the interactions intern and external of a system.
The concept is changed to functionality instead of functioning.
👁 The duality & dichotomy in functioning and functionality in the system.
⚠ The starting point and order a little bit different but at first sight, but a closer look show it is in essence the same just another chosen starting point. The changed order is impacting what is on the diagonals. That perspective to diagonal is having impact what is seen as most important.
⇅ The change in focus perspective is obvious when seen, otherwise hidden in ambiguities, a root cause for conflicts.
🤔 Issue 5 When: In the focus perspective of trading, justice, power, there are:
➡ two counterparts: the supply chain and the deliveries - consumers, allies & enemies.
👁 There is a duality & dichotomy in functioning and functionality in the system.
⚠ The interactions for trade justice & power are drivers for the system as a wole. The time and timing are dimensions that are highly influencing outcomes for the system.
⇅ Changing the context in disciplines (fractals) perspectives in concepts and a what is going on in a time dimension is a complexity very hard to realise for consciousness awareness.
🤔 Issue 6 Which/Why: Having a lot of states what is annoying to see missing is:
➡ how the interactions between all those those is behaving.
👁 The duality & dichotomy in what is controllable and what is only being influenceable in uncertainties and unpredictability within certain ranges predictable.
⚠ Assuming controllability in certainty and predictable never has become a truth.
⇅ A cultural change for adaption is the major aspect for influencing transformations, otherwise hidden in ambiguities, a root cause for conflicts.
⟲ AK-1.2.3 The human value drivers: safety, wealth, fame, honor
Exploring the human motivations as systemic drivers
The first fault line: systems are being built without acknowledging the human value drivers—safety, wealth, honor, and fame. These aren’t just soft concerns; they are the invisible forces shaping behavior, trust, and legitimacy. Traditional models lacked the language to express them, let alone regulate them.
Human motivations drive behavior in systems where people are both designers controllers and participants. This connects to Conant & Ashby’s Good Regulator Theorem, which says a system must model its environment to regulate effectively.
🤔 Gaps identified:
  1. Lack of human-centric modeling: Traditional frameworks don’t account for emotional, cultural, or motivational drivers like safety, honor, or fame.
  2. No integration of trust boundaries: Zero Trust models assume breach but lack nuanced trust-building mechanisms.
  3. No fuzzy logic for uncertainty: Systems assume binary control, ignoring aleatory (irreducible) and epistemic (reducible) uncertainty.
  4. No feedback-based legitimacy: Systems don’t adapt based on citizen trust or social legitimacy—only technical correctness.
Roles impact and interactions by human motivations in systems
The roles of human motivations is they are creating requirements for the system: The issue is that this is full of possible conflicts by the different perspectives.
Driver Engineering Administration Delivery Supply
Safety Secure design Risk policies User trust Supplier reliability
Wealth Cost efficiency Budgeting Value delivery Margin control
Fame Innovation, visibility Leadership, branding Customer perception Market positions
Honour Ethical standards Governance integrity Service fairness Trade legitimacy

Some Possible conflicts: The Zarf_Xpos rules have the intention to cover this in the 6*6 thinking reference. This very abstracted approach has a domain context for information processing here.
each system has a gradient of human values—some cells are more influenced by safety, others by fame, etc. This gradient can be used to:
Systems thinking the "good regulator"
A system that is generating result that are unpredictable harmful is an unsafe situation.
An important but hard to understand system property is the close loop that is optimising in predictable at some trust interval by values for desired outcomes. a straightforward explanation of the good regulator theorem (lesswrong)
Conant and Ashby are interested in the question: 'what properties should R have in order for a regulator to be good?' ... If a regulator is 'good' (in the sense described by the two criteria in the previous section), then the variable R can be described as a deterministic function of S.
Analysing what is stated. 👉🏾 There is an approach for a good regulator: the well known PID controller.
This is only suitable for a system with one dimension for the output and one for the input and there is an predictable influence in adjusting.
Any system with more dimensions becomes unpredictable in some area's, behaving chaotic.
About Safety tied to technology & functionality
Safety, Cyber Security axioms, Zero Trust" rests on two core rules: 🤔 These axioms are not realistic workable because there is no uncertainty of any type incorporated in this. It fails in the criterion for defined refutations (K.Popper).
👁 💡 The only way out of this dilemma is: 👉🏾 Perimeter demarcation under Zero Trust becomes less about a single network edge and more about enforcing trust boundaries around every asset, user, and transaction.
Why Demarcation in Cyber Security, safety axioms matters in Zero Trust:
⟲ AK-1.2.4 System drivers: Antipodes, dualities and dichotomies
Explore the systemic tensions in systemic drivers
The second fracture: systems are riddled with dualities—internal vs. external, control vs. influence, structure vs. behavior. Yet no unified taxonomy existed to model these tensions. Governance is fragmented, rules scattered, and timing ignored. Complexity is treated as noise, not signal.
Exploring the dualities dichotomies and contradictions that shape complex systems: internal vs. external relations, power in control vs. influence, organise structure vs. cultural behaviour.
🤔 Gaps identified:
  1. No unified rule taxonomy: Existing frameworks scatter rules, permissions, rights, and implications across disconnected silos.
  2. No modeling of dualities: Existing Systems theories don’t account for inherent tensions (e.g., functioning vs. functionality, internal vs. external power, justice, trade).
  3. No time-sensitive governance with defined uncertainties : Existing frameworks are lacking timing and temporal alignment from transformation logic. Systems assume binary control, ignoring aleatory (irreducible) and epistemic (reducible) uncertainty.
  4. No support for cultural adaptation:Existing Systems theories don’t account for socially evolvements, they’re static and technocratic.
To quickly grasp the nature of systemic tensions by the yypes of dualities and their impact:
Duality Type Description Systemic impact
Internal vs External Boundaries of control vs influence Governance scope, stakeholder mapping
Functioning vs Functionality Behavior vs purpose Design intent vs operational reality
Control vs Influence Direct command vs indirect shaping Leadership, policy, culture
Fairness vs Authority Negotations, justice and power Legitimacy, compliance, trust
Static vs Adaptive Fixed rules vs evolving norms Resilience, transformation capability

System rules, understanding, taxonomy
In the sender and receiver context that should get aligned for an understanding, the used language is the guideline. full array of guidance for business and activity (R.Ross 2025)
The full array of guidance for business and government is far richer than you might imagine,it includes not only rules, but permissions, authorizations, rights, warranties, and logical implications (inference rules). In organizations today, this guidance is not at all unified, but is spread more or less haphazardly across large numbers of processes and systems, both automated and not. No wonder operational governance and compliance proves so difficult and expensive. We need a unified view and the right kind of platforms to support it.
😉 On business rules and data semantics, outlines fundamental kinds of data descriptions in his work to help organizations achieve clarity and precision in business communication. There is no connection made into those rules into six categories that are a fit the tot the 6w1H in engineering or administration context. An attempt for that: These descriptions are essential for creating concept models that align data with business meaning.
Reconstruct paths

AK-1.3 Augmented axioms: Anatomy Physiology ZARF

Consolidating what is existing for needing knowledge into simplified knowledge is hard. Where should transformation in sorted knowledge be applied and for what reason? There are several approaches.
  1. Have a defined way of orientation in the knowledge representations.
  2. Search for deviations in the collected knowledge so
    the orientation is adjusted to the defined standard.
  3. Search for gaps and contradictions in the collected knowledge
    Make adjustments for closing gaps solving contradictions.
  4. Document and communicate the results of adjustments in perspectives for the audience.
The space for values, knowledge, structure, and tradition is limiting the scope. The reflections in perspectives and meditations are inward journeys.
⟲ AK-1.3.1 Understanding & changing the reference frame
Not using the "Why" but "which" in the 6w1h
Replacing "Why" with "Which" in the Zachman Framework shifts the focus from an understanding an abstract situation as purpose to concrete decision-making for abstractions. The purpose of a system is what it does (POSIWID) is a heuristic in systems thinking coined by the British management consultant Stafford Beer. From a cybernetic perspective, complex systems are not controllable by simple notions of management, and interventions in a system can best be understood by looking at how they affect observed system behaviour. By using "Which", it becomes choosing among viable options based on context, constraints, and priorities.
👁 ➡ Instead of asking "Why does this system exist?",
👁 💡 we now ask "Which option best fulfils our goals?".
This aligns better with adaptive planning, scenario modelling, and option evaluation, especially in dynamic environments like enterprise design or AI governance. Benefits of Using Which are:
An automatic property in fractals by using "which"
The Perpective of multiple perspectives for concepts definitions in the same context identifications. It are variations in the same basic questions. Only the ordering is the variation.
  1. Engineering: What, How, Where, Who, When, Which
  2. Administration: Which, When, Who, Where, How, What
  3. Trading justice and power (internal): Who, When, Which, What, How, Where
  4. Trading justice and power (external): Where, How, What, Which, When, Who
How would these different ordering get well ordered (good order) in a two dimensional approach?
4 dimensions for the 6w1h
In a figure:
See right side

In this choice for orderings not only the mentionend 4 variants in the horizontal and verticals are there but also 4 others in the diagonals.
  1. Machines - Technology: Which, When, Who, What, How, Where
  2. Processes - Operations: Who, When, Which, Where, How, What
  3. People - Service: Where, How, What, Who, When, Which
  4. Plan enable - Structure: What, How, Where, Which, When, Who
😉 The question in this is whether this would make sense. (LLM):
The order of the 6W1H axis isn’t fixed—it’s context-sensitive. Each ordering reflects: This means the reference frame isn’t just a grid, it’s a multi-perspective modeling tool.
That is nice reply, "the ordering is not fixed" is a nuance in difference for there original Zachman rules that it doesn't matter.
😉 Adjusting the image after some feedbacks. Intersting replies because SIAR was intended as: 😉 It is coming up with nice alternatives, AIRS crossing the flow not using a cycle. 😉 For engineering “Do the things right” (push) and administration “Do the right thing” (pull).
😉 For the dualities dichotomies it connected to the human drivers. ❗ Fairness vs Authority is the cultural challenge for the system.
An automatic property in fractals by using "which"
Using a fractal approach is similar to divide and conquer. The Divide and Conquer paradigm involves three main steps:
  1. Divide: Break down the problem into smaller sub-problems that are more manageable.
  2. Conquer: Solve each sub-problem recursively or using a suitable algorithm.
  3. Combine: Combine the solutions to the sub-problems to obtain the final solution.
Instead of doing what has always been done 👁 ➡ , combining components in another ordering.
👁 💡 Using the 6*6 reference frame conbined to systems thinking. Seeing systems thinking and lean as two powers that are strongly correlated.
The systems thinking 6*6 reference frame in an engineering context using and ordered asxis using a fixed 5w1H strcutur for anserwering a Why in the content.
  1. What ➡Bills of Material The parts are defining how they interact.
      👁 Which components are needed?
  2. How ➡Functional Specs The function decides where each part goes.
      👁 Which processes or algorithms apply?
  3. Where ➡Drawings / Geometry Layout:assign roles to: who installs, monitors, responds.
      👁 Which layout or topology is optimal?
  4. Who ➡Operating Instructions The timing of actions by roles-who.
      👁 Which roles or agents are responsible?
  5. When ➡Timing Diagrams Align all decisions for the system and in the system.
      👁 Which sequence or timing pattern fits?
  6. Which ➡Design Objectives - Choices With purpose: security, reliability, user-friendliness.
      👁 Which design path best meets constraints and goals?
🤔 The which question implies an iteration recursion for each column abstraction. The result is 7 times a which abstraction one more in variety than the number of columns.
Each abstraction isolates one dimension of the system, reducing ambiguity and assumptions.
😉 Although the presentations are by ordererings the approach is not sequential but iteratives.
😱 If you skip a cell, say you don't define when things happen, you risk performance issues or user frustration. As Zachman notes, missing interrogatives lead to implicit assumptions, which are breeding grounds for defects.
⟲ AK-1.3.2 Duality dichotomy Anatomy - physiology: 1* dimensions
Defining the anatomy frame structure
Instead of doing what has always been done, combining components in another ordering. A clear set of rules for the 6*6 reference model for better understanding of that model.
👁 ➡ Using the 6*6 reference frame in combination to systems thinking.
👁 💡 Seeing systems thinking and lean as two strong correlated powers.
Rules for the Zachmand 6*6 reference frame in the new (anatomy) perspective
Rule id Title - Purpose Core Function
ZARF_STRC_01 Ordered Horizontal Axes (Flows)
Defines the limbs and orientation 		Defines four horizontal flows—Engineering, Administration, Delivery, Supply—each with a distinct interrogative order. These flows represent complementary system perspectives.
ZARF_STRC_02 Ordered Vertical Axis (Abstractions)
Builds the spine of abstraction 		Establishes six abstraction layers from Context to Instance. These layers represent increasing specificity and operational detail.
ZARF_STRC_03 Time Dimension (Now, Near Future, Far Future)
Adds the heartbeat of time 		Adds temporal layering to each cell, enabling planning, forecasting, and phased transformation.
ZARF_STRC_04 Recursive “Which” & Domain Knowledge Evolution
Enables growth, adaptation, and evolution 		Defines fallback paths and rollback logic for failed transformations, preserving system validity and continuity.

Defining the physiology frame interactions
Rules for the Zachmand 6*6 reference frame in the new (physiology) perspective.
Rule id Title - Purpose Core Function
ZARF_INTR_01 Structured Interaction Paths & Transformation Boundaries
defines the joints and movement limits 		Limits transformations to vertical (same column) and horizontal (same row) moves. Diagonal interactions are restricted unless explicitly orchestrated.
ZARF_INTR_02 Nonlinear Interaction Logic & Recursive Depth Control
allows flexibility and depth 		Allows independent, non-sequential transformations. Recursion depth varies by stakeholder, domain, and time slice.
ZARF_INTR_03 Dependency Mapping & Precedence Logic
ensures coordination and balance 		Requires each transformation to declare its input dependencies and execution order. Prevents hidden knock-on effects.
ZARF_INTR_04 Cell Uniqueness & Structured Consolidation
enables domain-level strength and simplification		 Ensures semantic uniqueness of cells. Supports 2×2 and 3×3 consolidation patterns when recursion reaches atomicity..

⟲ AK-1.3.3 ZARF: Anatomy axioma's rationale & implications
ZARF_STRC_01: There are four interacting reference frames axis.
    • ZARF_STRC_02: There is one vertical reference frames axis.
    ZARF_STRC_03: The time dimension, now, near future and far future states.
    ZARF_STRC_04: In the "which" recursively at a cell changing domain knowledge
    ⟲ AK-1.3.4 ZARF: Physiology axioma's rationale & implications Physiology by ordered axis - six categories, multiple dimensions
    ZARF_INTR_01: Structured Interaction Paths, Transformation Boundaries & Diagonal Governance
    ZARF_INTR_02: Non-Linear Interactions, Recursive Depth & Contextual Boundaries
    ZARF_INTR_03: Explicit Dependency Mapping, Precedence Logic & Orchestration Integrity
    ZARF_INTR_04: Cell Identity, Recursion Boundaries & Domain Consolidation
    Metamorphose

    AK-1.4 Augmented axioms: Neurology Sociology ZARF

    Consolidating what is existing for needing knowledge into simplified knowledge is hard. Who has responsibilies for what activities and for what reason? There are several considerations.
    1. Have a defined way of roles/tasks for the knowledge usage.
    2. Search gaps for type and closed loops in the systems.
      Make adjustments for closing the found gaps.
    3. Document and communicate the results of adjustments in perspectives for the audience.
    4. Communicate the challenge of uncertainties unpredictability's.
    The space for values knowledge, structure, and tradition is limiting the scope. The reflections in perspectives and meditations are outward journeys.
    ⟲ AK-1.4.1 DIKW Closed loops - good regulators
    Value stream processes, understanding the physiology (I)
    A value stream, VSM VaSM, can be represented in a very simplified way that it is far too oversimplified. Reduced to what is basic to flows it is about: What & Which from internal to external controlled by Who & Where. The image in AK-1.3.1 is showing the complexity in the 6*6 reference frame. A VaSM is commonly presented as an operational situation for industry.
    A far more abstracted version of the flow Push (technology, engineering): And the Push (coordination, administrative): Organisation Boarding safetycvaluestream Neuro
    In a figure,
    see right side

    ❶ The flow is from left to right, push, at the top and right to left, pull, at the bottom.
    ❷ There are four similar areas, the chosen representation is unhiding 2 lines of 6 stages.
    ❸ The flow itself is uncontrolled, there are no regulators.

    The intelligence / realsiation dimension
    The DIKW model is often quoted it represents the main relationship from data to the wisdom. However, the origin and its reasoning for what its intentions in identification context are, is unclear. Missing that context it is obvious DIKW is a valuable truth but missing the relationship to content it got useless. A discussion over the intention of DIKW reveals the context and immediate changed it to DIKIW. Should We Rely on Intelligence Cycle (Bahadır Aydin, Zafer Ozleblebici 2015)
    The DIKIW Pyramid represents the main relationship from data to the wisdom. Every step has a meaning of its own. Data is the starting point of pyramid. The desired end is reaching wisdom, but it is not easy to reach, because it is obscure.
    Continuum Understanding Cleveland 1982
    In a figure:
    The Continuum of Understanding (Cleveland, 1982)

    There is a connection in applying the DIKW model for the good-regulator of viable systems theory.

    There are 5 interactions four the 4 DIKW states Researching Absorbing Doing Interacting Reflecting

    Know nothing (data) - Know what (information) are: Know how (Knowledge), know why (Wisdom) are:
    Value stream processes, understanding the physiology (II)
    Reduced to what is basic to control flows it is about: Who & Where for internal and external interactions regulating controlling the What & Which . The image in AK-1.3.1 is showing the complexity in the 6*6 reference frame. A VaSM is commonly presented as an operational situation for industry. The history of lean is based on industrial approaches attempting to understand the flow.
    An abstracted version of the control regulations in the flow : And the Push (coordination, administrative): Information over the flow is indirect, using the knowledge shared in the flow.
    Organisation Boarding good regulator Neuro
    In a figure,
    see right side

    ❹ The flow is top-down and bottom-up at the backend and frontend side.
    ❺ The four similar areas acting for internal alignment of the system in two complex lines of 6 stages.
    ❻ There are two❗ related artifacts that are expected to be in under control by a good regulator.

    The similarity to a heart is pure accidental. The knowledge storage areas are part of the brain nervous system as is the insight for decisions.
    The abstraction over both lines is reversed to operational control:
    ⟲ AK-1.4.2 Duality dichotomy Neurology - Sociology: 1* dimensions
    Defining the frame interactions
    Rules for the Zachmand 6*6 reference frame in the new (physiology) perspective:
    Rule id Title - Purpose Core Function
    ZARF_VIRU_01 Feedback Loop Closure & Convergence
    Senses and interprets feedback     		Ensures every transformation sends feedback upstream and includes convergence metrics to validate success.
    ZARF_VIRU_02 Governance Constraint Propagation & Audit Trails
    Enforces rules and memory     		Propagates top-down constraints from higher abstraction layers and logs all transformations for traceability.
    ZARF_VIRU_03 Composite Interaction Sequencing & Time Alignment
    Coordinates movement across limbs     		Orchestrates multi-cell transformations via atomic steps, coordinated by a System-2 cell, aligned to time slices.
    ZARF_VIRU_04 Exception Channels & Compensation Paths
    Responds to injury and restores balance    		 Defines fallback paths and rollback logic for failed transformations, preserving system validity and continuity.

    Defining the frame social expressions
    Th governs the external expression, positioning, and social dynamics of the system. Articulate how the system presents itself, adapts socially, and interacts with external agents, cultures, and ecosystems. The face, voice, and social behavior of the system.
    Rules for the Zachmand 6*6 reference frame in the new sociology perspective:
    Rule id Title - Purpose Core Function
    ZARF_XPOS_01 External Identity & Social Role Mapping
    defines how the system introduces itself     		Defines how the system presents itself to external actors—its identity, roles, and perceived purpose.
    ZARF_XPOS_02 Cultural Alignment & Stakeholder Resonance
    ensures it speaks the right language     		Ensures the system’s values, language, and behaviors align with the cultural expectations of its environment.
    ZARF_XPOS_03 Social Adaptation & Ecosystem Integration
    helps to adapt to changing social climates     		Governs how the system adapts to external changes, norms, and feedback from its ecosystem.
    ZARF_XPOS_04 Trust, Legitimacy & Reputation Management
    protects its reputation and social license     		Tracks how the system builds and maintains trust, legitimacy, and reputation across its social interfaces.

    ⟲ AK-1.4.3 ZARF: Neurology axioma's rationale & implications
    ZARF_VIRU_01: Closed Feedback Loops, Upstream Synchronization & Convergence Metrics
    ZARF_VIRU_02: Policy Enforcement, Constraint Propagation & Transformation Traceability
    ZARF_VIRU_03: Multi-Cell Choreography, Phase Alignment & Coordination Integrity
    ZARF_VIRU_04: Exception Handling, Rollback Integrity & Adaptive Recovery
    ⟲ AK-1.3.4 ZARF: Sociology axioma's rationale & implications
    ZARF_XPOS_01: External Identity & Social Role Mapping.
    ZARF_XPOS_02: Cultural Alignment & Stakeholder Resonance.
    ZARF_XPOS_03: Social Adaptation & Ecosystem Integration.
    ZARF_XPOS_04: Trust, Legitimacy & Reputation Management
    inside - outside

    AK-1.5 Insight for intelligence in viable systems

    Consolidating what is existing for needing knowledge into simplified knowledge is hard. When all what is changing has what kind of impact has those changes? Considerations for impacts:
    1. Get to a way of values for the information knowledge usage.
    2. Search gaps for type of values and value levels.
      Make proposals for found gaps.
    3. Document and communicate the proposals for adjustments in perspectives for the audience.
    4. Create understanding for uncertainties unpredictability's.
    The space for values, knowledge, structure, and tradition is limiting the scope. The reflections in perspectives and meditations are outward journeys.
    ⟲ AK-1.5.1 Dualities, dichotomies in the context of flow
    States transformations as dualities in the flow
    An understandable duality is the continuous change between states and processes. Even when well understandable this becomes quickly confusing chaotic.
    Duality Process Information in flows
    In a figure,
    see right side

    Some are focussing on states others on processes.
    DIKW revisited understanding and insight for closed loops.
    Data information Knowledge Wisdom, DIKW, is often stated as important but there is a gap in why it is important what the impact in a systems is and how it is made practical. Getting into the intentions of this with: From Data to Wisdom (Russell Ackoff 1995) Wisdom deals with values. It involves the exercise of judgment. Evaluations of efficiency are all based on a logic that, in principle, can be programmed into a computer and automated. We can speak of the efficiency of an act independently of the actor. Not so for effectiveness. There is a clear duality dichotomy stated in what is different to data & information a fraction boundary to knowledge & wisdom. There is more text in that short note. ... A philosophical twist:
    The turing test in the information age era: "It may well be that wisdom, which is essential for the pursuit of ideals or ultimately valued ends, is the characteristic that differentiates man from machines."
    Optimizing a flow are perspectives for intelligence in a system
    A detailed topic is: TOC theory of constraints, optimizing flow for a defined goal although that goal is by uncertainty ambiguousness understanding. There is much to find, but there is no alignment made into systems thinking. That is remarkable because in systems thinking there is a good-regulator as one of the components by anatomy. 👉🏾 Together, they form a dual regulator archetype: one reactive, one proactive. That is a duality and dichotomy. Even more challenging:
    ⟲ AK-1.5.2 Vision, Wisdom, knowledge Intelligence - good regulator
    Hierarchy, Allocation and of Understanding in intelligence.
    A visionary conference paper building on available knowledge. Hierarchies of Understanding: Preparing for A.I. (Scott A. Carpenter, Catherine Liu, Weixun Cao, and Allen Yao 2018)
    Already machines process data and information many orders of magnitude better than humans do in speed, quality, and quantity. Soon A.I. and other semantic technologies may process knowledge as easily as computing systems process data and information today. This work assumes that such A.I. ability comes into effect in the 2020s and that A.I. quickly outperforms human knowledge management.
    That predicition (2018) has become reality (2025) for the level in hierarchy up to information processing. Search machines (data) have got extensions for information processing (LLM).
    In Ackoff’s day, his hierarchy was often called a knowledge hierarchy; however, today it is more often called a wisdom hierarchy because its uppermost layer is the wisdom layer. ...
    The Vision HoU combines a top-down hierarchy of conjectured contexts (values, goals, models, categories, and indexes) with a bottom-up hierarchy of belief (data, information, knowledge, wisdom, and vision) ... Use the HoU to review the trends and hypothetical impact to human AoU caused by implementation of semantic technologies, and then predict what impact 2020s U.A.I. may have for human cognitive-cybernetic activities.
    Duality Process Information in flows
    In a figure,
    see right side

    Hierarchy of Understanding.
    👉🏾 There is a search for hierarchy that is practical.
    A shift ,seeking new balance in the Hierarchy of Understanding.
    The System Dynamics Model is a methodology for understanding, modelling, and analysing complex systems. It focuses on the feedback loops, time delays, and accumulations that drive system behaviour.
    The vision hierarchy of Carpenter (2002 2008) is a best fit for getting intelligence into a position in ZARF for the closed loop, good regulator. The change made is that DIKW is revisited to an understanding and insight for actors, added are the Environment and Vision EDIKIV. With a hierarchy a shift in that is possible when conditions change.
    Duality Process Information in flows
    In a figure,
    see right side

    Data systems (c.1960s-present) should up-shift one’s allocation of understanding (AoU).

    The shift in data-handling is seen at the moment (2025) by the trust in search engines and evolving LLM.
    Duality Process Information in flows
    In this mindset the goal is achieving wisdom vision using the hierarchy from the environment, data in a bottom up approach. For a practical case it is looking at the shop-floor, Gemba, in lean.

    The top down approach is disturbing our common mind The learner applies some kind of context to the knowledge from which information emerges. Similarly, data emerges from contextualized information. What data is needed from the environment for proof or falsification of a hypothesis is however recognizable as good scientific practice.

    Creation intelligence Abstraction Use of intelligence
    Environment Context Vision
    Data Concept Wisdom
    Information System Logic Knowledge / Insight
    Knowledge / Insight Technology Information
    Wisdom Components Data
    Vision Instance Environment

    When Vision is unknown, should get support by intelligence, the abstraction starts with getting data.

    When the Vision is known, is applied from the higher level context by intelligence, the abstraction starts there.

    The direction of the abstraction level is defined by context. A teaser in this is Wisdomism (Tuomi).
    The intelligence cycle and its relevancy in the changing world
    Having not one but two intelligence cycles, what about "the intelligence cycle"? Should We Rely on Intelligence Cycle (Bahadır Aydin, Zafer Ozleblebici 2015) Is about the one for getting a Wisdom Vision from data.
    Famous scholar Ackoff defines data as symbols. It is widespread and has no meaning alone.
    👉🏾 If data can’t be related to other events by itself, it has no specific purpose at all. Information: The IntelligenceCycle (source FBI) In the conclusion:
    Intelligence requirements are crucial for all intelligence cycles. The requirements can be classified as standing requirement and spot requirement. Traditional intelligence cycle may be applied for standing requirement, which provides information for mid and long term. As for today’s needs, they are usually spot requirement, which is specific and timely needed.
    The overwhelming conceptualizations of intelligence cycle may not be useful, because of massive data. So we must dwell on the results apart from intelligence cycle.
    👉🏾 The interpretation of this:
    ⟲ AK-1.5.3 Intelligence Duality, dichotomy: context-abstraction
    The intellignece frameworks a practical case influncing the abstractions
    A nice write up for a specific domain, the information security was noticed (safety): CTI Key Concepts: A5. The Intelligence Cycle (LI: Nomende C. Security analyst 2024)
    The Intelligence Cycle is a six-stage process used by government, and military agencies to produce intelligence. The six stages are Planning and direction, collection, processing and exploitation, analysis, dissemination and feedback. The intelligence cycle can be traced back to Sherman Kent, a Yale University history professor. His journey to intelligence started during World War II, and he was known as the “father of intelligence analysis”.
    There are several figures used for the explanation. All six in a cycle and others showing five, in a circle the sixth in the middle. Another post (LI: Treston Wheat ) same topic, similar text but:
    The cycle, depicted as a closed loop, emphasizes continuous refinement and feedback to ensure that intelligence requirements are met effectively.
    👉🏾 When one of the who cycles in the abstractions are a feedback control closed loop, it is acting as a good regulator in the system (system-2 ViSM) for the system.
    The intelligence cycle as an information flow with subsystems. :
    The delivery of results (which) is connected to a when that is the external to doing the analysis it could by seen as the universe (ViSN).
    1. system-1 What Planning and Direction, the first stage, involves establishing the goals for an intelligence programme, which includes understanding what needs to be protected, the potential consequences of failing to do so, the intelligence required by the organisation for protection and response, and the prioritisation of what to protect.
    2. system-3 How The collection stage concerns gathering various types of data and information from numerous internal and external sources. Internal sources are networks and security devices, threat data feeds, interviews, news websites and blogs, social media platforms, websites and forums. Closed sources are ones like dark web forums.
    3. system-4 Where Processing and exploitation is the stage in which collected data is normalised, structured and organised in a way that can be readily retrieved, searched, and used by analysts.
    4. system-5 Who The analysis and production focuses on transforming processed information into actionable intelligence. Effective intelligence analysis considers the user of the intelligence and their decisions and is presented in a readily understandable and actionable format.
    5. system-2 When During the dissemination stage, intelligence is delivered through channels, such as written reports, emails, verbal briefings, or integration with security tools. It is tailored to the needs and technical understanding of the audience.
    6. universe Which The feedback stage provides information on the future iteration of the cycle. It allows intelligence consumer to report the effectiveness of the intelligence and if it meets their needs.
    👉🏾 The confusing en hard parts for understanding in this are:
    Intelligence frameworks influence at abstractions levels
    Practical cases are influencing the mindset how things are functioning by their functionality. The intelligence cycle for creating / supporting a vision: This mapping shows how Knowledge Insight acts as a pivot point—where feedback, cultural alignment, and strategic foresight converge. Knowledge / Insight pattern recognition, sensemaking, and foresight synthesis Bridges Wisdom (what we know) with Vision (what we should do) Enables decision relevance, timing, and strategic clarity.
    To me surprise a LLM gave this correct answer when in search for the decision maker:
    In ZARF, the Instance layer represents the operational manifestation of decisions—not the decision-maker itself. It’s where behavior is enacted, not where choices are made. So, Wisdom is formed at the upper layers (Context–Concept), Insight emerges in System Logic–Technology, and Instance consumes the outcome—but doesn’t originate it.
    The intellignece frameworks influencing the abstractions
    💡❗ Connecting the "when" and "component" to the good regulator (system-2 ViSM) gives some practical sense to the TOC optimizing flows in being both reactive (Goldrath) and proactive (M. Balle) in the VaSM cycles effecting controlling outcomes.
    The consequence is that there are many good-regulators in a system not only one. Reviewing that for the classic practical example of a car, that looks to be correct.
    ⟲ AK-1.5.4 Confusing cycles by contexts, abstractions to clear
    Information System (IS) and systems thinking a gap for improvements
    In pursuit of systems theories for describing and analyzing systems in organizations (researchgate: Twenty-Sixth European Conference on Information Systems (ECIS2018), Alter, Steven 2018)
    Goal: a path forward by which the IS discipline might pursue systems theories in order to understand IS in new ways, generate innovative and useful systems theories, and achieve more impact in the world. ... (5.1) WST is much less useful for analyzing an entire large enterprise, such as Toyota Motors or the British Government, whose thousands of participants perform thousands of activities that are not linked directly. .... The WSF (Work system framework) identifies and organizes by nine elements of even a basic understanding a work system’s form, function, and environment during a period when it is relatively stable.
    ... Work system life cycle model. The WSLC represents the iterative process by which work systems evolve over time through a combination of planned change (formal projects) and unplanned (emergent) change via adaptations and workarounds. ... Implementation refers to implementation in the organization, not implementation of algorithms on computers. A full iteration from one operation and maintenance phase to the next might be viewed as a transition from a previous version of the work system to a subsequent version.
    It is a not very hopeful description of the state of Information Systems where the association to systems theory is broken. Those nine elements could be connected to ZARF.
    The system flown in a practical lens for a system as a whole
    The operational value stream in a Pull and Push in all steps looks complex but is simple when understood. The duality and dichotomies in applying systems thinking is a change in perspective.
    A narrative in attempt escaping confusing anatomy and physiology details.

    Learning restroperpective

    AK-1.6 Learning systems maturity from 6x6 RFW's

    The perspective of what is seen is an uncertainty on his own. The choices by chosen scopes by the consumer, actor, stakeholder, is an unpredictability.
    There are learning points
    1. Systemic failures in systems by distractions do exist. Distractions that adjust the purpose behind understanding systems into avoiding adaption.
    2. Simple distractors are caused by wanting adaption but missing how to adapt those in the system.
    3. Using the intelligence cycle as a subsystem in the system.
    4. Out of the crisis using smart systems supporting the systems.
    The space for values, knowledge, structure, and tradition is limiting the scope. There is a exception in the mindset to the other components. The reflections in perspectives in systems are the good regulators at the journeys.
    ⟲ AK-1.6.1 Evaluating the pattern of four layers, the 3D model
    How the idea for the 3D model got started
    Thinking on devops, portfolio management, budgeting by information systems, the evolvement was:
    1. A partial understanding of value stream modelling abbreviated as VaSM to avoid confusion.
      It is about the operations context in functioning for the product/service in the full Pull Push cycle for the product/service.
      ⚠ Confusing and distracting: using the word products for components, the product/service it is not about isolated components.
      👁 An imaginary floorplan for the activities of the VaSM to visualize.
    2. Changing, shaping the VaSM is what development is about.
      It follows the same paths as the VaSM but the focus in not on the functioning but the functionality of the product/service. The context approach and mindset for involved people is very different to that of the operations.
      A full cycle is four aspects, a pattern that is popping up every time::
      • Gathering ideas, proposal for products/services (backlog),
      • Selecting & prioritizing from the backlog,
      • Realisation of what was demanded in building and verification.
      • Accepting the innovation, changes together with well documented specifications.
      👁 An imaginary floorplan for the activities of Development & operations connections to visualize.
    3. For the safety, cyber security, aspect it is not part of VaSM. The question where is does belong, brought it to actual realisations the instances by operations and the rules corporate ethos.
      This is where the viable system theory entered, abbreviated as ViSM to avoid confusion.
      A Secure Information Management Framework (SIMF)
      👁 Two imaginary floorplans for the instances by operations and the execution in command & control to visualize. These have unpredictable interactions by the universe.
      ⚠ Reviewing this I became aware the adaption for change as a whole (system-4 ViSM) and the ethos atmosphere (system-5 ViSM) are missing. There is no logical hierarchy between development, operations VaSM and the operational instances, they are acting independent although there are tight relationships.
      The classic four dualities, a pattern that is popping up every time:
      • Engineering - Machines, technology instances by operations
      • Administration - Processes value stream modelling - operations, development
      • Delivery- People execution in command & control
      • Supply - Structure adaption for change, ethos atmosphere
    4. Regulating, controlling flows is by a feed-back loops adapting for what is seen as problems to solve (system-2).
      This part is what gets much attention ins ViSM but is in its fundaments distracted by the hierarchical leadership control setting in human values.
    The steep learning path for understanding Zarf is simplified by following a similar path.
    VaSM, ViSM, SIMF perspectives in a 3D model
    Each of the floorplans got a fractal content for better understanding what it is about. Stakcing them vertical with the change by time increasing for wat is done in the know resulted in a 3D objects with 4 layers. This is about the anatomy and phusilogy of the system.
    The projection what is seen changing from floor-plans to side-views following the flow of VaSM at that floorplan for different perspectives in interactions. In a video (interactive cube) showing aside the stacked floorplans also the DevOps and PortfolioPlan relationships:
    The maturity of the four stacked floorplans
    Each cell at the four layers got indicative and an visualisation that are reflecting the words and concepts used informations systems.
    This should help in the understanding but changes for dedicated disciplines and changes by culture are to be expected. The result in practical cases should be the proof of maturity in what is chosen now.
    The maturity of applying Jabes the realisation using ZARF is part of the Jabes proposal. (I-Jabes ../design_meta/design_meta.html).
    A primary evaluation of the four stacked floorplans
    Stacking the floorplans is changing the perspectives in meaning. This is a start of neurology and sociology for the system.
    ⟲ AK-1.6.2 Systemic distractors in systems causing failures
    The unknown impact of balancing generic human values
    The four human values are simple but have no scale in good and bad and no measurements. The only value that has a scale for measrurement is an ammount by money at a moment in time.
    ➡ Human values ​by appearances: ➡ Values ​​of the human spirit. There are frictions with morality because morality is adding subjective value in bad vs good. Not having scales in bad/good and measuremnents is a disturbig question in morality, ethics. Experiments in this area by their nature questionable by ethics. Ignoring what those drivers have for effects is also questionable. Aside what history can learn about this, there some experiments done.
    🕳 Universe 25, John Calhoun famous mouse-behavior experiment, February 1970. He supplied for full safety in short-terms but nothing of the othervalues. The results did repeat many times in the same way by a full collapse of the community as system.
    🕳 Milgram experiment He supplied for safety for the teacher and offer honour in the results for actions. The results did repeat many times in the same way by a activities that were seen as not ethical, the opposite of the promise and the personal idea of actor.
    Distractors for failures in by hypes, buzzwords
    🕳 Acronyms the fast food gravity for uncertaintity. From a linkedin discussion the weirdness effects in the world of buzz.
    VUCA, BANI and RUPT: rapid, unpredictable, paradoxical, tangled, TUNA: turbulent, uncertain, novel, ambiguous. ViBRanT a cool acronym for marketing: ViBRanT = dynamic, lively, pulsating, swinging.
    Every few years a new alphabet soup is cooked but Complexity cannot be reduced to four letters. Those who want to understand should stop collecting acronyms and start studying complexity, thinking about it, and applying it in practice. Acronyms are fast food for thinking, quickly consumed but without nutritional value. Complexity is slow food; it requires time, attention, and discussion, but it truly satisfies.
    😲 This jumping to buzz word in branding, marketing is a market on his own.
    It is felt as personal honour, giving personal wealth by their activities but is not helping the system as a whole, but it is a hampering factor.
    🕳 Acronyms the fast food for process cycles Unfortunately, that's not the only thing that's happening with a multitude of acronyms like PDCA, DMAIC, ADKAR, OODA, ADDIE (Analyze - Design - Develop - Implement - Evaluate) , SCARF (Status - Certainty - Autonomy - Relatedness - Fairness), SOAR (Strengths - Opportunities - Aspirations - Results), AGIL (Adaptation - Goal attainment - Integration - Latency) and many more.
    The similarities in these frameworks: How is it possible to reduce those to something simple and universal?
    😲 The jumping to acronyms is food for branding buzzwords, creating a market on his own.
    The signals are certifications for a acronym, just name some: Safe, Itil, Togaf, (supplier)-certified, those for Safety cybersecurity.
    It is felt as personal honour, giving personal wealth by their activities but is not helping the system as a whole, but it is a hampering factor..
    A view of system thinking on systems
    There is a difference in thinking of systems a model of real situation and thinking on systems how it goes in systems thinking. This is a step into abstraction generalizing how systems behave. general system theory principles (Graham Berrisford 2025)
    Ludwig von Bertalanffy was an Austrian-born biologist and philosopher, widely recognized as the principal founder of General Systems Theory (GST). In the middle of the 20th century, Bertalanffy set out to develop a GST by identifying system concepts and principles shared by different sciences. For example, many feature the concept of a system in which components/parts interact - in some regular or repeatable way - to produce some emergent effect(s) of value or interest.
    Bear in mind that general system theorists look for where different sciences share the same concept, not just the same word. Words such as "information" and "organization" are used with different meanings by different systems thinkers.
    Soft Systems Theory SST is about “organizations”, meaning human institutions and businesses with a management structure and organized activities, in which humans act in defined roles. Soft systems thinkers' ideas (Graham Berrisford 2024)
    In the 1950s and 60s, some sociological thinkers became aware of two major developments in system science - general system theory and cybernetics - and wrestled with how to apply to system theory to what was called "management science" and might now be called "organization theory".
    Systems Thinking Foundations (Graham Berrisford 2025) An interesting disturbing statement at 45:38
    Has the time come to rescue system thinking from: 😱 It states the the distraction into organisation, is a root-cause that systems thinking is failing. Evaluating that statement is looks to be correct. To solve, rescue from: the hierarchical approach by the bad human value in power over others.
    ⟲ AK-1.6.3 Vision Wisdom Knowledge into knowledge management
    Knowlegde management, a fundament in Policies, policymakes.
    The question for documenting and sharing knowledge in a more practical way is generic. When creating and defining policies it is that what the basics are is about. Got a signal for looking at a research in that. It is case study by observing what and how it is done, there is no attempt to align that to any scientific theory. Communities of Practice Playbook CoP (EU JRC july 2020) that is associated with a short (100 pages) handbook Science Communities of Practice Playbook light
    (4.1 page 99) In this regard, knowledge assets are the fundamental elements of the community’s knowledge pool. They are the artefacts of all the tacit and explicit knowledge present within and around the community.
    For example, this knowledge can be unstructured and personal (e.g. individual expertise and skills) or structured and codified (e.g. guidelines and regulations). The more these assets are made explicit and structured, namely codified or made reliably accessible over time, the easier it is to share and engage members in using and adding to that knowledge and its various sources. By not making prior or implicit assumptions (or taking contextual knowledge for granted), but instead clearly stating any assumptions and contextual knowledge, it is easier for others to access this knowledge pool.
    Communities of practice operate wheel
    In a figure:
    see right side.

    The circle is promoted by 4 stages Drive, Steer, Build, Manage but each of those shows two artic acts with two others. The total of artifact is 3+3 for each.
    A misinterpretation is a focus only on those 16 artifacts at the outer ring.
    Knowledgemangement for a variety in purposes
    The "CoP Playbook" is a good case study for organizing the organisation using knowledge in Wisdom using Zarf and Jabes. Although nowhere Zachman is mentioned there is a remarkable similarity by 4 disciples Steer Build Manage Drive and 6 levels in indetifications (context). It is a complete cycle and not only that of engineering as in the Zachman EA.
    In that detailed case study to get done in floolowing chapters the attention points in observable practices, metrics and roles to get into those details.
    ⟲ AK-1.6.4 Smart systems, out of the information systems crisis
    a n the A primary evaluation of the four stacked floorplans
    The intelligence cycle is a revitalisation of DIKW making it usable for: The data gathering part and transforming that to information is getting support by machines, LLM. That change is an important change for knowledge management.
    A smart system, eg a LLM, helping in understanding and duplication in patterns
    Having the content in a website format hard work to create but easy access for a LLM. Not all is automagically processed, figures were additional uploaded for a analyses. That kind of analyses is far more demanding used selectivley.
    😉 The following pages are asked to be analysed in a LLM: The following figures are asked to be analysed: ✅ The result is a reinforced learning loop. Adjusting content and asking to updated the analyses by the LLM, resulting in adjusting the content. Using examples ad hints gave good responses for a desired outcome.
    A smart system, Jabes, supporting the knowledge work effectively
    Traditional reference models (like Zachman) lacked the depth to handle human values, systemic tensions, and adaptive governance.
    👉🏾 From these gaps, ZARF (part of Jabes) emerged—not as a patch, but as a reframe.
    The sections diagnose what was missing.
    The tradional gaps Tadional gaps Converage
    Human Motivation No modeling of safety, honor, fame, or trust ZARF_XPOS (Sociology)
    Legitimacy & Feedback No feedback-based trust or social adaptation ZARF_VIRU + ZARF_XPOS
    Uncertainty Handling No fuzzy logic or refutation criteria ZARF_VIRU (Neurology)
    Systemic Dualities No modeling of internal/external tensions ZARF_STRC + ZARF_INTR
    Governance Complexity No unified taxonomy of rules and constraints ZARF_VIRU
    Cultural Adaptation No support for evolving social norms ZARF_XPOS
    Time Sensitivity No phased transformation logic ZARF_STRC + ZARF_VIRU

    ✅ The approach of putting the content itself in 6*^6 reference frame consistently for knowledge work is the idea of Jabes. There are no applications-tools available for that. Making those available and adding standard meta reference frames is the innovative idea.
    👉🏾 Jabes is a frame work and a proposal for a technical tool. That is not a tool in the sense of some guidelines (Leadership toolbox, Scrum toolbox) but a technical practice in line with SAP for ERP DB2 for a DBMS to store data. That tool has the goals of:
    🔰 Contents Frame-ref ZarfTopo ZarfRegu SmartSystem ReLearn 🔰
      
    🚧  MDM2int SHouse VPossess Fame-int Honour-int Learn-I 🚧
      
    🎯 MDM2ext SLife VWealth Fame-ext Honour-ext Learn-@2 🎯

    AK-2 Details systems ZARF tactical 6x6 reference framework


    dual feeling

    AK-2.1 Enabling the internal understanding continuum

    Understanding systems and changing systems are several levels of abstraction. When changing systems the complexity on what should be done increases, it is about unpredictability non-linearity. The biggest problem with that: the human demand of anything should be predictable and linear. Challenges for change:
    1. Doing activities as always the same type of construction
    2. Improving the activities for achieving the same
    3. Improving type of construction although same purpose
    4. Creating new type of activities
    5. Creating new type of constructions
    ⟲ AK-2.1.1 Information semantics for contexts and abstractions
    business rules and data semantics
    Ronald G. Ross, a leading authority on business rules and data semantics, outlines six fundamental kinds of data descriptions in his work to help organizations achieve clarity and precision in business communication. These descriptions are essential for creating concept models that align data with business meaning.
    The Six Kinds of Data Descriptions:
    1. Distinguishing Things
      • Identifying what makes one concept or item different from another.
      • Helps clarify boundaries between similar terms or entities.
    2. Naming Things
      • Assigning consistent and meaningful names to concepts.
      • Crucial for shared understanding and avoiding ambiguity.
    3. Defining Things
      • Providing precise definitions that reflect business intent.
      • Goes beyond dictionary meanings to capture contextual relevance.
    4. Disambiguating Things
      • Resolving confusion when terms have multiple meanings.
      • Ensures that stakeholders interpret terms consistently.
    5. Classifications
      • Grouping things based on shared characteristics.
      • Supports structured thinking and data organization.
    6. Categorizations
      • Assigning things to categories based on business rules or logic.
      • Often used for decision-making, reporting, and compliance.
    These descriptions are part of Ross’s broader methodology for building concept models, which serve as blueprints for aligning business vocabulary with data structures. brsolutions
    Mapping of the identification, contexts, semantic
    In Zarf abstracted words are used but in the goal of defining better understandable meaning less abstracted words are required. In the approach of R.G.Ross there are specific words used.
    Mapping of the Zarf context axis to that of R.G.Ross with the intended delivery of a rules set for the meaning is a specific practical case. The context-axis is the flow fo achieving distinguised well understandble meaning.
    Semantic BRules description
    What: Defining Things Clarifies the essence of a concept—what it is.
    How: Categorizations Explains how things are grouped or used based on business logic.
    Where: Classifications Often relates to where things belong within a taxonomy or structure.
    Who: Naming Things Assigns identity—who or what is being referred to.
    When: (Not directly mapped) Ross’s framework doesn’t explicitly address temporal aspects, but Verb Concepts (from his broader model) can help express timing or events.
    Which: Distinguishing & Disambiguating Things Helps choose between alternatives and clarify which meaning applies.

    This still very abstract.
    This is a guidance for when you're building a concept model or trying to improve data quality, asking the right questions like: "What is this?", "Which type does it belong to?", or "How is it defined?",
    Advantages to do this are: There are some issues to mitigate in the mapping.: As example the goal for applying business rules for descriptions in the context of "Customer Interaction" Modeling:
    Semantic BRules description
    What: Defining Things Define what a “customer interaction” is—e.g., a touchpoint involving communication between a customer and service agent.
    How: Categorizations Categorize interactions by channel (email, phone, chat), intent (support, complaint, inquiry), or urgency.
    Where: Classifications Classify interactions by location—e.g., in-store, online, mobile app. This supports geo-tagging or regional analysis.
    Who: Naming Things Name the entities involved: customer, agent, system. Assign identifiers like customer ID, agent ID.
    When: (Not directly mapped) Timestamp the interaction. Use event modeling to track sequences—e.g., “Customer called at 10:15 AM, ticket resolved at 2:30 PM.”
    Which: Distinguishing & Disambiguating Things Things Distinguish between similar interactions—e.g., differentiate a complaint from a feedback.
    Disambiguate “support” when it could mean technical help or billing inquiry.

    Mapping of abstraction semantic for using BRules
    The abstraction-axis is how the meaning is perceived by another perspective in the involved tasks. The combination of both axis context and abstraction should cover a specific discipline.
    For three disciplines related to the IS (Information Systems) domain going into more details, the are:
    ViSM Semantic Stakeholder
    Role/Task    		 Devops
    decisions    		 Portfolio
    budget
    system-1 Context Role Decision node Initiative
    system-3 Concept Decisions Trigger / Event Budget Item
    system-4 System Logic Influence Agent / Actor Resource
    system-5 Technology Engagement Outcome / impact Constraint
    system-2 Components Feedback Feedback loop Outcome
    universe Instance Legitimacy Governance Scenarios

    Next Steps
    (LLM:)
    Build modern01

    AK-2.2 In purpose of creating a information system: how to start

    ⟲ AK-2.2.1 Context: Safety a functional requirement topic
    The playbook was created to enhance collaboration and knowledge sharing within the European Commission through communities of practice. ​ Key success conditions include shared vision, participation, trust, and inclusive communication. User personas represent groups of users based on empirical research, focusing on their goals and behaviors rather than demographics. Personas should be specific and used for ideation within a defined scope.
    Propose processes, tools, and methods that align with governance to meet identified needs.
    Develop an operational model that addresses the needs of the majority while employing the KISS principle (Keep, Improve, Start, Stop).
    Science Communities of Practice Playbook light (EU JRC july 2020)
    You should approach the Communities of Practice Success Wheel by considering it as a circular journey–you can start anywhere, but eventually you will travel through all of the domains, as they are interwoven and interdependent. We advise you to start with vision, but you can also chose to start where you feel you are struggling most in your community life at the moment.
    Using
    Mapping of the (chapter 3.1.4) there are four topics grouped by Drive, Steer, Buid, manage and by "senior and middle management", "core group", "all members", "community manager" by triplets. The diagonal serving Ideate & Asses in Supply-Drive:
    Semantic Semantic Short description Long description
    Which: Purpose What demand or need triggered its creation? Vision: What is the challenge you want to address / the problem to solve?
    What is your long-term goal?
    When: Performance What impact is visible to stakeholders? Objectives: What is your strategy to reach your community vision?
    Define SMART steps, behaviours and rituals.
    Who: People Who requests or consumes outcomes? Stakeholder mapping: Define your membership and the surrounding community ecosystem.
    Who are the actors involved in/impacted by the community?
    What: Practice What external practices influence the CoP? Risk-free environment: What are key elements to building trust and guaranteeing a safe place?
    How: Process How are requests and inputs processed? Governance: How do you work together, take decisions and act on them?
    List working practices and processes fitting the community needs, purpose, and values.
    Where: Platform What channels connect external demand? Community purpose: What is the community's raison d'être in support of the vision?

    The diagonal serving Plan & Enable in Administration-Steer:
    Semantic Semantic Short description Long description
    Who: Purpose Who sets the strategic direction? Core group: How do you get your core group to steer the community?
    When: Performance What governance indicators are used? Convening: What kind of convening opportunities/events fit with your community in general?
    Which: People Who governs and sponsors? Investment and sponsorship: What support do you need from management?
    How do you get them involved and create participation opportunities?
    Where: Practice What norms and rules guide behavior? Leadership: How will you ensure strong leadership participation?
    How: Process How are decisions made and roles assigned? Communication, connection and conversation: What convening opportunities will you design to create and encourage connections, conversations and communication?
    What: Platform What policies and permissions steer access? Boundary-spanning: How do you regularly feed your community with external expertise and promote access to other networks?

    The diagonal serving Demand & Backend in Engineering-Build:
    Semantic Semantic Short description Long description
    Which: Purpose What is the CoP building? Collaboration/cooperation: How do you make members collaborate and/or cooperate to enrich the common practice and produce knowledge assets/qualitative deliverables?
    When: Performance What metrics track capability? Co-creation: What content needs to be curated/synthesised/co-created and what methods will you use to succeed in this?
    Who: People Who contributes expertise? Coordination: How do you coordinate members' work towards delivering on the objectives agreed?
    What: Practice What tools and methods are used? Community management: What role and tasks will the community manager perform?
    How: Process How is knowledge created? In real life and online: How will you combine and ensure the flow between real-life and online, asynchronous and synchronous community interactions?
    Where: Platform What infrastructure supports building? Facilitation: What facilitation methods do you need to get the best out of the community's dynamic social processes?

    The diagonal serving Frontend & Delivery in Delivery-Manage:
    Semantic Semantic Short description Long description
    Who: Purpose What value is delivered to members? User experience: How do you ensure a user-centric experience for the tasks (you want) members (want) to do in the community?
    When: Performance What feedback loops exist for members? Measurement: What have you achieved?
    What can you learn from those measurements and how will you address the challenges/obstacles?
    Which: People Who facilitates and engages? Experience design: What are the community's personas and their user requirements, as well as the pain points to address?
    Where: Practice What rituals and routines sustain engagement? Support: What processes and content do you need to put in place to provide support?
    How: Process How is participation managed? Vitality: What habits and behavioursshould you observe and encourage?
    What: Platform What interfaces support member interaction? Results: How do you measure the key results in delivering on the community objectives? How will you capture impact stories?

    Measurement: What have you achieved?
    What can you learn from those measurements and how will you address the challenges/obstacles?
    ⟲ AK-2.2.2 Safety in ordered internal states axis
    Rows (perspectives / layers) Here’s one possible mapping: ZARF Row (Metier) CoP Alignment Planner (Scope / Motivation) Playbook: Drive (vision, attractiveness, transparency, awareness). Owner (Business / Governance) Playbook: Steer (shared goals, sponsorship, stakeholder engagement). Designer (System Model) Playbook: Build (objectives, routines, trust, KM strategies). Builder (Technology / Process) Playbook: Manage (onboarding, facilitation, structures, responsiveness). Sub-contractor (Detailed Specs) Playbook: Community Manager role (tools, templates, daily moderation). Functioning System (Reality) The live community of practice itself (members engaging, knowledge circulating).
    ⟲ AK-2.2.3 Safety internal goals in transfomations
    ⟲ AK-2.2.4 Safety negative results by assumptions
    ZARF Crisis Response Model Public Trust Recovery Across ZARF Layers & Time Slices 🧭 Scenario: Digital Service Outage During Benefits Disbursement Layer Now (Immediate Response) Near Future (Stabilization) Far Future (Resilience & Renewal) STRC (Anatomy) Identify affected cells: What–Component, Who–Instance, When–Technology Redesign How–Logic and Where–Technology to prevent recurrence Reframe Which–Concept to include resilience as a design goal INTR (Physiology) Trigger horizontal updates: Who–Instance ↔ When–Component Consolidate 2×2: What–Technology + How–Technology → “Recovery Engine” Consolidate 3×3: Which–Concept, Who–Concept, When–Concept → “Trust Cluster” VIRU (Neurology) Activate exception path: rollback What–Component, notify Who–Instance Orchestrate composite recovery via System-2 cell, log all actions Embed feedback loops into How–Logic and Which–Context XPOS (Sociology) Reassert identity: “Citizen-first, transparent, accountable” Adapt messaging and behavior to cultural expectations, engage stakeholders Publish postmortem, launch listening sessions, reinforce legitimacy 🔍 Layer Interactions in Crisis STRC maps the structural impact and time horizon of the failure. INTR governs how cells interact to contain and correct the issue. VIRU ensures governance, logs actions, and orchestrates recovery. XPOS manages the social narrative, cultural fit, and trust restoration.
    Build modern01

    AK-2.3 Value streams in Systems & components on their own

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-2.3.1 About Frameworks for architecture
    What are Frameworks?
    ⟲ AK-2.2.1 Context: Safety a functional requirement topic
    information asset classification (K van Wersch 2025) ISO and NIST have shaped the way the world thinks about information security. Their standards are widely used and for good reason: they provide structure, consistency, and a shared vocabulary. The methodology begins with things you can inventory (files, systems, databases, devices) and only afterwards connects them to business purpose or impact. And that's exactly where practice goes astray.
    A context-first approach would begin with: What gets lost in today's "asset-first" framing is context and meaning.
    Here's how I believe it should flow:
    1. Identify the context where information lives and flows (enterprise architects).
    2. Understand meaning and value how information gains purpose (business analysts).
    3. Assign accountability - link responsible people to that context.
    4. Then apply information security - aligned with steps 1-3.
    Until this shift is made explicit, "information asset classification" will keep pulling us into an object-first mindset and security will remain more of a compliance exercise than a true business enabler.
    Roles, Tasks, Methodologies for a safe working environment in the system.
    Example Scenario Let’s say How–Component is being updated to reflect a new automation tool: Governance rules from How–Concept require ISO 27001 compliance The new tool lacks encryption, violating the inherited constraint ZARF blocks the transformation, logs the violation, and alerts the compliance officer A feedback loop is triggered to review whether the policy needs adaptation or the tool must be replaced Transformation: How–Component ┌─────────────────────────────┐ │ Inherited Constraints: │ │ • ISO 27001 compliance │ │ • Role-based access control │ │ │ │ Audit Log: │ │ • Actor: DevOps Lead │ │ • Timestamp: 2025-09-16 │ │ • Status: Blocked │ │ • Reason: Encryption missing│ │ │ │ Feedback Triggered: │ │ • Policy review initiated │ └─────────────────────────────┘ Example Scenario Let’s say a new product launch affects: What–Concept (strategic intent) How–Technology (platform selection) Who–Instance (staffing and roles) When–Component (deployment schedule) ZARF decomposes this into atomic moves: Each move is sequenced and assigned to a team A System-2 cell coordinates across flows All moves occur in the “Near Future” slice A rollback path is defined in case How–Technology fails compliance 🧩 Visual Cue (Conceptual) Code Composite Transformation: Product Launch ┌─────────────────────────────┐ │ Sequence: │ │ 1. What–Concept │ │ 2. How–Technology │ │ 3. Who–Instance │ │ 4. When–Component │ │ │ │ Coordination: │ │ • System-2 Cell: PL-Coordinator │ │ • Time Slice: Near Future │ │ • Handoff: to Delivery team │ │ │ │ Audit Log: │ │ • Actor: Strategy Lead │ │ • Status: In Progress │ └─────────────────────────────┘ Example Scenario Let’s say Which–Component is being updated to reflect a new supplier module: The module fails compliance checks during How–Technology validation Exception channel triggers rollback of Which–Component to previous version Compensation path updates Who–Instance to revert staffing assignments All changes are logged, and a feedback loop is triggered to review supplier criteria 🧩 Visual Cue (Conceptual) Code Transformation: Which–Component ┌─────────────────────────────┐ │ Exception Trigger: │ │ • Compliance failure │ │ │ │ Compensation Path: │ │ • Rollback to prior version │ │ • Notify Who–Instance │ │ │ │ Time Slice: Near Future │ │ │ │ Audit Log: │ │ • Actor: Procurement Lead │ │ • Status: Reverted │ └─────────────────────────────┘
    ⟲ AK-2.3.2 The ordered internal states axis
    States in the internal purpose line: culture
    An example for leaders applying the lean mindset: Excellence Isn't an Accident (LEI James Morgan 2025)
    If you want to create world class products, first you must develop world-class people. That isn't an accident. It is the result of a culture of discipline, craftsmanship, and the pursuit of mastery at every level of the organization.
    1. What 👁 Putting People First: Organizing your development system and using lean practices to support people to reach their full potential and perform their best sets up your organization to develop great products and services your customers will love.
    2. How 👁 Understanding before Executing: Taking the time to understand your customers and their context while exploring and experimenting to develop knowledge helps you discover better solutions that meet your customers needs.
    3. Where 👁 Developing Products Is a Team Sport: Leveraging a deliberate process and supporting practices to engage team members across the enterprise from initial ideas to delivery ensures that you maximize value creation.
    4. Who 👁 Synchronizing Workflows: Organizing and managing the work concurrently to maximize the utility of incomplete yet stable data enables you to achieve flow across the enterprise and reduce time to market.
    5. When 👁 Building in Learning and Knowledge reuse: Creating a development system that encourages rapid learning, reuses existing knowledge, and captures new knowledge to make it easier to use in the future helps you build a long-term competitive advantage.
    6. Which 👁 Designing the Value Stream: Making trade-offs and decisions throughout the development cycle through a lens of what best supports the success of the future delivery value stream will improve its operational performance.
    The LPPD Guiding Principles provide a holistic framework for effective and efficient product and service development, enabling you to achieve your development goals.
    States in the internal purpose line culture
    An example for leaders what the should do by actvities. 18 practices for ceo's (Alex Nesbitt 2025 reference to McKinsey)
    What are Frameworks?
    1. What ➡External Stakeholders Centre on the long term "why" (purpose)
    2. How ➡Board engagement Help directors, help the business
    3. Where ➡Team & processes Put dynamics ahead of mechanics
    4. Who ➡Personal Norms Do what you can do
    5. When ➡Culture & organisation Manage both health and performance
    6. Which ➡Corporate strategy Focus on beating the odds.
    ⟲ AK-2.3.3 Positive internal goals in transformations
    Positive actions in transformations
    18 practices for ceo's (Alex Nesbitt 2025 reference to McKinsey)
    ⟲ AK-2.3.4 Negative results by assumptions
    Negative actions in transformations
    18 practices for ceo's (Alex Nesbitt 2025 reference to McKinsey)

    There is a natural variation over all components by cells and transformations interactions between the cells.
    What are Frameworks?
    From 4M to 7M; from Chaos to Control (Alper Ozel 2025
    Negative actions in transformations

    There is a natural variation over all components by cells and transformations interactions between the cells.
    Search in steps going up

    AK-2.4 Choices by systems for capabilities in uncertainties

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-2.4.1 About Frameworks for enterprise architecture
    Flow in of Strategic Thinking
    strategic-thinking (Andre Constable 2025) Strategic thinking is the cornerstone of effective leadership, sound decision-making, and long-term organisational success. It goes beyond the confines of traditional planning, enabling leaders to make integrated, courageous choices in the face of uncertainty. In today's complex and fast-changing world, the ability to think strategically has become essential for survival and sustained performance.
    1. Future Orientation Strategic thinkers do not merely solve today's problems, they look ahead.
      They explore emerging trends, anticipate disruptions, and use structured tools such as scenario planning, PESTLE analysis, and competitive landscape assessments to guide long-term decisions.
    2. Systems ThinkingOrganisations are part of broader ecosystems.
      Strategic thinkers recognise interdependencies across functions, partners, industries, and geographies. This holistic view is crucial for addressing systemic challenges and capitalising on cross-sector opportunities.
    3. Hypothesis-Driven Strategy Effective strategies are built on assumptions.
      Strategic thinkers make these assumptions explicit and test them rigorously. Whether through war-gaming, pilot projects, or feedback loops, they continuously refine their approach based on evidence.
    4. Clarity and FocusClarity in purpose, values, and direction is a hallmark of strategic thinking.
      These elements act as guardrails, shaping what the organisation will and will not do. Organisations that define their identity clearly are more likely to make coherent, disciplined choices.
    Core Dimensions of Strategic Thinking
    Strategic thinking must be embedded at every level of the organisation, not confined to the C-suite. This requires structured yet flexible processes that promote:
    1. What ➡Strategic Development Organisations must start with a clear mission and vision, conduct robust internal and external analysis, and define strategic shifts that reflect changing realities.
    2. How ➡Strategic Translation High-level thinking must be translated into actionable strategies. Tools such as strategy maps and Balanced Scorecards help articulate cause-and-effect relationships and align teams around common goals.
    3. Where ➡Organisational Alignment Strategic coherence across business units is essential. Each team must understand its role in the broader strategy and be empowered to adapt that strategy to its specific context.
    4. Who ➡Operational Planning Daily operations should reflect strategic priorities. Leaders must ensure that budgets, initiatives, and KPIs are aligned with long-term objectives, not just short-term performance targets.
    5. When ➡Monitoring and Learning Strategy should be treated as a living process. Organisations must build feedback loops, review performance data, and be prepared to adjust their approach based on new information or shifts in the environment.
    6. Which ➡Strategic Agility In an era of rapid change, agility is key. Strategic thinking equips organisations to anticipate multiple futures and adjust course when necessary. Practices like contingency planning and strategic foresight enable resilience.
    The why of Strategic Thinking
    Strategic Thinking vs. Strategic Planning While the two concepts are often used interchangeably, they are fundamentally different. Planning tends to be linear and predictable. Strategic thinking embraces complexity and uncertainty. One is about execution; the other is about advantage.
    "Having a good strategy with no execution is a big disappointment. But having no strategic thinking at all is a failure in leadership."
    ⟲ AK-2.4.2 About Frameworks for enterprise architecture
    What are Frameworks?
    PEST analysis was developed in 1967 by Francis Aguilar as an environmental scanning framework for businesses to understand the external conditions and relations of a business in order to assist managers in strategic planning. t has also been termed ETPS and other letter variants natanalysis. A PESTLE analysis is a strategic management framework used to identify and analyze the key external macro-environmental factors—Political, Economic, Social, Technological, Legal, and Environmental—that can impact an organization. By examining these external forces, businesses can understand their broader operating environment, identify potential opportunities and threats, and make more informed strategic decisions to adapt and improve their performance.
    Advantages: Disadvantages: The Six Factors of a PESTLE Analysis
    1. What ➡Social: This refers to societal trends, cultural factors, and demographic shifts, including customer beliefs, customs, and lifestyle changes.
    2. How ➡Technological: This factor focuses on technological advancements and innovation, such as new internet usage habits, automation, and research and development.
    3. Where ➡Political: This factor examines government policies, stability, and regulations, such as tax policies, trade restrictions, and political climate.
    4. Who ➡Legal: This considers the impact of laws and legislation, including employment laws, consumer protection laws, and industry-specific regulations.
    5. When ➡Economic: This includes factors like economic growth or decline, interest rates, exchange rates, inflation, and unemployment rates.
    6. Which ➡Environmental: This encompasses ecological factors and environmental concerns, like climate change, natural resource availability, and the increasing demand for sustainable business practices.
    Positive actions in transformations
    How to Conduct a PESTLE Analysis
    Negative actions in transformations

    There is a natural variation over all components by cells and transformations interactions between the cells.
    Build modern01

    AK-2.5 Resource alignments for the system as a whole

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-2.5.1 About Frameworks for architecture
    What are Frameworks?
    Example TIS, part of Theory of constraints
    five-state-model (Kevin Kohls 2025) In the Throughput Improvement System (TIS), we use a simple but powerful lens: every workstation can only be in five states: Running, Down, Blocked, Starved, or Off. These states can be programmed into a PLC or tracked with phone video. Each time a part is made, the counter increments and the Run cycle continues. ... With TIS, we have sonar. We can see constraints before they hit and avoiding problems is far cheaper than experiencing them.
    Why it matters is for metrics: Optimizing just a machine component in the flow doesn't improve automagically the system as a whole. Understanding the interaction of the component in the system is a pre requisite for choosing where efforts will have positive seen effects.
    Flow functionality in ordered internal states horizontal axis:
    1. What ➡ Off Unclear by unknown service planning
    2. How ➡ (On) in order
    3. Where ➡ (On) Down Look for the problem to solve
    4. Who ➡ (On) Blocked Somebody is expected to react for a solution by decisions.
    5. When ➡ (On) in disorder Needing maintenance, could be decided: temporary accepted.
    6. Which ➡ (On) Starved Unclear by unknown flow planning
    Example Smed - Quick Changeover
    Quick Changeover Basics - SMED (C.Roser 2014) One popular approach to battle waste is to streamline changeovers. Changing machines from one set-up to another is often a time-consuming exercise. Hence, in lean manufacturing, reducing changeover times is a well-known method for improving efficiency. Also known as quick changeover or single minute exchange of die (SMED). ... As with any improvement project, the first question you should ask yourself is, "Is this my biggest problem right now?". As always, you should have an overview of the problems you are facing and have them prioritized.
    Flow functionality in ordered internal states horizontal axis:
    1. What ➡ Measure: Changeover Times
    2. How ➡Classify: Identify Internal and External Elements
    3. Where ➡Path Reorder: Move As Many Elements as possible to External
    4. Who ➡Path Overall: Shorten Elements External and internal.
      Depedencies for the change over at the workers
    5. When ➡Path Stopped: Shorten Internal Elements
      Depedencies in the change over for the process
    6. Which ➡Capability: Standardize and Maintain New Procedure
    Because I see the axis as ordered but the activities in nonlinearity based on existing knowledge, it makes more sense to focus on the worker interest in that ordering.
    ⟲ AK-2.1.2 Flow optimizing for positive improvements
    Example TIS Optimizing by avoiding wat is seen as unwanted
    By projecting an improved MTBS or MTTR and entering those into simulation, we unlock one of the most valuable insights of the Throughput Improvement Process (TIP): the next bottleneck.
    With clear states, we stop debating and start improving.
    Added is the state "Off", but I'm missing the state the machine is running but creating too many defects.
    A simulation is a indication the whole system is evaluated using a model of the system. The goal of the simulations is finding what is holding up in the speed of flow system.
    Focus on machine states:
    1. Off ➡Unknown service Machine is turned off; no data collected. 🎭
    2. (On) in order ➡In service Running Possible actively making parts
    3. (On) Down ➡Failing service Something is wrong; the machine should be running but isn't.
    4. (On) Blocked ➡Failing service Nowhere to put the next part.
    5. (On) in disorder ➡Failing service Too many defects are created by the machine.
    6. (On) Starved ➡Unknown service No parts available to work on. 🎭
    👁 💡 These "failing service" states are simply to represent in status flags. For alerts at a higher level only a summary alert signal is sufficient.
    👁 💡 Measuring the quality seeing defects in created products needs an additional measurement that is possible not part of the machine.
    👁 ➡ The "unknown service" states are needing additional information before it is clear it is about an alert or normal wanted condition. When all planned products are created there is no reason to create more of those. Starvation is in that case planned.
    Example Smed - Quick Changeover
    Before you start measuring, you should make sure that you get the entire process measured, not just part of it. The changeover itself starts after the last part produced at full speed and ends with the first part produced at full speed. It is easy to overlook, for example, times where the machine is running already but the operator still adjusts the settings and hence the machine is slower than planned.
    Whenever you measure times on the shop floor, or even take video, you should inform the workers and their representatives and get their agreement. ... If the workers disagree with you measuring them, they can easily mess up your measurements by working extra slow. In many cases, you wouldn't notice if they added additional steps to the procedure.
    1. Measure: ➡ a list of steps including an average time to do those
    2. Classify: ➡ what can be done without stopping and what needs a stopped machine>
    3. Path Reorder: ➡ to minimize the stopped time by ordering
    4. Path Overall: ➡ to improve by minimizing the workers activities.
    5. Path Stopped: ➡ the goal in improving the flow of the process.
    6. Capability: ➡ Knowledge assurement, specifying, documenting, training.
    The last step is the most difficult one and the most frequently forgotten one. It is not enough to do a changeover quickly once; you have to do it quickly every time. So you need to fix the new standard, document it, train all relevant workers in the new standard, and do a process confirmation. Any standard not maintained that way will be soon lost.
    ⟲ AK-2.1.3 Flow positive internal goals in transformations
    s?
    Positive actions in transformations
    ⟲ AK-2.1.4 Flow negative internal results by assumptions
    ks?
    Negative actions in transformations

    There is a natural variation over all components by cells and transformations interactions between the cells.
    Learning restroperpective

    AK-2.6 Learning maturity from details at systems internals

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-2.6.1 Unification by a visual in diagonals vs the quadrant
    Goals in states and flows a selection
    The Holistic Approach: Combining BPM with Value and Performance Management, Enterprise Architecture, Governance, and SOA (M von Rosing, R Eijpe, C. Laar, A Rosneberg, S Kuhlmann - december 2010). Over the past few years, many initiatives have come to life for SAP customers: Initiatives from service-oriented architecture (SOA), business process management (BPM), value management (VM), enterprise architecture (EA), and with this not only the technology architecture and information architecture, but also the business architecture.
    ... The key distinction for BPM as a discipline is added focus on flexible and dynamic process design and process orchestration and automation through IT enablement. In addition to reduced costs through continued improve- ment and automation, BPM also provides the foundation for converged and agile business and IT responsiveness and is the key to applying the principles discussed in this chapter. Figure 4.8 shows these principles from the process management lifecycle perspective in integrating business modeling, process modeling, gover- nance, ownership, business value, and business performance.
    SAP Holistic BPMSOA
    The orientation in the figure is not what I am used to but having done the orientation adjustment more often this figure got my attention. It is chaotic disordered at the outer part but nicely ordered in the fractals in the centre.
    Goals in states and flows a selection
    For states:
    Organization Strategy Technology Process
    Responsive Focused Robust Flexible
    Technology governance Process Governance Technology performance Process performance

    For transformations:
    Run / Execute -Monitor Analyse Design Implement
    Business Performance Business governance Information architecture Information engineering
    Values fiance & ethical measurements System components Platform tools

    ⟲ AK-2.6.2 Unification by visuals quadrant flows
    The goal and the flow stability
    These are more advanced and tailored to complex organizational and ICT systems, but they still follow the same principle: structured progression through stages of From SEI (software engineering institute) Barriers to see:
    ⟲ AK-2.6.2 Unification by a visual in diagonals vs the quadrant
    Zarf Relevant concepts in considerations
    Risks, Gaps & Ambiguities Complexity & overhead The model is ambitious and multi-dimensional. Without careful scoping, it can become overwhelming, hard to apply in real projects. Ambiguity & lack of concrete rules While many principles are presented, some rules (how to move diagonally, recursion boundaries, orchestration) are expressed more aspirationally than operationally. Steep learning curve It requires familiarity with systems theory, lean, Zachman, recursion, fractals. Teams without exposure may struggle. Risk of over-generalization In trying to cover “all systems,” it may lose specificity for particular domains—details may have to be imposed externally. Value integration is subtle Embedding human motivations (safety, fame, etc.) is powerful, but translating that into system constraints or design decisions may be tricky or subjective. Which vs Why trade-off The replacement of “Why” with “Which” is philosophically interesting, but it may de-emphasize deeper purpose or normative grounding in favor of decision logic. Some domains still need a sense of why to anchor direction. Practical application / tooling missing The page is conceptual; applying it in real community, organizational or software design may require additional templates, governance, tooling.
    ⟲ AK-2.6.3 Learning from AI understanding complex frameworks
    Zarf Relevant concepts in considerations
    Example Application Let’s say the “Which–Technology” cell (design choices for tech stack) is recursively explored across multiple platforms. Once the viable options are narrowed to a few with clear trade-offs, further recursion (e.g., down to chipset specs) may be unnecessary. At this point: Dashboard Templates by Role:
    Stakeholder Role Ordering Used             Dashboard Focus Areas
    Engineer /
    Architect     		What → How → Where
    → Who → When → Which     		Technical structure, process flow, implementation choices
    Administrator /
    Regulator     		Which → When → Who
    → Where → How → What     		Governance, timing, accountability, compliance
    Citizen /
    End User     		Which → When → Who
    → What → How → Where     		Identity, service delivery, trust, usability
    Vendor /
    Supplier     		Where → How → What
    → Which → When → Who     		Location, product, integration, timing, stakeholder roles
    Planner /
    Strategist     		Who → When → Which
    → Where → How → What     		Strategic roles, future planning, decision geography

    The sense in variations for the ordering axis 6w1h
    That isn’t just listing variations of the 6W1H axis—it’s revealing how different disciplines, perspectives, and system roles reorder the same interrogatives to reflect their priorities, logic, and worldview. This is a fractal insight: the same building blocks (What, How, Where, Who, When, Which) are reused, but their ordering changes depending on context. Why This Is Powerful: Those variations turn the 6×6 reference frame into a multi-perspective, recursive, decision-aware system. It’s not just a matrix—it’s a lens that adapts to the viewer.
    Perspective Focus - most visible
    Engineering Technical structure, process, and control
    Administration Governance, timing, accountability
    Internal Power, Trading Roles, timing, decision-making
    External Power, Trading Location, function, product, stakeholder
    Technology/Machines Decision logic, timing, execution
    Operations/Processes Role-driven flow, spatial layout, repetition
    People/Service Identity, timing, responsibility, delivery
    Planning/Structure Strategic roles, timing, decision geography

    Imagine the ZARF grid as a lens. Each ordering tilts the lens, changing what’s in focus: For the Why to start there are the How's and When's that matters most.
    ⟲ AK-2.6.4 Consolidation at Frameworks for architecture
    The goal and knowledge stability
    On this site references to frameworks like JABES, JABSA, and SIMF, which extend traditional cycles with deeper abstraction layers. These integrate: These are more advanced and tailored to complex organizational and ICT systems, but they still follow the same principle: structured progression through stages of
    The goal and knowledge stability
    The operations dashboard (I.Carillo 2025 - Toyoada) Reading Sakichi Toyoda's 1924 loom patent, I found something nobody talks about. Here's the story: Poka-Yoke is about freeing humans from mindless watching so they can apply judgment where it matters. Fast forward 100 years.We have AI, IoT, and predictive analytics. Yet I still see:
    The goal and knowledge stability
    What Most Companies Miss about the Role of Chief Engineers (LEI 2025 J.Morgan, J.Liker) The organizational focus needs to be on making the horizontal value streams, the product programs and therefore the CE successful. This priority should be reflected in your operating system and your leadership behaviors across the organization:
    1. Allow CEs to focus on their products and do not overburden them with major people-development responsibilities. However, always solicit their input on the people that contribute to their program.
    2. Establish your most important team metrics based on product success.
    3. Build CE-centric tools and methods into your development process. (The concept paper, kickoff meetings, and CE reviews are examples.)
    4. Create CE-centric senior leader forums within your operating system to promote a product-first focus.
    5. Groom some of your best people for the CE role and provide appropriate recognition.
      
    🎯 MDM2ext SLife VWealth Fame-ext Honour-ext Learn-@2 🎯
      
    🚧  MDM2int SHouse VPossess Fame-int Honour-int Learn-I 🚧
      
    🔰 Contents Frame-ref ZarfTopo ZarfRegu SmartSystem ReLearn 🔰

    AK-3 Details systems ZARF practical 6x6 reference framework


    dual feeling

    AK-3.1 Enabling the practical undertstanding continuum

    Understanding systems and changing systems are several levels of abstraction. When changing systems the complexity on what should be done increases, it is about unpredictability non-linearity. The biggest problem with that: the human demand of anything should be predictable and linear. Challenges for change:
    1. Doing activities as always the same type of construction
    2. Improving the activities for achieving the same
    3. Improving type of construction although same purpose
    4. Creating new type of activities
    5. Creating new type of constructions
    ⟲ AK-3.1.1 Explanation model example: Adaptive Transit Planning
    Scenario Adaptive Transit Planning
    🔰 An explanation model serves in better understanding of abstract concepts. It should be well known for understanding, not too simmple and not too complex. The choice is using the public transport system, transit of people and some chosen problem.
    The chosen problem at Adaptive Transit Planning: 🎭 This explanation model wille be used for the more complex and abstracted scenarios: For these there is a translations mapping for the Semantics needed:
    ViSM Semantic Information FLow Platform Information System
    system-1 Context Platform Component
    system-3 Concept Decision Node
    system-4 System Logic Stakeholder Role
    system-5 Technology Resource
    system-2 Components Feedback Loop
    system-1 Instance Governance Rule

    Intelligence for Adaptive Transit Planning
    🚧 The proposed intelligence result:
    eDIKWv Abstract Action / activity
    Environment Instance Sensors collect passenger counts, GPS positions, and ticket scans
    Data Components Data is structured into heatmaps, route congestion graphs
    Information Technology Analysts identify patterns: peak congestion zones, bottlenecks
    Knowledge System Logic Predictive models suggest rerouting and dynamic scheduling
    Wisdom Concept Strategic decision: deploy extra buses, notify public, adjust pricing
    Vision Context Routes updated, drivers dispatched, public alerts sent

    🚧 Feedback & Recursion: 🚧 Time-Sliced Contexts:
    Roles and flows for Adaptive Transit Planning
    ⚠ Although this would be a simple model example there are surprises. When these contents was created the compononts abstractions got missing. Raising the question for undertanding why it was missing with a hint for what it could be, the problem for a role became clear, an alternative being created: Transit Orchestrator.
    For roles in the components there is an ambiguity: 🚧 Engineering - constraints for the how, role mapping across layers:
    Role Abstract Action / activity
    Strategic Planner
    Operations Coordinator     		Context Defines long-term mobility goals, equity, and sustainability vision
    Governance Lead Concept Aligns stakeholder mandates, policy frameworks, and legitimacy logic
    Insight Strategist System Logic Synthesizes predictive models, scenario planning, and decision paths
    Data Analyst Technology Builds routing algorithms, congestion forecasts, and telemetry logic
    Transit Orchestrator Components Configures dispatch tools, assigns vehicles, calibrates driver interfaces
    Bus Driver / Sensor Network Instance Executes routes, collects real-time data, and responds to conditions

    🚧 How the components in the system are expected to work as a whole:
    Flow Contextual Lens Transit Planning role
    Engineering SDLC, route optimization, sensor logic Designing adaptive schedules and routing algorithms
    Administration Governance, public trust, cultural fit Ensuring legitimacy, fairness, and stakeholder alignment
    Delivery Service execution, customer experience Managing real-time operations and passenger flows
    Supply Resource allocation, vendor coordination Aligning buses, drivers, and infrastructure

    Fractals for details getting to work instructions in Adaptive Transit Planning
    ⌛ ⏳What is next, Visual Implications.
    (LLM:) This dashboard can be rendered as a vertical swimlane diagram:
    Would you like to simulate a breakdown scenario—say, when the Insight Strategist misreads demand—and trace how the system recovers through ZARF_VIRU_04? We could model that next.
    Adaptive Transit Planning 6*6 Matrix: Semantic Mapping
    Questions that help structure stakeholder understanding across context layers & abstraction layers.
    ❶ Alignment by What en How:
    What (define) How (Categorize)
    Context What is the scope in mobility equity, urban sustainability? How is the Strategic transport policy defined for mobility?
    Concept What are the intended service coverages, accessibility goals? How is Adaptive routing strategy structured?
    System Logic What are the congestion thresholds, rerouting logic? How are Optimization heuristics, feedback loops strcutured?
    Technology What is there possible in Routing algorithms, telemetry dashboards? How is a Scheduling engine, load balancing, shaped - measured?
    Components What information is usefull by Ticket scanners, sensors? How are Vehicle specs, driver protocols giving constraints?
    Instance What information to collect in Passenger counts, GPS logs? How are Bus movements, stop timing impacting dynamics?

    ❷ Alignment by Where en Who:
    Where (Classify) Who (Name)
    Context Where are the issues: Urban geography, population density? Who Governance structure, public mandates?
    Concept Where does the Service area definitions apply? Who have what Stakeholder roles (citizen, operator)?
    System Logic Where does Zone prioritization, route clustering have impact? Who has what role in an Accountability matrix, escalation logic?
    Technology Where is GIS mapping, zone definitions to be found? Who has what access (Role-based), and act in escalation paths?
    Components Where is an Infrastructure layout to be found? Who defines Role assignments, shift plans?
    Instance WHere are transport stops (Bus Metro Train), stations located? Who assings Drivers, dispatchers?

    ❸ Alignment by When en Which:
    When (Time) Which (Distinguish)
    Context When: by Strategic timeframes (Now, Near, Far Future)? Which strategic option to select, legitimacy validated?
    Concept When: by the Planning horizons (daily, weekly)? Which Scenario to be chosen, trade-off resolved?
    System Logic When: in Time-slice orchestration, exception triggers? Which influences are dominant or latent?
    Technology When: for Real-time updates, predictive alerts? Which Algorithm to be chosen, threshold applied?
    Components When: for Timetables, shift calendars? Which Vehicle to be assigned, resources to get allocated?
    Instance When: in Peak hours, delays? Which Route to be selected, actions to be taken?

    ⟲ AK-3.1.2 Practice Example: Information FLow from Supply to Delivery
    Scenario Information FLow from Supply to Delivery
    ⟲ AK-3.1.3 Practice Example: Platform Engineering
    Scenario Platform Engineering
    The discipline of Platform Engineering in the Information Technology context, is primarily situated in the Technology domain, but it interacts deeply with People (stakeholders, users, operators) and Processes (budgeting, lifecycle, compliance).
    Platform Engineering 6*6 Matrix: Semantic Mapping
    Questions that help structure stakeholder understanding across context layers & abstraction layers.
    ❶ Alignment by What en How:
    What (define) How (Categorize)
    Platform
    Component     		What are the components (e.g., CI/CD, observability, identity)? How is it grouped (infra, app, data, security)?
    Decision
    Node     		What is the decision (e.g., upgrade, deprecate, patch)? How is it structured (manual, automated, policy-driven)?
    Stakeholder
    Role     		What is the role (e.g., platform engineer, SRE, architect)? How is it categorized (builder, operator, enabler)?
    Resource What is the resource (e.g., compute, storage, licenses)? How is it classified (shared, dedicated, ephemeral)?
    Feedback
    Loop     		What feedback is generated (metrics, logs, alerts)? How is it structured (push/pull, closed/open)?
    Governance
    Rule     		What policy applies (e.g., access, compliance)? How is it enforced (RBAC, audit, automation)?

    ❷ Alignment by Where en Who:
    Where (Classify) Who (Name)
    Platform
    Component     		Where is it deployed (cloud, edge, hybrid)? Who owns or maintains it?
    Decision
    Node     		Where does it apply (domain, environment)? Who decides or approves?
    Stakeholder
    Role     		Where does it act (infra, app, governance)? Who embodies the role (persona, team)?
    Resource Where is it allocated (cluster, tenant)? Who consumes or provisions it?
    Feedback
    Loop     		Where is it routed (dashboard, alerting system)? Who receives or acts on it?
    Governance
    Rule     		Where is it scoped (global, local, tenant)? Who governs or escalates?

    ❸ Alignment by When en Which:
    When (Time) Which (Distinguish)
    Platform
    Component     		When is it provisioned, scaled, retired? Which components are critical, optional, redundant?
    Decision
    Node     		When is it triggered (event, schedule)? Which options are viable, risky, deferred?
    Stakeholder
    Role     		When is the role active (lifecycle stage)? Which roles overlap or conflict?
    Resource When is it needed or constrained? Which resources are bottlenecks or elastic?
    Feedback
    Loop     		When is it reviewed or escalated? Which feedback loops are convergent or noisy?
    Governance
    Rule     		When is it evaluated or refreshed? Which rules are flexible, strict, obsolete?

    Fractals for details getting to work instructions in Platform engineering
    🚧 ZARF Integration: ⌛ ⏳What is next, Visual Implications.
    (LLM:) Resulting Artifacts: Would you like to co-design one of these artifacts—say, the Platform Engineering Compass or the Role-Task Matrix—using your ZARF overlays and AK-1.4 feedback logic?
    ⟲ AK-3.1.3 Practice Example: Information System Engineering
    Scenario Information System Engineering
    The problem:
    Cloud threats

    AK-3.2 The Purpose of defending against external threats

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-3.2.1 Context: Safety a functional requirement topic
    The displaced position at technlogy
    ⟲ AK-3.2.2 Safety in orderd external states axis
    Roles, Tasks, Methodologies for a safe environment for the system as whole.
    1. Where 👁 Demarcation
      • Define trust zones via network segmentation (VLANs, subnets, micro-segments) to isolate workloads and data.
      • Map data classification (public, internal, sensitive, restricted) and enforce controls at each zone boundary.
      • Gate all ingress/egress through identity-aware proxies or API gateways to make boundaries explicit.
    2. How 👁 Deny
      • Apply principle of least privilege with RBAC/ABAC so entities see only what they absolutely need.
      • Configure firewalls, network ACLs, and Zero-Trust Network Access (ZTNA) to block everything except whitelisted traffic.
      • Use strong authentication (MFA, certificates, hardware tokens) before granting any access.
    3. What 👁 Delay
      • Implement rate-limiting on login and sensitive APIs to thwart brute-force and automated scans.
      • Plant canary tokens, dummy credentials, or hidden honey-files in critical systems; their use triggers alerts and stalls attackers.
      • Design chokepoint proxies or jump-hosts that force lateral traffic through monitored sprint-break checkpoints.
    4. Which 👁 Deter
      • Display legal banners, warning notices, and visible security posture cues (e.g., login quarantine pages, phishing-resistant UX).
      • Run continuous security training and phishing drills to make every user a tripwire for social engineering.
      • Publicize red-team findings, bug-bounty programs, or incident post-mortems to signal active defense.
    5. When 👁 Detect
      • Centralize logs with a SIEM or XDR platform that correlates network, endpoint, and cloud telemetry in real time.
      • Deploy EDR agents, network IDS/IPS, and anomaly-based monitoring to flag behavior deviations.
      • Use honeypots, deception networks, or attack-surface scanners to capture reconnaissance and lateral-movement attempts.
    6. Who 👁 Defend
      • Maintain tested incident response plans, run tabletop exercises, and integrate IR into your CI/CD pipelines.
      • Harden systems through patch management, secure configurations (benchmarks), and regular vulnerability assessments.
      • Ensure immutable backups, disaster recovery rehearsals, and business-continuity workflows are always up to date.
    ⟲ AK-3.2.3 Safety external goals in transfomations
    transfromation reasoning
    ⟲ AK-3.2.4 Safety negative results by assumptions
    transfromation threats
    Common Mistakes to Avoid in Transitions Between the Six D's By steering clear of these transition pitfalls, you ensure each flows smoothly into the next, building a coherent, layered cybersecurity posture that not only blocks threats but actively slows, warns, spots, and counters them.
    Imagine a public digital service platform suffers a major outage during a benefits disbursement cycle. Citizens are frustrated, media scrutiny intensifies, and political pressure mounts. The system must respond not just technically—but socially. Rule ID Activated Role During Crisis XPOS_01 Reasserts system identity and clarifies its social role XPOS_02 Aligns crisis response with cultural expectations XPOS_03 Adapts behavior to ecosystem feedback and stakeholder needs XPOS_04 Manages reputation, restores legitimacy, and rebuilds trust Example: Public Trust Recovery Timeline Phase Action Day 1 Acknowledge outage, publish initial facts, activate crisis team Day 2–3 Share recovery plan, open feedback channels, engage media Week 1 Publish postmortem, announce policy adaptations, begin trust rebuild Month 1 Launch citizen listening sessions, update governance protocols Quarter 1 Release audit findings, track reputation metrics, reinforce legitimacy ZARF_XPOS during crisis acts like a public-facing immune system: XPOS_01 is the face—reassuring identity XPOS_02 is the voice—speaking with empathy XPOS_03 is the reflex—adapting to feedback XPOS_04 is the memory—learning and rebuilding trust
    Four seasons resources

    AK-3.3 Value streams by systems the subsystems in a universe

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-3.3.1 About Frameworks for architecture
    What are Frameworks?
    Examples for the goals in transformations
    Combining: 7 abilities of execution with
    7M process management (Alper Ozel 2025
    Positive actions in transformations
    Build modern01

    AK-3.4 Choices by systems as capabilities by uncertainties

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-3.4.1 About Frameworks for architecture
    interactions room

    AK-3.5 Resource continuity of the system in a universe

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-3.5.1 About Frameworks for architecture
    States in the external purpose line
    From a tool claiming to support "What are Frameworks?" Application Portfolio Management
    1. Where 👁 Manage your Application Portfolio in one solution. Perform Lifecycle Assessment, T.I.M.E. Analysis, and improve your data quality on an ongoing basis.
    2. How 👁 Align your investment portfolio with capability maps to better connect strategic goals and critical functions.
    3. What 👁 With single source of truth, manage your master data to make business impact decisions, and ensure business continuity
    4. Which 👁 Map your Business Processes, gain holistic overview of which processes support which value streams and business capabilities.
    5. When 👁 With our Information Objects, you can track your master flows through various integrations, and ensure ongoing GDPR compliance.
    6. Who 👁 Track your ideas to form initiatives from creation until approved state as visualised on digital roadmaps.
    Changing states with the States in the external purpose line
    Learning restroperpective

    AK-3.6 Learning maturity from details by systems practical's

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
    ⟲ AK-3.6.1 Systems adding value, what are the values?
    What are Frameworks?
    Value Requirements (T.Gilb 2025) Value Requirements are the most important requirements for any project. They are the main purpose, and main justification, for a project. They are the stakeholder's values.
    Value requirements start life as value "attributes¨, needed by stakeholders. No project can deliver all needed values, by a deadline. No project will find all stakeholder values to be worth delivering.
    So all value requirements start life by being acknowledged as possible delivery candidates. But VRs need to go through an evaluation process to determine that we can prioritize them for real delivery.
    ⟲ AK-3.6.2 SSystems thinkning and lean: duality not a dichotomy
    reflections on how lean really works
    Value Requirements (T.Gilb 2025) Because lean thinking is a study of challenges and responses, it’s really a study of how we define challenges together and how we build responses together, according to each person’s unique perspective, interests and special insights. To a large extent, lean thinking is not just a science of improvement, but also a science of building stronger teams.
    Lean is not for everyone. Not because it’s particularly mysterious or complicated, but because it requires four deep commitments: to face our challenges in order to find more value to deliver; to be disciplined in our responses, both with routine problems and new, unexpected ones; to self-train and learn what we have to learn in order to succeed at responding to our challenges (which, in lean, men ans accepting to follow a sensei where and when he or she points the way); and to do it all together.
    It’s easy to mistake the lean system for a toolbox: apply this tool to this problem and things will automatically improve. It’s equally easy to fall into the opposite extreme and think that coaching doesn’t require the constraints of the TPS (or cherry-picking your favorite aspect of the system as the only you need – hint: it’s a system!). In truth, the system is a concrete, hands-on theory of improvement that helps the sensei to find which exercise will make you progress right now (just as the sensei will progress in his or her understanding of the system itself).
    Lean is a self-development method, not an organizational framework. And yes, we all have good days and bad days. Sometimes we think the work is good enough (why can’t customers see how hard I work and how difficult it is, for a change?). Sometimes we’re under pressure to cut corners, and then to cover up cutting corners. Sometimes, we simply can’t be bothered to challenge habits.
    And that’s ok. The point of a lean system is that it remains there for us when we want to get back on the bike and keep climbing up the learning curve – no matter how often we fall. The deeper learning is always right behind the lesson we currently struggle with. Which is also what makes it endlessly fun.
    ⟲ AK-3.6.3 Learning from AI trying to improve complex frameworks
    Addtional rules for ZARF: Together, they turn ZARF into a fully governed, enterprise-grade reference frame for managing complexity end-to-end.
    Traditional reference models (like Zachman) lacked the depth to handle human values, systemic tensions, and adaptive governance. These sections diagnose what was missing. Identified Conceptual Gaps - ZARF Response attempt to resolve:
    ⟲ AK-3.6.4 Learning from AI trying to understand complex systems
    The world is a continuum.
    46 lessons (I learned about system thinking, Ron Immink ) There are no separate systems. Everything we think we know about the world is a model. Every word and every language is a model. All maps and statistics, books and databases, equations and computer programs are models. So are the ways you picture the world in your head, your mental models. None of these is or ever will be the real world.
    Once we see the relationship between structure and behaviour, we can begin to understand how systems work, what makes them produce poor results, and how to shift them into better behaviour patterns. These behaviour-based models are more useful than event-based ones, but they have fundamental problems. They typically overemphasise system flows and underemphasize stocks.
    The lessons I picked up:
    1. Because of feedback delays within complex systems, by the time a problem becomes apparent, it may be unnecessarily difficult to solve. A stitch in time saves nine.
    2. Don't put all your eggs in one basket.
    3. Systems happen all at once.
    4. The behaviour of a system cannot be known just by knowing the elements of which the system is made.
    5. When a living creature dies, it loses its "systemness".
    6. Elements do not have to be physical things. Intangibles are also elements of a system.
    7. Once you start listing the elements of a system, there is almost no end to the process.
    8. Many of the interconnections in systems operate through the flow of information. Information holds systems together and plays a great role in determining how they operate.
    9. Purposes are deduced from behaviour, not from rhetoric or stated goals.
    10. Keeping sub-purposes and overall system purposes in harmony is an essential function of successful systems.
    11. A system generally goes on being itself, changing only slowly if at all, even with complete substitutions of its elements, as long as its interconnections and purposes remain intact.
    12. The least obvious part of the system, its function or purpose, is often the most crucial determinant of the system's behaviour.
    13. A change in purpose changes a system profoundly, even if every element and interconnection remains the same.
    14. Interconnections are also critically important. Changing relationships usually change system behaviour.
    15. Stock is the foundation of any system. Stocks are the elements of the system that you can see, feel, count, or measure at any given time.
    16. A stock is the memory of the history of changing flows within the system.
    17. Stocks generally change slowly, even when the flows into or out of them change suddenly. Therefore, stocks act as delays or buffers or shock absorbers in systems.
    18. Changes in stocks set the pace of the dynamics of systems.
    19. The time lags that come from slowly changing stocks can cause problems in systems, but they also can be sources of stability.
    20. The presence of stocks allows inflows and outflows to be independent of each other and temporarily out of balance with each other.
    21. Human beings have invented hundreds of stock-maintaining mechanisms to make inflows and outflows independent and stable.
    22. Most individual and institutional decisions are designed to regulate the levels in stocks.
    23. Systems thinkers see the world as a collection of stocks along with the mechanisms for regulating the levels in the stocks by manipulating flows.
    24. The information delivered by a feedback loop can only affect future behaviour; it can't deliver the information, and so can't have an impact fast enough to correct the behaviour that drove the current feedback.
    25. Complex behaviours of systems often arise as the relative strengths of feedback loops shift, causing first one loop and then another to dominate behaviour.
    26. Delays are pervasive in systems, and they are strong determinants of behaviour. Changing the length of a delay may (or may not, depending on the type of delay and the relative lengths of other delays) make a large change in the behaviour of a system.
    27. Whenever we see a growing entity, whether it be a population, a corporation, a bank account, a rumour, an epidemic, or sales of a new product, we look for the reinforcing loops that are driving it and for the balancing loops that ultimately will constrain it.
    28. A quantity growing exponentially toward a constraint or limit reaches that limit in a surprisingly short time.
    29. When a subsystem's goals dominate at the expense of the total system's goals, the resulting behaviour is called suboptimisation.
    30. When a systems thinker encounters a problem, the first thing he or she does is look for data, time graphs, the history of the system.
    31. Systems rarely have real boundaries.
    32. The greatest complexities arise exactly at boundaries.
    33. You can often stabilise a system by increasing the capacity of a buffer.
    34. We are too fascinated by events. We pay too little attention to their history.
    35. Rebuilding is the slowest and most expensive kind of change to make in a system.
    36. Things take as long as they take.
    37. Missing information flows is one of the most common causes of system malfunction.
    38. Paradigms are the sources of systems.
    39. The physical structure is crucial in a system, but is rarely a leverage point, because changing it is rarely quick or simple.
    40. Disorderly, mixed-up borders are sources of diversity and creativity.
    41. Changing the length of a delay may utterly change behaviour.
    42. Change comes first from stepping outside the limited information that can be seen from any single place in the system and getting an overview.
    43. We don't give all incoming signals their appropriate weights
    44. Remember that hierarchies exist to serve the bottom layers, not the top.
    45. Thou shalt not distort, delay, or withhold information.
    46. Power over the rules is real power.
    Systems need to be managed not only for productivity or stability, but they also need to be managed for resilience. Resilience is the ability to bounce or spring back into shape, position, etc., after being pressed or stretched. The ability to recover strength, spirits, good humour, or any other aspect quickly. is a measure of a system's ability to survive and persist within a variable environment. The opposite of resilience is or rigidity. There are always limits to resilience.
      
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