Logical Systems for Business Professionals

Business professionals are (a) not trained for having precise discussions of these sorts of issues with software engineers, (b) don’t care to have such technical discussions about these sorts of issues with software engineers, (c) are not interested in the theoretical or philosophical or religious debates that commonly exist related to these alternatives between different software engineers, (d) if the alternatives were appropriately articulated to a business professional, who tend to be very practical, they would most often error on the side of system safety, reliability, and therefore predictability.

A logical theory enables a community of stakeholders trying to achieve some goal or objective or range of goals/objectives to describe and agree on important logical details related to the shared understanding for some area of knowledge in order to implement a logical system that works effectively for that purpose.

This is my best summary of the moving pieces related to creating a logical system effectively.

Logical systems are going to need a source of high quality data in order to function effectively.  Ask yourself who will provide that high quality data specific to an area of knowledge? (AI + HI = Transformation)

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A system (a.k.a. formal system) is a cohesive conglomeration of interrelated and interdependent parts that is either natural or man-made (designed system). A logical system is a type of system.  Systems are organized. A system has a describable pattern of behavior.  The notion of a system is explained by systems theory.

A logical theory is used to explain (provides a logical conceptualization for) and test a logical system. There are many approaches to representing logical systems in machine-readable form, a logical theory being the most powerful (ontology + rules).  A logical theories describes patterns.  A logical theory provides a logical schema for the logical system.

(See this simple explanation of a logical system for details of the parts of a logical system. See this example of the specific detailed parts of a financial report logical system.)

Proofs verify theories (Book of Proof).  The ideas of proof theory can be used to verify the correctness of logical systems and computer programs working with those machine-readable logical systems using mathematics.

Models provide flexibility.  Model theory is a way to think about flexibility.  Safer finite model theory is preferable to general model theory.

Set theory is foundational to logic and mathematics.  Axiomatic (Zermelo–Fraenkel) set theory is preferred to naïve set theory.

Graph theory is a tool for explaining associations between things.  There are different categories of graphs.  Directed acyclic labeled property graphs are preferred to less powerful “trees” and graphs which contain cycles that can lead to catastrophic problems and system failures caused by those cycles.  An example of a catastrophic failure is getting into a processing loop that you then cannot get out of. Network theory is part of graph theory.

Classification is the process of distinguishing between different things and putting things into groups or sets.  Classification is a powerful tool. The book Everything is Miscellaneous can help you understand classification.

The difference between data and information is that data is the raw numbers and words where information is data in context.  Knowledge is a set of data and information and a combination of skill, know-how, and experience which can be used to improve the capacity to take action or support a decision making process. That improved capacity to take action is referred to as insight and wisdom.

There are different approaches to representing knowledge. These knowledge representation approaches form a spectrum. These different knowledge representation approaches offer different levels of power in terms of reasoning capabilities (see larger image):

Logic is a set of principles that form a framework for correct reasoning. Logic is a process of deducing information correctly.  Logic is a formal communications tool.  Horn logic is a subset of first-order logic and is the basis for Prolog. Datalog is a subset of Horn logic (function free PROLOG) which is immune from logical paradoxes which cause catastrophic failures and should be used as contrast to more powerful but also more potentially problematic full set of first order logic features.  Logic is used to represent meaning (semantics).

Logic allows you to reason over some knowledge representation such as a knowledge graph system or some other knowledge assembly.  Logic allows you to create a chain of reasoning. A logic gate can be thought of as a building block for creating digital logic circuits.

There are three general types of reasoning: deductive reasoning, inductive reasoning, and abductive reasoning.  There tend to be three reasoning chaining strategies: sequential, forward chaining, backward chaining.

A world view is a view of how certain specific issues should be handled. The following are common issues which appear when implementing logical systems which exchange information in machine-readable form, the safest and most reliable alternatives are:

The dimensional fact model provides a clear and exhaustive representation of multidimensional concepts.  XBRL Dimensions specifies a dimensional fact model.

The Logical Theory Describing Financial Report is a logical conceptualization of the mechanical, mathematical, structural, and logical aspects of general purpose and special purpose financial reports for the purpose of representing such reports digitally using XBRL and other technical syntaxes. A financial report can be represented as a machine-readable knowledge graph.

The Standard Business Report Model (SBRM) formally documents a logical conceptualization of a business report in both human-readable and machine-readable models. The Seattle Method provides functionality that is similar to the Standard Business Report Model but goes further, supporting financial reports which are a special type of business report.

The Extensible Business Reporting Language (XBRL) is the international standard for the electronic representation of business reports such as financial reports.

The Basic Formal Ontology (BFO) provides the "rules of the road" and is designed to promote consistency in the creation of logical knowledge representations that are internally consistent, domain-neutral, and will be able to work with logical information represented for other domain-specific knowledge representations.

There are many different approaches to representing logic within some physical technical format (syntax). XBRL is only one format.  Other enterprises have different preferences or different technology stacks or potentially even multiple technology stacks. The logic (semantics) represented using some physical technical format (syntax) can be converted to some other physical technical format if both the input format and output format have the same logic (semantics) representation capabilities.
Why is all this stuff necessary? Financial statements are not forms. Those creating financial reports are permitted to modify their report models within the boundaries of what is allowed in financial reporting.  A proven, industrial strength, good practices based, standards-based pragmatic approach to creating provably high quality XBRL-based general purpose financial reports is necessary.  "Freeform" or uncontrolled customizations of report models will not work.  Controlled customization is necessary.  The Seattle Method and SBRM are the control mechanisms.

This approach leverages Lean Six Sigma principles, philosophies, and techniques. Lean Six Sigma  is a discipline that combines the problem-solving methodologies and quality enhancement techniques of Six Sigma with the process improvement tools and efficiency concepts of Lean Manufacturing.  Specifically, Lean  is ‘the purposeful elimination of wasteful activities.’ It focuses on making process throughout your company faster, which effects production over a period of time. Six Sigma  works to develop a measurable process that is nearly flawless in terms of defects, while improving quality and removing as much variation as possible from the system.

I understand less how cryptography fits into this equation. For some use cases being able to prove information provenance is important as are audit trails.  Digital distributed ledgers can provide benefits.  Merkle hashes and Merkle DAGs are very helpful tools, it seems, for making sure information has not been tampered with. NFTs have benefits.  These ten keys to creating a universal financial reporting framework can help you understand how to put the pieces together.

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If all the pieces are put together effectively, a knowledge based system can be created.  Good old fashioned artificial intelligence (GOFAI) will serve as a foundation upon which other additional artificial intelligence will be build, neuro-symbolic AI. (here is larger image)


A kluge is a term from the engineering and computer science world that refers to something that is convoluted and messy but gets the job done. Elegance is the quality of being pleasingly ingenious, simple, neat. Elegance is about beating down complexity.  Creating something complex is easy.  Creating something simple and elegant is hard work.

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