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Ledger

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A "list" and a "ledger" are not the same thing. A ledger is a computational substrate. A list is a collection of items. A ledger stores state. A list is inert. A ledger is dynamic: every ledger entry changes the state of the system. A list is descriptive. A ledger is computational. A ledger is essentially a model of financial reality, not just a record of items contained in a list. A list is just an ordered collection of items but there is no description of the relationship between the items in the list. A ledger is a governed, rule‑bound, balanced record of financial events with the relationship between the financial events explained/described. A list has no semantics, no structure, and no logic. A ledger has semantics, structure, and logic baked in. A ledger is a sequenced append-only committed formal record.  A ledger is more than a database you query for current state.  A ledger is an  immutable record of what changed, when it changed, and under what authorizati...

Mereology

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Mereology is the science of parts and wholes: what they are, how they relate, and how complex things are built from simpler ones.  Mereology is the theory of parthood relations: of the relations of part to whole and the relations of part to part within a whole. A Taxonomy of Whole-Part Relations  points out that part-whole relations can be broken out into six different groups: component-integral object : for example (pedal – bike) the pedal is an integral part of the bicycle member-collection : for example (ship – fleet) each ship is a member of the fleet portion-mass : for example (slice – pie) a slice is a portion of a pie stuff-object : for example (steel – car) steel is the stuff from which the car is made feature-activity : for example (paying – shopping) paying is a feature or component of shopping place-area : for example (Everglades – Florida) the Everglades is a place within Florida The following graphic shows the different possible who...

Theory of the Financial Reporting Framework

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This article describes the Theory of the Financial Reporting Framework .  A general purpose financial statement is a formal semantic structure .  That formal semantic structure of such a general purpose financial statement is described by the accounting equation and double entry bookkeeping model and a reporting framework.  It is that double entry bookkeeping model which differentiates "bookkeeping" from  general "recordkeeping" .  This is part of the essence of accounting . To the untrained eye, it might not look like it; but a financial reporting framework fundamentally prescribes where information from a set of business events must be reported within a financial statement. The Theory of Accounting and Control ,  Resources, Events, Agents (REA) , and ISO/IEC Accounting and Economic Ontology  each point this out. A general purpose financial statement provides quantitative financial information and nonfinancial information, aggregations and disaggreg...

Metatheory

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A hypothesis is a testable explanation or guess about why something happens; a prediction. A hypothesis helps to think about and test an idea.   A theory is a well supported explanation of why something happens.  A theory is used to explain an idea or ideas.  A law describes (makes a statement about) a universal principle or phenomenon that consistently specifies what must happen under specific conditions and is based on empirical evidence from observations.  Laws describe what happens.  Another term for law is principle. And so, it seems that a hypothesis is a preliminary testable idea or notion , a theory is a t ested explanation of an idea or notion , and a law is a descriptive regularity of the nature of an idea or notion .  A metatheory is a higher‑order framework that defines the foundational principles, assumptions, and evaluation criteria for constructing and comparing theories. If a theory is a blueprint, a metatheory is the building code that...

My Garden

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In January 1999, I met with the partner in charge of the CPA firm I worked for; Knight, Vale & Greggory (KVG) which is now part of RSM ; and told him how well my meeting with the AICPA related to what became XBRL  went.  KVG which was a smaller regional CPA firm basically donated my time to create a working proof of concept of an XML-based digital financial report.  In that meeting the partner in charge told me that KVG obviously could not continue underwriting the cost of this endeavor to manifest digital financial reporting.  I told him that I completely understood but I was going to continue to pursue this; and I resigned from KVG to create " my garden ". In his article, What The Garden Is For , Matt Wood (ex-PWC now at AWS) provides an analogy between a system and a garden.  Here is my garden: Digital Information Organism Reference Reporting Frameworks Conformance Suite Example Financial Statement Holon Introducing the Global Open Industry Standard Digit...

Classification

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While the terms classification and categorization are often used interchangeably in casual conversation, they represent two distinct approaches to organizing information.  The easiest way to distinguish classification and categorization is by their level of formality and structure: classification is formal, systematic, and rule-based, while categorization is informal, intuitive, and based on similarity. Classification is the process of assigning important  things in an area of knowledge to a set of pre-defined, mutually exclusive category or class based on strict rules or criteria. Classification relates to the inclusion of a thing in a set.  It is typically a top-down approach designed for objectivity and consistency. Things tend to be classified into three broad hierarchal categories to help make distinctions clear: Basic level category is the most salient things; the differences between categories is the most noticeable, prominent, and important Superordinate level ...

Professional Oriented Knowledge Frameworks

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A knowledge graph is an approach to representing knowledge within some sort of knowledge organization system for some sort of knowledge framework. In his article, Embracing Complexity - Conclusion , Tony Seale explains how to built your organization's knowledge graph. In summary, Seale believes that an organizational knowledge graph should include: Networked data Networked cloud Networked artificial intelligence Unified network that pulls all three of the above together Then, there are three practical tools that make a knowledge graph go: The graph adapter The data service The graph neural network Using this approach, a knowledge graph can then give an organization the ability to connect all it's critical data in the entire organization together.  This gives both humans and artificial intelligence access to all that data. Seale is not specifying any specific technical implementation . He seems to be suggesting using a semantic network and network theory  which is part of gr...