XBRL Semantic Model

The purpose of the Triangle of Meaning is to understand how to make communication reliable, repeatable, and interoperable. Basically the triangle of meaning is about precision of communication. As explained by the Triangle of Meaning a conceptualization (a thought process), referents in the conceptualization (real world things being conceptualized in the form of a model), and representations or implementations of the conceptualization of the real world thing needs to be in sync in order to communicate effectively.

XBRL provides both a global open industry standard technical syntax (implementation) and a semantic model (conceptualization) of the real world notion of a "business report" (real world thing).  Both the technical syntax and the semantic model are described in the many XBRL Specifications.

The real world things that fit into that model are defined within my Essence of Accounting, reporting frameworks used, accounting and reporting standards written, conceptual frameworks, theories which explain how accounting works, ISO/IEC standards that describe things like the Accounting and Economic Ontology, books like The Future of Accounting, and such.  I have taken all that information, analyzed it, and distilled the observed patterns down to a set of machine readable logical patterns and I have describe these logical patterns in the form of a set of  theories that all follow a metatheory pattern.  The theories are all described using the mechanisms provided by XBRL.

At its essence, the XBRL semantic model is a clean and complete global open industry standard multidimensional knowledge graph of business‑report meaning (a.k.a. business report).  That semantic model includes business report elements (a.k.a. report elements), connections between report elements (a.k.a. relations, associations), structures (a.k.a. assemblies) of useful connections and conditions, facts (measurements, observations), and conditions that must be satisfied (a.k.a. assertions, restrictions, constraints. That XBRL semantic model describes what a business report is and how a business report works.  It provides, in essence, a theory of how a business report works; how the elements, connections, conditions, and facts interact with one another. The XBRL semantic model defines/explains/specifies what a business report means, independent of how it is serialized (XML, JSON, JSON-LD, RDF, GQL, SQL, PROLOG, CSV, etc.) into a physical technical syntax/format.

The XBRL semantic model tries to carefully separate the notion of a "report" which is a document with the notion of the information which is represented in the form of a global open industry standard multidimensional knowledge graph of information (a.k.a. business‑report meaning).

The XBRL semantic model objects (high level things used to build stuff) include the following logical objects which describes the structure of a business report (a.k.a. knowledge graph of business information):

I like to use the term "theory" to explain what is being described to provide clarity.  My logical theory defines and explains the above four core high level objects.

XBRL International's Project Tavi specifies a complete, compiled, and fully assembled XBRL semantic model canonical representation of the business report’s meaning in final canonical form, the compiled model. It also provides a process to determine if a compiled model is structurally valid.

As such, the discrete units of a report and the report as a whole can be structurally verified to be consistent with the XBRL semantic model.

In addition, Project Tavi provides strong typing of many XBRL semantic model objects. In particular, now hypercubes can be typed. Further, eight specific hypercube types have been defined. These types enable clear identification of the nature of the information within the hypercube. Further, users can create/define their own cube type objects.

Finally, Project Tavi defined some foundational financial reporting semantics. There is a lot more that is possible, but this is a start.

The terms "squishy" and "accounting" don't really go together. Project Tavi makes XBRL-based reports significantly less squishy.  The definition of a well structured report is getting clearer to others.

A global open industry standard multidimensional knowledge graph of information needs the following types of systems to make it work effectively:

  • Vocabulary system for defining elements
  • Context system for defining the "aspects" or "facets" or "dimensions" of elements
  • Connections system for defining connections between elements and elements to the context system
  • Structure system for connecting elements together
  • System for providing measurements and observations
  • Measurement context system for communicating the context of such measurements and observations including their units, the periods, and the entities the measurements and observations relate to
  • A presentation system that enables everything to be organized into a human readable presentation
  • A system to manage permitted logical conditions and differentiate what is logically permitted from what is not logically permitted (e.g. assertions, constraints, restriction management)
XBRL provides all this.

But there is still a gap. The Seattle Method reveals some fundamental limitation in how XBRL has been implemented and understood and offers a path beyond those limitation. Standard XBRL taxonomies are, in essence, rather poorly organized taxonomies of financial reporting concepts. They define what the concepts, how they are labeled, provide references to authoritative literature.  But they do not fully encode how those concepts function within a complete reporting system. The Seattle Method augments these taxonomies with the functional logic that is currently missing; the relationships, constraints, rules, and structural principles that govern how concepts combine to produce a valid financial report.
This addresses one of XBRL's most significant limitations: the gap between having tagged data and having understood data. An XBRL filing with perfect tagging is still just a collection of labeled values unless you have a framework for reasoning about whether those values, taken together, represent a logically coherent financial report. The Seattle Method provides that framework.  The Seattle Method thinking is not just a financial report, but the entire accounting information system when you are operating in a digital environment with artificial intelligence capabilities being used.

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