Structural Layers of Information

Information is constructed from concepts, is expressed as propositions, organized into structures, encoded in physical technical representations, transformed across time and scope, and verified for conformance, correctness, and coherence.

This is the complete structural model of information separated into layers that accommodates different patterns of information including roll ups, roll forwards, restatements, reconciliations, and comparatives as structural primitives.  Each layer is clearly differentiated, each layer building on the layer below it, and each layer capturing the structural nature of information.

Layer 1: Conceptual Layer (What exists)

The layer of concepts, categories, and types that define the semantic universe in which the information lives. This layer answers: What kinds of things can information be about?

Examples: Asset, Liability, Equity

This is the “ontology” layer; the vocabulary of meaning.

Layer 2: Propositional Layer (What is claimed)

The layer of claims about concepts: subject–predicate–object claims. This layer answers: What is being asserted about those things?

Examples: “Cash = $10M at 12/31/2026” or "Assets = Liabilities + Equity".

This is the “truth‑conditional” layer; the atomic units of meaning.

Layer 3: Organizational Layer (How are different claim types grouped)

The layer that structures claims into coherent units: records, disclosures, tables, notes, schedules, datasets. This layer answers: How are things arranged into meaningful collections?

Examples: A journal entry. A primary financial statement.  A disclosure.

This is the “schema/layout” layer; the architecture of information.

Layer 4: Representational Layer (How information is encoded)

The layer of physical or digital encodings: CSV, JSON, PDF, HTML, RDF, XBRL, SQL rows. This layer answers: In what physical technical form does the information appear?

Examples: A CSV file. An XBRL instance. A PDF document. A JSON API response. An RDF graph.

This is the “surface form” layer; the physical embodiment of information using some technical syntax format.

Layer 5: Transformational Layer (How information relates, changes, and evolves)

The layer that expresses operations on information, not just information itself. This is where accounting’s structural verbs live. This layer answers: How do information sets relate across time, scope, and context?

  • Set: Simple flat list of facts that have something in common. Basic structure but with no mathematical relationship.
  • Roll‑Up; Aggregation across entities, accounts, or dimensions; Summation structure.
  • Roll‑Forward; Beginning balance → changes → ending balance. Temporal reconciliation structure.
  • Restatement/Adjustment: Replacement of an original claim with another revised or restated claim. Revision structure.
  • Reconciliation: Explanation of differences between two information sets. Difference‑explanation structure.
  • Comparative: Alignment of claims scenarios or periods. Parallel alignment structure.
  • Difference/Variance/Analysis/Allocation: Transformations that redistribute, compare, or explain values. Analytical structure. This is the “dynamic” layer; the calculus of information.
  • Text-Block/Prose: Complex layout formatted as HTML. Helpful representation.

This is a layer which helps organize information in natural, logical forms commonly used by humans to work with information. This includes being able to dynamically pivot information within a software application.

Layer 6: Verification Layer (How information is tested, confirmed, or validated)

Verification is a structural stance toward information: Verification asks whether information conforms to rules, constraints, expectations, or reality. It includes:

  • Conformance verification: Does the information follow the rules? Examples: schema validation, control checks, policy compliance, encoding validation, internal consistency checks.
  • Substantive verification: Does the information correspond to reality? Examples: confirmation, vouching, tracing, reperformance, external evidence matching.
  • Analytical verification: Does the information behave as expected? Examples: ratio analysis, trend analysis, reasonableness tests, predictive analytics.
  • Transformational verification: Are roll‑ups, roll‑forwards, reconciliations, and restatements correct? Examples: checking aggregation logic, verifying changes (beginning → change → ending), confirming restatement adjustments (original→ adjustment→ restated), testing reconciliation components.

This layer defines the evaluation of information against expectations. This layer answers: Is this information provably correct?

* * *

While not really a layer, there is one additional item which is useful to consider which is pragmatics or perspective.  Different users use information in different ways. Pragmatics/perspective does not add a new structural layer. Pragmatics adds a new interpretive perspective that operates across all layers. For example, when information is put into action (a.k.a. becomes operational); different actions require different perspectives.  Multiple organizational layer options might be necessary.


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