Distinctions

Conceptual distinctions that clarify why many industrial and regulated systems fail despite extensive data collection.

Most system failures are not caused by missing technology, but by blurred concepts.

The Distinctions section separates ideas that are often treated as interchangeable — and shows why that confusion leads to architectural weakness.

These articles clarify differences such as:

  • logging versus audit trails
  • events versus intervals
  • reconstruction versus observation
  • data availability versus trustworthiness

Each distinction sharpens how systems should be designed, validated, and evaluated.

These texts are intentionally precise. They are meant to be referenced, quoted, and reused when explaining why “having the data” is not the same as understanding or trusting it.

Articles in this category

Audit is not logging

Why traceability fails even in systems with extensive logs and why auditability requires explicit decision context.

6 min read

Logs are not audit trails

Why log streams fail compliance and what true audit trails must guarantee in regulated industrial systems.

6 min read