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In plain terms: L2 represents the ship as connected engineering objects instead of disconnected files. It is the system’s answer to “what is this vessel?”

What it does

L2 is the : a structured model of what kinds of things exist in ship design and how they relate. It is stored as a , where every engineering object is a node and every meaningful relationship is a typed link. The model reads naturally:
A Vessel has Hulls and Compartments. A Compartment contains Systems. A System uses Equipment. Equipment cites Materials from Suppliers. Drawings reference Modules. Work Packages reference Modules and Materials. Evidence links to Drawings and Decisions.

Why a knowledge graph instead of tables

In a traditional database you would have a vessels table and a compartments table joined by a key. In a knowledge graph you have Vessel nodes and Compartment nodes connected by typed links like contains or adjacent_to. The payoff is that questions about relationships become simple, single-step lookups instead of complex multi-table joins:
  • “Which compartments share a bulkhead with this fuel tank?”
  • “Which prior vessels have a similar system layout?”
  • “Which decisions cite this rule version?”

What L2 outputs

The canonical objects: vessel, hull, compartment, system, equipment, drawing, material, supplier, work_package, module, evidence.

How it stays trustworthy

The ontology is validated automatically; the system never accepts an object that does not pass its rules (for example, “every Vessel must connect to at least one Hull”). And the ontology itself, the definition of what kinds of things can exist, is governed by humans, never by the AI. Related: Where Humans Stay in Control.