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Technical Term

Technical manifestations of a Concept in code, data, and metadata

What is a Technical Term?

A Technical Term is the manifestation of a Concept in the digital landscape—code, databases, and APIs.

While Business Terms focus on how people talk, Technical Terms focus on how systems "speak." Linking these together in the Knowledge Graph provides 100% traceability from a high-level business requirement down to the exact database column or line of code.

Why it Matters

  • Automated Discovery: We can scan codebases to find where business concepts are actually implemented.
  • Impact Analysis: See how a change in business logic affects specific technical components.
  • Transparency: Provides a clear map of how data flows through the enterprise.

Technical Terms in Code and Data

Technical Terms include any symbol or identifier used in technical artifacts:

  • Variable names (e.g., _customer, cust_id, ?cust)
  • Database columns (e.g., P_NAME, CLIENT_REF)
  • API parameters (e.g., /customers/{id})

Automated Discovery

Technical Terms are often discovered automatically by scanning repositories (Python, Java, SQL, CSV, etc.). Each detected manifestation becomes a Technical Term that links back to the Concept.

Semantic & Validation Artifacts

Later in the lifecycle (Build phase), Technical Terms also represent:

  • OWL classes and properties in an ontology.
  • SHACL shapes and constraints.

Ontology (minimal facts we can state today)

Required facts about a Technical Term

  • Inherits from Term: All facts required for a Term apply.
  • Term Kind: Must be identified as a "Technical Term".
  • Provenance (Source Location): Must capture where the term was found:
    • Repository URL
    • File path & Line range
    • Commit / Revision
  • System / Artifact: The specific system where the term resides.
  • Mapping Kind: For ontology terms (e.g., representsClass, constrainedByShape).