Example 10: Concept Map

Defining domain vocabulary through falsifiable propositions. The title is a Guiding Question that determines what belongs on the map. Every Concept → Relation → Concept chain ALWAYS forms a readable, falsifiable sentence. Relations can be reused when multiple concepts share the same relationship.

vgraph learningCM: ConceptMap "What is Learning?" {
    node student: Concept "Student";
    node subject: Concept "Subject";
    node practice: EmphasizedConcept "Practice";
    node understanding: Concept "Understanding";
    node resources: Concept "Resources";

    node learns: Relation "learns";
    node requires: Relation "requires";
    node leads_to: Relation "leads to";
    node uses: Relation "uses";

    edge student -> learns;
    edge learns -> subject;
    edge subject -> requires;
    edge requires -> practice;
    edge practice -> leads_to;
    edge leads_to -> understanding;
    edge subject -> uses;
    edge uses -> resources;
}

Note: In concept maps, relationships are represented as nodes (Relation type) rather than edge labels. This ALWAYS creates readable propositions like "Student learns Subject" and "Subject requires Practice". Every concept must be connected to at least one relation — never leave a concept unconnected. When multiple concepts share the same relationship (e.g. "Dog is a Mammal" and "Cat is a Mammal"), reuse a single Relation node. CRITICAL: When a relation has BOTH multiple inbound AND multiple outbound edges, ALL inbound concepts must make sense as propositions with ALL outbound concepts (n × m propositions, all must be valid). If any combination is invalid (circular, meaningless), use specific relations or restructure the graph.