Develops the theory
Defines curiosity, connection quality, ethical boundaries, evidence standards, patterns and research methods.
Architecture decision
Research, meaning generation and delivery are separate layers.
This distinction allows one research programme and one connection architecture to support travel, museums, exhibitions and learning without letting any single application define the whole project.
Curiosity Labtheory, research, principles and evaluation
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Curiosity Engineturns a seed into evidence-aware connected meaning
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Curiosity Appsdeliver domain-specific user experiences
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Meaning Tracesreturn practical observations to the Lab
Structures the meaning
Identifies anchors, associations, relationship bases, context, evidence, themes, inserts and open questions.
Delivers the experience
Owns camera, location, search, interface design, accessibility, offline behaviour, maps and application-specific navigation.
Shared terminology
A small vocabulary for the whole system.
| Term | Working definition |
|---|---|
| Curiosity Seed | An object, place, name, image, concept or observation that begins exploration. |
| Curiosity Package | The structured, evidence-aware output that an application can present. |
| Narrative Anchor | A meaningful detail within the seed’s description that opens further interpretation. |
| Structural Echo | A bounded analogy between things that share an underlying structure. |
| Meaning Trace | A record of which connections were explored and how the interpretation developed. |
“AI may become an important component of the Curiosity Engine. It is not the definition of the Engine.” Curiosity System Model, v0.1