Ontological Parsimony (C-5)
About this pattern
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How to use this pattern
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“Add only what you cannot subtract.”
The FPF kernel aspires to remain small enough to learn in a week yet broad enough to model engines, proofs and budgets alike. Unchecked growth of primitives—well‑known from earlier “enterprise ontologies”—bloats diagrams, stalls tooling and intimidates new adopters. C‑5 therefore demands minimal‑sufficiency: a new core concept enters the kernel only when all routes of composition, refinement or role‑projection fail to express it without semantic loss.
Keywords
- minimalism
- simplicity
- Occam's razor
- essential concepts.
Content
Context
The FPF kernel aspires to remain small enough to learn in a week yet broad enough to model engines, proofs and budgets alike. Unchecked growth of primitives—well‑known from earlier “enterprise ontologies”—bloats diagrams, stalls tooling and intimidates new adopters. C‑5 therefore demands minimal‑sufficiency: a new core concept enters the kernel only when all routes of composition, refinement or role‑projection fail to express it without semantic loss.
Problem
Result: steep learning curves, fragile integrations, eroded trust in “first‑principles” promises.
Forces
Solution — Four‑Gate Minimal‑Sufficiency Protocol
A proposal to add a U.Type or core relation MUST clear all four gates before admission and survives under a Sunset Timer thereafter.
Lifecycle — Sunset Timer A cleared type enters the kernel provisionally with a timer (default = 4 quarters). If usage count remains zero at expiry, the type faces Sunset Review: delete, demote to Extention Pattern, or renew with fresh evidence.
Manager’s mnemonic: “Compose, Unique, Functional, Crisp — or sunset.”
Archetypal Grounding
Conformance Checklist
Consequences
Rationale
Cognitive science shows working memory tops out around 4 ± 1 unfamiliar chunks (Cowan 2021). Combining that with Gate discipline keeps kernel size tractable (≈ 40 primitives). Software metrics from lean DSLs (Rust traits, Kubernetes CRDs) reveal that compositional modelling reduces change propagation cost by ~30 %. The Sunset Timer borrows from Kubernetes feature gate “alpha/beta/GA” progression model — proved effective at pruning half‑baked APIs.
Relations
Illustrative Uses (2022 – 2025)
- Robotics CAL 2023 –
U.LiDARSensorrejected (Gate G‑1 passed via role composition), saving three schema migrations. - Green‑Finance CAL 2024 –
U.CarbonCreditadmitted provisionally, but Sunset Review (usage = 0) demoted it to sector pattern, avoiding kernel noise. - Neuro‑informatics 2025 –
U.ProvenanceChainaccepted; by Q3 its heavy reuse in three patterns lifted timer and marked it established.
Open Questions
- Hard size cap — should the kernel enforce an absolute limit (e.g., 64 live types) beyond which any new entry forces retirement of an old one?
- Semantic similarity tooling — can embedding models automate Gate G‑2 overlap detection reliably across domains?
- Gate calibration — is default Sunset Timer (4 quarters) optimal for research‑oriented patterns with slower uptake?