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modumatics Modular Infrastructure for Inclusive Housing Tran Thien Toan Ngo · PhD Dissertation

Evidence Corpus Profile

IMPORTANT

Dataset and provenance boundary. All empirical claims in this evidence profile are derived from local screening and extraction datasets only: 574 screened records and 41 extraction-level records in curated screening and extraction registers maintained for this review.12

Evidence profile item | Value | Interpretation for this subsection |
— | —: | — |
Screened records | 574 | Broad search space exists, but most records are not truly text-conversion studies |
Included after screening | 41 | A relatively small but coherent corpus focused on text-related floor-plan methods |
Excluded | 533 | Most exclusions are due to unidirectional or non-text intermediate workflows |
Include rate | 7.1 percent | Availability exists, but field maturity is still concentrated in narrow method families |
Extracted records used here | 41 | Full included set used for synthesis, not a cherry-picked subset |

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The screening matrix clarifies scarcity. Bidirectional capability in the included set was mixed: 15 “yes”, 19 “maybe”, 7 “no”. The dominant exclusion signature was the absence of both bidirectionality and explicit text intermediates.5 Overall, the evidence funnel reveals that the field’s availability is broad at the search level but narrow at the methodological level relevant to this thesis’s concerns. The next section characterises the representation families that dominate the included set.

FIGURE

Ch2 evidence funnel for textual floor-plan representations

The funnel makes explicit that availability exists, but extraction-level work remains selective and heavily filtered by representational criteria.

SUPERSEDED

Superseded by the diagram-spec system

This Mermaid source is superseded. The canonical figure is built from the structured spec text_based_floor_plan_evidence_funnel (type funnel) in the diagram-spec engine at 50-outputs/figures/diagram-spec-system/. Build or edit it via the wrap-sk-diagram-spec skill — do not edit this Mermaid for the dissertation figure. Governed by wrap-rl-visual-materials-governance.md (N4).

graph TD
  A[Search query scope<br/>Textual floor plan representations] --> B[Screened records<br/>n = 574]
  B --> C{Holistic screening judgement}
  C --> D[Excluded<br/>n = 533]
  C --> E[Included<br/>n = 41]
  E --> F[Extracted evidence fields<br/>method, format, fidelity, interpretability, interoperability, downstream tasks]
  F --> G[Comparative synthesis for Ch2.6.3]
  D --> H[Common exclusion signature:<br/>unidirectional only + no text intermediate representation]

Directionality counts reinforce this mixed maturity. Thirteen records were tagged as bidirectional, 9 as floor-plan to text, and 7 as text to floor-plan. The remainder were either graph-to-layout specialisations or unspecified conversions.6 Taken together, the screening and directionality profiles confirm that bidirectional, governance-capable text representations remain a minority practice in the current literature.

Representation Families

Representation family | Typical textual form | Recurring strengths | Recurring constraints |
— | — | — | — |
Graph-based | node-edge lists, adjacency structures, JSON graph objects | Strong topology retention; good compatibility with graph analytics | Human readability often lower; semantics can remain implicit unless schema is explicit |
NLP/LLM-based | natural-language prompts, structured prompt JSON, language-grounded metadata | High accessibility for human-in-the-loop workflows; flexible generation and editing | Determinism and precision can be uneven; evaluation often benchmark-specific |
Token/sequence-based | token sequences, DSL-like strings, linearised structures | Compact serialisation; amenable to parsing and regression tests | Human legibility can be low; schema brittleness if tokens are under-specified |

WARNING

Evidence-quality caveat. The field currently reports many strong method demonstrations, but cross-study comparability is limited by inconsistent metric coverage and frequent “not mentioned” entries in extraction fields for fidelity, interpretability, interoperability, and evaluation methodology.7

Regression governance remains a recurring gap. Few studies publish stable encode-decode regression suites that can be rerun when models, dependencies, or schema bindings change. This matters for lifecycle adaptation because governance workflows are longitudinal and must remain checkable under version drift, not only under one-off experimental conditions.8 In summary, none of the three dominant approaches — graph-based, NLP/LLM-based, or token/sequence-based — individually satisfies the full property set. Each approach covers some governance requirements but leaves others unaddressed. Therefore, this evidence profile grounds the Chapter 2 argument that a purpose-designed planimetric notation is needed rather than an extension of an existing family.

Notes

  1. Author screening register for text-based floor-plan representation evidence (574 screened records, February 2026) ↩︎
  2. Author extraction register for text-based floor-plan representation evidence (41 extracted records, February 2026) ↩︎
  3. Author screening register for text-based floor-plan representation evidence (574 screened records, February 2026) ↩︎
  4. Author extraction register for text-based floor-plan representation evidence (41 extracted records, February 2026) ↩︎
  5. Author screening register for text-based floor-plan representation evidence (574 screened records, February 2026) ↩︎
  6. Author extraction register for text-based floor-plan representation evidence (41 extracted records, February 2026) ↩︎
  7. Author extraction register for text-based floor-plan representation evidence (41 extracted records, February 2026) ↩︎
  8. Author extraction register for text-based floor-plan representation evidence (41 extracted records, February 2026) ↩︎