Purpose and Interface Scope

The complete evaluation results for Chapter 5 (the standardisation schema) are documented here, and the supplementary data package deposited with this thesis is described in the final section. The evaluation addressed three substantive questions: whether the schema resolves clause-level ambiguity in the NDIS SDA Design Standard 2019, whether resolution concentrates differentially across clause classes in a pattern consistent with the schema’s design intent, and whether the two-channel architecture is warranted by measurable complementarity between the text and figures channels. All reported metrics are grounded in artefacts held in the data package described in the final section; evidence registers mapping reported results to specific package files are listed there.

Text-Channel Evaluation Corpus and Integrity

The text-channel evaluation corpus is defined by 611 serialised clauses drawn from the NDIS SDA Design Standard 2019, covering 25 design categories. Clauses were serialised using the schema documented in Appendix: Standards Serialisation Schema and assigned clause-class labels (design_requirement, rationale, applicable_to, other). Corpus integrity baselines — structural completeness checks, identity-stability analysis, and cross-layer coverage measures — are reported in Appendix: SDA Corpus Integrity Metrics.

Text-Channel Ambiguity Resolution Results

The central evaluation measure is the per-clause ambiguity-delta: the reduction in measurable ambiguity achieved by the schema relative to an unstructured baseline. Across the 611-clause corpus, the mean per-clause ambiguity-delta is 0.2514. The aggregate full-schema delta against a null-model baseline (no schema applied) is 0.382, compared with 0.007 for the null model. The minimal-schema variant yields 0.315, establishing that clause-class annotation contributes +0.301 of the total gain and deontic annotation contributes an additional +0.067.

Table A5.1: Ambiguity-delta by schema variant

Resolution is concentrated in design_requirement clauses — the class carrying direct normative force — with an ambiguity-delta of 0.570. The rationale class achieves 0.475; applicable_to achieves 0.023; other achieves 0.000 by design, as the schema excludes residual clauses from resolution logic. This distribution confirms that the schema resolves ambiguity where the consequences of ambiguity are highest, rather than across the corpus indiscriminately. In summary, the clause-class-differentiated resolution profile is the principal evidence that the schema’s design intent — to concentrate resolution power where normative stakes are highest — is realised in practice. The next section reports the deontic force analysis that extends this picture to the modal dimension of the corpus.

Table A5.2: Ambiguity-delta by clause class

Structural resolution and deontic resolution rates are 90.6% and 90.9% respectively across the 611-clause corpus, indicating that clause-role and modality profile are preserved through the schema in the large majority of cases.

Deontic Force Analysis

The corpus is defined by 164 modal clauses, and deontic outcomes require three-way decomposition. Of the 75 coverage-gap cases, ontology coverage is insufficient to assess force; these cases represent a transparent design boundary rather than force loss. Of the remaining cases, 61 represent actual force collapse and 28 represent force-preserved resolution. This decomposition separates ontology under-coverage from genuine modality loss — a distinction that a single aggregate collapse rate obscures.

Lexical ambiguity over the corpus is a census property, reported here as a plain proportion rather than estimated from a sample. Of the 204 lemmas that meet the frequency threshold of at least three appearances, 121 — 59.3 per cent — are polysemous as the corpus stands. The polysemous set includes built-environment fundamentals — door, wall, height, basin — and spatial-category terms such as space and area; because these are also among the most frequent lemmas, their polysemy is the single largest source of the interpretive burden the schema must address explicitly. The burden concentrates where it matters most for compliance: of the 54 fallback terms the schema retains, 107 of their appearances fall within the 164 modal clauses. Full per-term polysemy counts are in Appendix: Polysemy Metrics and Confidence. The text-channel ambiguity and deontic results together show the schema reducing interpretive uncertainty precisely where normative stakes are highest while leaving the residual burden visible rather than hidden. The figures-channel results in the next section, and the cross-channel complementarity they reveal, are what warrant the two-channel architecture.

Figures-Channel Results and Cross-Channel Complementarity

The figures channel provides 189 design requirements extracted from SDA Design Standard figures, complementing the 611-clause text corpus. Of the 189 figure-derived requirements, 75.7% have no equivalent in the text channel. Conversely, 86.4% of text-channel design requirements have no figure equivalent. The figures-channel ambiguity-delta is 0.9148, substantially higher than the text-channel mean of 0.2514. Together, these figures establish that the text and figures channels carry largely disjoint normative content and differ substantially in their amenability to structured resolution, warranting the two-channel architecture rather than single-channel extraction from either source alone. Overall, the figures-channel results and cross-channel complementarity data constitute the central evidentiary basis for the schema architecture decision documented in Chapter 5. The next section presents the robustness and validation findings that confirm the stability of these results across corpus partitions.

Stability and Sensitivity Checks

Because the corpus is a complete census rather than a probability sample, stability is reported as descriptive structure across partitions of the corpus, with no interval estimate or significance test attached. When the 611 clauses are divided into ten equal partitions, on average 94.96 per cent of the terms in any one partition also occur in the others, so the schema vocabulary is shared across the corpus rather than confined to any single region of the standard. Structural coupling between primitives is reported descriptively rather than tested against a null: the co-occurrence counts for every primitive pair are deposited in the data package, and they show coupling concentrated among a minority of pairs rather than spread evenly. The one design parameter that could have driven the results, the minimum-frequency threshold, is shown to be non-load-bearing by reporting the analysis at each adjacent cut-off from one to ten appearances — no finding in this appendix changes across that range. The next section situates these results against established building and housing ontologies.

External Benchmarking

Comparison against established building and housing ontologies establishes the superiority of the schema-first approach. The SDA Design Standard serialisation achieves 100.0% clause coverage of the corpus by construction. Applied to the same clause set, IFC4 achieves 32.1% coverage and BOT achieves 20.8%, leaving approximately two-thirds of normative content unrepresented under an ontology-extension strategy. The systematic literature review underpinning Chapter 5 identified 15 of 134 floor-plan representation papers as addressing accessibility concepts, confirming that accessibility representation constitutes an under-served area in the field. Therefore, the external benchmarking evidence confirms that the schema-first approach achieves normative coverage that established ontology-extension strategies cannot match for this instrument, and this establishes the comparative justification for the design decision to develop a purpose-built serialisation schema rather than extending an existing ontology.

Supplementary Data Package

The Chapter 5 data package is deposited with this thesis in two forms: a single compressed archive and an expanded directory for direct file access. Its deposit locations are recorded in the Data Package Manifest below; an examiner can locate every component of the package from that manifest. All file references elsewhere in this appendix are given relative to the root of the deposited package (the ch5-artefact-bundle entry in the manifest).

Data Package Manifest

The interactive explorer, opened in any web browser, provides entity-browsing, triple inspection, and design-category filtering across the full serialised dataset without requiring a server. Within the expanded package, Table A5.3 lists the canonical artefact files in the canonical/ and text-corpus/ subdirectories.

Table A5.3: Canonical data package artefacts

Four flat-file exports in the package root support spreadsheet inspection: entities.csv, triples.csv, polysemy.csv, and requirements-by-category.csv. Semantic exports for graph-tool and semantic-web reuse are at semantic/sda-knowledge-graph.graphml (NetworkX DiGraph in GraphML format) and semantic/sda-ontology.ttl (RDF Turtle, planimetric.org namespace).

Field-level documentation for every field in every file is in data-package/DATA-DICTIONARY.md. Regeneration scripts are included in the package root — gen_csv_exports.py, gen_graphml.py, gen_rdf_turtle.py — all self-contained Python 3.12 programs that can be run against the canonical JSON artefacts to reproduce the derived outputs.

Provenance and Versioning

Evidence Appendices

The detailed findings for each evaluation dimension are presented in dedicated examiner-facing appendices:

• Appendix: Chapter 5 Figures-Channel Ambiguity Analysis — five-dimensional ambiguity model and per-dimension resolution rates for the 406-entry figures corpus
• Appendix: Chapter 5 Polysemy Burden Assessment — WordNet lexical polysemy, dimensional polysemy, and categorical absence polysemy across the 56-entity vocabulary
• Appendix: Chapter 5 Cross-Channel Validation Results — match type distribution and directional asymmetry between text and figures channels
• Appendix: Chapter 5 Predicate Coverage and Deontic Force — deontic force distribution, modal term inventory, force by field type and SDA category, and predicate vocabulary
• Appendix: Chapter 5 Data Pipeline and Reproducibility — pipeline architecture, file inventory, verification procedures, and reproducibility constraints
• Appendix: Chapter 5 SDA Corpus Integrity Metrics — structural completeness, identity stability, and cross-layer coverage for the text-channel corpus

Raw evidence files mapping reported results to specific data package artefacts are also deposited in the package’s evidence/ subdirectory (its location within the deposited thesis is recorded in the Data Package Manifest above), for reference by researchers accessing the data package directly.