# 04 - Convert to JSON-LD

## Context / Goal
Produce the ontology-annotated JSON-LD representation of the corpus: the format evaluated for inter-lab data exchange (FAIR). Two variants: (a) full - bulk points embedded; (b) hybrid - metadata JSON-LD with `sourceFile` links to CSV.

## Dependencies
03 (`./out/csv/`, MANIFEST.csv).

## Input
CSV tree.

## Processing instructions
- `@context`: project vocab `https://sandia.gov/ontology/tribology#` + QUDT units + PROV-O provenance; predicates `partOf`, `cutFrom`, `performedOn`, `performedBy` as `@id` links.
- Entity classes: `Batch, Wafer, Coupon, Instrument, CompositionMeasurement, NanoindentationMeasurement, AFMMeasurement, ProfilometryMeasurement, FrictionTest (track), FrictionCycle, FrictionLoopPoint, WearMeasurement, SimtraProfile, Run`.
- Variant FULL: one JSON-LD file per coupon (embedding its tracks/cycles/loops), compact serialization (no pretty-print). Directory `./out/json/full/`.
- Variant HYBRID: single `./out/json/hybrid/dataset.jsonld` with all metadata entities; cycle/loop arrays replaced by `{"sourceFile": "<relative csv path>", "rows": N, "sha256": "..."}`.
- Stream-write; validate one sample file with `json.load` + rdflib JSON-LD parse.

## Output
- `./out/json/full/` (expect ~0.7-1.2 GB), `./out/json/hybrid/dataset.jsonld` (expect < 20 MB).
- Record byte sizes of both variants into `./out/bench/storage_sizes.csv` (append: format, variant, bytes).
- Marker `./out/.done/04.ok`.