Sdccdif

sdc_cdif

One Semantic Data Charter model, described in CDIF.

sdccdif reads a published SDC model's package and writes the CDIF JSON-LD that describes the collection of Governed Data Records conforming to it: Core and Discovery for the dataset, Data Description for every leaf of the record, a Codelist for every enumerated leaf, and one sentinel value domain for the reference model's sixteen exceptional values. The output is checked with CDIF's own frame, JSON Schemas, SHACL and conformance validator, at a pinned commit of their validation repository.

1. What this is, and where it came from

The sample document, samples/nhanes-participant/cdif-dm-xy8upneajsb8vdcmnve01g6g.jsonld, describes the records of one published model: NHANES Participant (dm-xy8upneajsb8vdcmnve01g6g) from the FAIR Data Demo, a demographic, examination and laboratory record of the National Health and Nutrition Examination Survey (CDC). The model is public:

• the catalog record: https://sdcstudio.axius-sdc.com/api/v1/catalog/dm/xy8upneajsb8vdcmnve01g6g/
• the schema the records conform to: https://sdcstudio.axius-sdc.com/dmlib/dm-xy8upneajsb8vdcmnve01g6g.xsd
• the Semantic Data Charter: https://semanticdatacharter.com

The writer reads the package (the model's JSON-LD and its schema), the public catalog record and the published schema versions. It needs no account, and it refuses a model whose package was never built: the schema and the JSON-LD are the evidence it describes, and nothing is written that they do not carry.

pip install -e ".[fetch]"

sdccdif write --package samples/nhanes-participant --out cdif.jsonld sdccdif write --ct-id xy8upneajsb8vdcmnve01g6g --save-package pkg/ --out cdif.jsonld # any published model, from the catalog

What the document contains, for the NHANES Participant model:

2. How to verify it

The tests run CDIF's validators from data/, where their artifacts are copied at the pinned commits (validation 129085c, metadataBuildingBlocks 61f24aa; build/snapshot_cdif.py verifies the pins before copying):

pip install -e ".[dev]"

python -m pytest tests -q

Or run their conformance validator directly on the sample:

cd data/cdif-129085c

python ConformanceValidate.py ../../samples/nhanes-participant/cdif-dm-xy8upneajsb8vdcmnve01g6g.jsonld --source local --frame CDIF-frame-2026.jsonld

Result at the pin: Core SHACL passed; Discovery JSON Schema and SHACL passed; Data Description JSON Schema and SHACL passed; 0 violations; the three declared profiles consistent with the profiles the detector finds in the content. Every codelist node passes the cdifCodelist building block's JSON Schema, rules.shacl and conformance.shacl.

3. What the projection could not say

Left out rather than filled in, because the package does not carry it: a distribution of the records (the records are not public; the model is), temporal coverage, statistics. CDIF marks all of these recommended, not required. The model's own Dublin Core (subject, coverage, publisher, contributors, relation) is read from the schema header and published when the modeler wrote it; SDCStudio's field defaults ("Universal" for coverage, "None" for relation, blanks) read as unset, which is why the NHANES document carries none of them: its modeler left them at the defaults. One recommended item is declared rather than read from the package, and said so here: the publisher's contact point (contact@axius-sdc.com on the sample, in src/sdccdif/data/declared.json; --contact-name and --contact-email override it, and an empty address omits it).

And in the other direction, what the record carries that the description has no place for, stated so a reader knows where to look rather than as a shortcoming of either side:

• The governance envelope is data in every record. Each Governed Data Record carries its own audit event, PROV activity and PROV agent as leaves, validated with the rest. CDIF's provenance is a property of the dataset. The writer lists those leaves as variables with the Attribute role, so a reader can see they are there; the per-record values live in the records.
• The schema is bound to each record, not only to the collection. Every record names the schema it was validated against, and the schema never changes after publication. The description can say that once, on the dataset, which is what dcterms:conformsTo with the SHA-256 and schema:publishingPrinciples do.
• The reason a value is missing is typed in the record. A leaf may carry one of the sixteen exceptional values in place of its value, so a refusal, a value not asked for, and a value masked for privacy are different facts. CDIF's sentinel value domain describes the set; which reason applies, and where, is in the record.

4. What we learned about the CDIF profiles

Implementer's notes from building this against the artifacts at the pins above. They describe how the artifacts behave, so the next implementer spends the day on their own document rather than on these.

• The frame embeds every referenced node. CDIF-frame-2026.jsonld carries @embed: @always throughout, so a node referenced from many places (here, one sentinel domain referenced by 153 variables) is repeated at every reference in the framed tree. Harmless for validation; the framed document is many times the size of the source. Sibling @graph nodes that are not a schema:Dataset (the codelists) do not appear in the framed output and are validated separately against the codelist building block.
• `cdif:role: Attribute` requires `cdif:qualifies`. The Data Description SHACL asks every attribute to name the variable it qualifies, following DDI-CDI. A record-level attribute has the record's unit identifier to point at, which is what this writer does.
• The conformance detector gates Data Description on the instance-variable rules. detect_conformance.py reports a profile as present only when its per-class SHACL passes, so a document that declares Data Description and fails those rules is reported as over-claiming the profile rather than as failing it. Reading the SHACL section first explains the conformance section.
• The local conformance map has JSON Schemas for Discovery, Data Description and Complete. Core is checked by SHACL only (no schema mapped is the expected line), and the Codelist profile has no entry, so a codelist cannot be declared on the catalog record and checked through ConformanceValidate.py; the building block's own schema and rules check it directly.
• `cdif:physicalDataType` takes a string or a reference, and CDIF's own examples use both ("xsd:integer" and a full XML Schema URL). The string form is used here.
• IRI-shaped values must be IRI references. schema:propertyID and schema:additionalType written as strings that look like IRIs or CURIEs are SHACL violations; {"@id": ...} is the accepted form. Plain labels remain strings.
• The SKOS prefix is not in the frame's context, so framed output shows full SKOS IRIs until the validator's compaction step adds it. Expected; noted so the intermediate output does not alarm anyone.

MCP server

sdccdif is also an MCP server, registered as io.github.SemanticDataCharter/sdccdif, so an assistant that can read a published model with sdcreader can ask for its CDIF description. One tool, write_cdif, over the same function the CLI calls; stdio; read-only apart from the document it returns; no account; no tool takes a URL (the catalog host is fixed at start with --host). The protocol scaffold is sdcreader.mcp, shared by every SDC projection server.

uvx sdccdif mcp            # or: sdccdif-mcp, or sdccdif mcp

Layout

• The model's package is read with sdcreader (load_package, fetch_package, read_model): the record tree, its leaves, the enumerated values with their codes, the model's Dublin Core with SDCStudio's defaults as unset. The package format is documented there, once.
• src/sdccdif/: cdif.py (the JSON-LD), cli.py, data/sdc4-exceptional-values.json (the sixteen exceptional values, extracted from the SDC4 reference model schema).
• data/cdif-129085c/: CDIF's context, frame, JSON Schemas, SHACL, conformance map and validators. data/mbb-61f24aa/: the cdifCodelist building block and the three per-class rules the detector gates on.
• samples/nhanes-participant/: the model's package as fetched and the document written from it.
• build/snapshot_cdif.py: re-creates data/ from read-only clones of the CDIF repositories at the pinned commits.

Licences

Apache-2.0 (see LICENSE, NOTICE). The CDIF artifacts in data/ keep their own licences: the validation repository is CC0; the building blocks are CC BY 4.0, CODATA and the Cross-Domain Interoperability Framework.