Sdccdif

io.github.SemanticDataCharter由 GitHub 账号 SemanticDataCharter 发布v4.1.1更新于 Nov 2, 2026

CODATA CDIF descriptions of published Semantic Data Charter models; read-only, no account.

已验证STDIO仅桌面开发者工具数据与分析

概览

AI 生成的概览

为已发布的 Semantic Data Charter 模型生成 CODATA CDIF 的 JSON-LD 描述,只读、无需账号。

可以做什么
  • 根据模型标识符或磁盘上的包目录,为一个已发布的 SDC 模型生成 CDIF JSON-LD 文档
  • 描述数据集、带 SHA-256 校验和的 schema 引用,以及每个叶子变量的数据类型、单位、范围和值域
  • 为枚举组件生成代码表,并为十六个例外值生成一个哨兵值域
  • 在工具结果中返回文档,除此之外不写入任何内容
适用场景
当你已有已发布的 Semantic Data Charter 模型,并希望在助手内直接获得符合 CDIF 规范的描述,用于元数据、目录或互操作工作时适用。
运行要求
作为本地 stdio 进程运行,通过 uvx 从 PyPI 包 sdccdif 启动(Python)。未声明账号、API 密钥或环境变量。它从磁盘读取模型包,或从固定的 SDCStudio 目录主机获取,因此目录查询需要网络访问。
安装前请注意
除返回的文档外为只读,且没有工具接受 URL,目录主机在启动时固定。模型包会从第三方目录主机获取。发布者联系点写在包数据中并可用参数覆盖,请检查输出中最终包含的联系信息。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Sdccdif,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

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 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.jsonldsdccdif 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:

schema:Datasetthe collection of records conforming to the model: name, description, identifier, URL, dates, language, licence from the model's rights, creator, publisher with a contact point, keywords; and, when the modeler wrote them in the model's Dublin Core, the publisher's name, subject keywords, contributors and coverage (schema:spatialCoverage as a named Place)
schema:publishingPrinciplesthe permanence page: a published model is immutable, a change is a new model naming the one it revised
dcterms:conformsTothe schema, by its published URL with ?sha256= and an spdx:Checksum of the bytes
schema:variableMeasured153 cdi:InstanceVariables, one per leaf of the record in document order, with the path, the library slot as schema:propertyID, the skos:exactMatch concepts as cdif:uses, the XSD datatype, unit, range, a substantive value domain and the shared sentinel domain
cdif:rolethe respondent sequence number is the UnitIdentifier; the governance leaves (audit event, PROV activity and agent) are Attributes qualifying it; everything else is a Measure
cdif:hasPrimaryKeythe unit identifier
67 skos:ConceptSchemesone per enumerated component, each value as skos:notation with its definition and the code it is defined by; a component composed three times is one codelist referenced three times
1 cdif:SentinelValueDomainthe SDC4 exceptional values (NI, MSK, INV, DER, UNC, OTH, NINF, PINF, UNK, ASKR, NASK, QS, TRC, ASKU, NAV, NA) as a skos:ConceptScheme, referenced by every variable
dcat:CatalogRecorddeclares cdif/core/1.1, cdif/discovery/1.1 and cdif/data_description/1.1

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-129085cpython 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 ([email protected] 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.

来源:README.md,提交 ddcd8a9

工具

1

write_cdif

Write the CODATA CDIF description (JSON-LD: Discovery, Data Description with every variable, Codelists, and the sentinel domain for the sixteen exceptional values) of one published Semantic Data Charter model. The document cites the model's schema by URL and SHA-256. Validated in this package's CI with CDIF's own framing, JSON Schema and SHACL checks from a pinned snapshot.

输入参数datect_iddirectorycontact_namecontact_email

版本历史

2
  1. v4.1.1最新Oct 26, 2026
  2. v4.1.0Oct 13, 2026

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