
Sdc Mapper
io.github.SemanticDataCharter由 GitHub 账号 SemanticDataCharter 发布v4.3.2更新于 Oct 29, 2026
Map Governed Data Records to documented formats, reporting what happened to every value.
概览
把受治理的数据记录映射为 UBL、EDIFACT、OMOP、FHIR、HL7 v2 等有文档的目标格式,并报告每个值的处理结果。
- 可以做什么
- 列出已安装的目标映射器,并把记录映射到指定目标格式,可配合 YAML 映射文件
- 按异常值并排比较所有已安装目标的保真度
- 校验映射文件是否符合映射 schema
- 查看哈希链调用日志:按天数汇总或校验完整性
- 解析模型命名的代码(LOINC、SNOMED CT、NCI 词表、代码表),并报告每个值的去向
- 适用场景
- 当助手需要处理 Semantic Data Charter 的受治理数据记录,并把它转换为标准格式、同时保留每个值(包括缺失、掩码或不可用值)的可审计说明时适用。
- 运行要求
- 以 stdio 本地进程运行,从 PyPI 安装并用 uvx 启动。需要模型包目录或从 SDCStudio 主机获取的已发布模型标识,因此可能需要网络访问。每种目标格式是单独的包,需另行安装。未声明认证或环境变量。
安装
在 SourceWeft 中
- 打开 控制台中的 Sdc Mapper,将其添加到工作区。
- 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-mapper
The shared core of the Semantic Data Charter's Governed Data Record mappers. It validates a record, reads the model the record names, resolves every value against what the model says about it, hands the result to a target mapper, and reports every value: how it reached the target, or that the target cannot hold it. Where the record says why a value is missing or unusable (an Exceptional Value, from the ISO 21090 null flavors), the report also says whether the target could say it too. Every call is appended to a hash-chained log that holds no values.
Each target format is its own package (sdc-gdr2ubl, sdc-gdr2edifact, sdc-gdr2omop, ...) registered under the
entry-point group sdc_mapper.targets. Outbound only. Apache 2.0.
Status: 4.3.2. Five target mappers are released: sdc-gdr2ubl (OASIS UBL 2.3), sdc-gdr2edifact (UN/EDIFACT
D.24A), sdc-gdr2omop (OMOP CDM 5.4), sdc-gdr2fhir (HL7 FHIR R4) and sdc-gdr2hl7v2 (HL7 v2.5.1).
Use
A model is a package directory (dm-<ct>.jsonld, dm-<ct>.xsd) or a published model's --ct-id, fetched from the
SDCStudio host; with neither, the record's own root names it. Exit status: 0 mapped, 1 refused, 2 error.
The three outcomes
- valid: mapped.
- valid with Exceptional Values: a value that failed its constraint is covered by an Exceptional Value (Invalid, with the constraint kept), and the rest of the record is mapped. Exceptional Values written at the source (a refusal, a masked field) are kept as written.
- refused: a broken structure, the wrong model, or an error no Exceptional Value covers. Nothing is written; the reasons are returned and logged.
Mapping files
YAML, validated against schemas/mapping.schema.json, bound to one model schema version and one target version.
Transforms: copy, code (a table), format, constant, binding (the code the model defines an enumerated value
by), link (the code of the concept the component links to), omit; clusters group or omit. binding and link
take a system (http://loinc.org, http://snomed.info/sct, a code list's IRI); their text is the model's, so a mapper
reports it as a lookup (LOOKUP_TRANSFORMS). Steps: .. up, . none, +name an element of the value's own, =name
the element of that name the parent already has. within: restricts a rule to a context. A value no rule reaches is
reported, never dropped. place(record, mapping) turns a record and its mapping into placements a mapper writes from.
Codes the model names
sdc_mapper.codes reads the IRIs the component libraries use for a concept as a code system and a code: LOINC codes
and answers, SNOMED CT, NCI Thesaurus, and any code list whose IRI ends in #code (UBL's, HL7's). A code system is
named by the IRI FHIR uses for it; a mapper turns that into its own name for the system (OMOP's vocabulary_id, HL7
v2's coding system). bound_code(value) is the code an enumerated value is defined by, linked_code(value) the code
of the concept its component links to (skos:exactMatch, then dcterms:subject), and model_codes(value) every code
the model names for it: a target code that is one of these came from the model.
Writing to a target
place() gives each value its target steps. Steps written =name join an element made by another value, so a writer
holds those writes back until every other value is written, then writes them shallowest first: sort them by
join_depth(steps). A row-oriented target (a set of tables, as OMOP's) can treat each step as a table or a column,
+TABLE as one new row per value, and keep the record's own row (its person, its document) under a name of its own;
sdc-gdr2omop does so with a RECORD table.
Writing a mapper
A mapper has name, target, target_version, package, version, an Exceptional Value table (ev_table: an
EVRule per ISO 21090 code: preserved, degraded, carried or lost) and map(record, mapping) -> MapResult. It returns
one ValueOutcome for every value it was given, never writes a rejected value as a value, and registers itself:
Tests
python -m pytest tests -q (offline). The fixture is a HalvorsenDemo Credit Note record and its model's package;
the reference mapper in tests/refmapper.py is a flat CSV used only to exercise the contract.
License
Apache 2.0. See NOTICE for the shipped SDC4 reference model schema and the fixture.
来源:README.md,提交 a13e162
工具
0版本历史
3- v4.3.2最新Oct 29, 2026
- v4.3.1Oct 26, 2026
- v4.2.0Oct 25, 2026
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