Reference metadata

Note

Additional information about how reference metadata can be used to configure statistical processes is available in the following tutorial:

Configure your processes.

Model for SDMX Reference Metadata.

Reference metadata are quite generic (and therefore powerful) in SDMX. Though they are typically used to provide additional information about statistical data, such as information about the general methodological and quality aspects of the statistical production process, they can also be used to drive process steps such as validation or mapping, for example by providing configuration details in a metadata report.

class pysdmx.model.metadata.MetadataAttribute(id: str, value: Any | None = None, attributes: Sequence[MetadataAttribute] = ())

An entry in a metadata report.

An attribute is iterable, as it may contain other attributes.

id: The identifier of the attribute (e.g. “License”).

value: The attribute value (e.g. “BSD-2-Clause”).

attributes: The list of “children” attributes (i.e. attributes can be nested).

class pysdmx.model.metadata.MetadataReport(id: str, name: str, metadataflow: str, targets: Sequence[str], attributes: Sequence[MetadataAttribute])

An organized collection of metadata.

A metadata report is iterable and it is also possible to directly retrieve an attribute using its ID.

id: The identifier of the report (e.g. DTI_MACRO).

name: The name of the report (e.g. “Configuration metadata for the MACRO dataflow”).

metadataflow: The URN of the dataflow for which the report belongs.

targets: The URN(s) of SDMX artefact(s) to which the report relates.

attributes: The list of metadata attributes included in the report. Attributes may contain other attributes.