It is important to remember that only the last version of each statistical observation is made available in the system. When a statistical observation is being updated, the previous value of the observation is lost and cannot be returned.
Depending on the request, a data query can result in a (potentially very) large response in which case data is delivered asynchronously. For more information please read the page 'API getting started' for the section about ASYNC endpoint
This is the SDMX 2.1 REST request for data:
https://<api_base_uri>/sdmx/2.1/<resource>/<flowRef>/<key>/<parameters> |
where
Parameter | Description |
api_base_uri | |
resource | Following resource is supported: data |
flowRef | The identifier of the dataflow reference. |
Optional | Description |
key | The key in the query is constructed as a dot ('.') separated list of dimension filtered values. |
parameters | Multiple parameters can be combined by means of '&' character. |
Format | |
Data filtering on time | |
Data filtering on first N and last N observations | |
Details | |
Compression |
SDMX 2.1 endpoint - REST - SDMX-ML 2.1 Generic Data
Retrieving data in SDMX-ML Generic Data format using REST from the SDMX 2.1 endpoint.
Example |
Usually, in any SDMX REST Data query, there is a parameter dimensionAtObservation, which can have one of those two values:
TIME_PERIOD: This will return a timeseries view of the data, i.e. pivoted (cross-sectional) data.
AllDimensions: This will return a "flat" view of the data, with no groupings.
However, this API automatically sets dimensionAtObservation on TIME_PERIOD. Then, if it is necessary to get the data in a flat format, one should use the SDMX-CSV format available in the API.
SDMX 2.1 endpoint - REST - SDMX-ML 2.1 Structure Specific Data
The Structure Specific schema is the preferable option for processing of large amounts of data.
Retrieving data in SDMX-ML Structure Specific Data format using REST from the SDMX 2.1 endpoint.
Example |
Usually, in any SDMX REST Data query, there is a parameter dimensionAtObservation, which can have one of those two values:
TIME_PERIOD: This will return a timeseries view of the data, i.e. pivoted (cross-sectional) data.
AllDimensions: This will return a "flat" view of the data, with no groupings.
However, this API automatically sets dimensionAtObservation on TIME_PERIOD. Then, if it is necessary to get the data in a flat format, one should use the SDMX-CSV format available in the API.
SDMX 2.1 endpoint - REST - SDMX-CSV Data
In SDMX-CSV, the response contains the data displayed in a flat format. It includes codes, and not labels, for dimensions positions. The labels equivalent to codes can be resolved by requesting the dataflow or data structure definition with references resolution.
Retrieving data in SDMX-CSV format using REST from the SDMX 2.1 endpoint.
SDMX 2.1 endpoint - REST - JSON-stat Data
In JSON-stat, the response includes labels, and not codes, for dimensions positions
It is mandatory to specify the language when requesting JSON-stat format for data
Retrieving data in JSON-stat format in English using REST from the SDMX 2.1 endpoint.
Example |
SDMX 2.1 endpoint - REST - TSV Data
In TSV, the response includes codes, and not labels, for dimensions positions. The labels equivalent to codes can be resolved by requesting the dataflow or data structure definition with references resolution.
Retrieving data in TSV format using REST from the SDMX 2.1 endpoint.