Last modified by Helena on 2025/09/10 11:19

From version 15.3
edited by Helena
on 2025/05/16 13:14
Change comment: There is no comment for this version
To version 15.5
edited by Helena
on 2025/05/16 13:16
Change comment: There is no comment for this version

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... ... @@ -328,14 +328,10 @@
328 328  
329 329  Several changes have been made the Data Structure Definition to support microdata use cases in addition to aggregated time series.
330 330  
331 -=== Multiple measures ===
331 +(% class="wikigeneratedid" id="HMultiplemeasures" %)
332 +**Multiple measures**
333 +Multiple measures are a common characteristic of microdatasets. To support this use case, the MeasureDimension has been deprecated and replaced with the option to define zero or more measures. Measures now act like any other component in that they use concepts, can have their own local coded or uncoded representation defined within the Data Structure Definition, and can be either mandatory or conditional. Creating a measure with the “MEASURE” concept role applied emulates the version 2.1 MeasureDimension behaviour as illustrated in the SDMX-ML example below:
332 332  
333 -Multiple measures are a common characteristic of microdatasets. To support this use case, the MeasureDimension has been deprecated and replaced with the option to define zero or more measures. Measures now act like any other component in that they use concepts, can have their own local coded or uncoded representation defined within the
334 -
335 -Data Structure Definition, and can be either mandatory or conditional. Creating a measure with the “MEASURE” concept role applied emulates the version 2.1
336 -
337 -MeasureDimension behaviour as illustrated in the SDMX-ML example below:
338 -
339 339  > <str:MeasureList id=”MeasureDescriptor”>
340 340  > <str:Measure id=”OBS_VALUE” minOccurs=”1” maxOccurs=”1” usage=”mandatory” > <str:ConceptIdentity>
341 341  > <Ref id=”OBS_VALUE” maintainableParentID=”CONCEPTS” agencyID=”SDMX” maintainableParentVersion=”1.0.0” />
... ... @@ -351,20 +351,18 @@
351 351  > <str:Measure>
352 352  > </str:MeasureList>
353 353  
354 -=== Multi-value measures and attributes ===
355 -
350 +(% class="wikigeneratedid" id="HMulti-valuemeasuresandattributes" %)
351 +**Multi-value measures and attributes**
356 356  Both measures and attributes have been extended with the option to take ‘arrays’ of 193 multiple coded or uncoded values. This supports use cases like multiple observation 194 status flags. New //minOccurs// and //maxOccurs// properties define the valid number of 195 values. The //usage// property separately defines whether the measure or attribute is //mandatory// or optional. In the SDMX-ML measure example above, the properties //minOccurs=”1” maxOccurs=”1” usage=”mandatory”// specify that OBS_VALUE must be 198 reported, and can only consist of a single value.
357 357  
358 -=== Attributes relationship to measures ===
359 -
354 +(% class="wikigeneratedid" id="HAttributesrelationshiptomeasures" %)
355 +**Attributes relationship to measures**
360 360  In addition to attaching attributes to a specific level within the dataset, their relationship 202 to measures can also be defined.
361 361  
362 -=== Value lists ===
358 +(% class="wikigeneratedid" id="HValuelists" %)
359 +**Value lists**
360 +Value lists help in modelling microdata by providing an enumeration similar to code lists 206 but allowing any string values without being restricted to the rules of SDMX identifiers. That allows ValueItems (the equivalent to Code) to contain symbols like ‘¥’ and ‘€’, but also means they are not identifiable.
363 363  
364 -Value lists help in modelling microdata by providing an enumeration similar to code lists 206 but allowing any string values without being restricted to the rules of SDMX identifiers.
365 -
366 -That allows ValueItems (the equivalent to Code) to contain symbols like ‘¥’ and ‘€’, but 208 also means they are not identifiable.
367 -
368 368  == 3.6 Geospatial Data Exchange ==
369 369  
370 370  The version 3.0 model has been extended to provide explicit support for geospatial data.