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Last modified by Artur on 2025/09/10 11:19
From version 1.22
edited by Helena
on 2025/06/16 13:27
Change comment: There is no comment for this version
To version 1.24
edited by Helena
on 2025/06/16 13:29
Change comment: There is no comment for this version

Summary

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... ... @@ -280,11 +280,12 @@
280 280  
281 281  Mapping table:
282 282  
283 -|**VTL**|**SDMX**
284 -|(Simple) Identifier|Dimension
285 -|(Time) Identifier|TimeDimension
286 -|Measure|Measure
287 -|Attribute|DataAttribute
283 +(% style="width:470.294px" %)
284 +|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX**
285 +|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension
286 +|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension
287 +|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure
288 +|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute
288 288  
289 289  If the distinction between simple identifier and time identifier is not maintained in the VTL environment, the classification between Dimension and TimeDimension exists only in SDMX, as declared in the relevant DataStructureDefinition.
290 290  
... ... @@ -312,11 +312,12 @@
312 312  
313 313  The summary mapping table of the **unpivot** mapping method is the following:
314 314  
315 -|**VTL**|**SDMX**
316 -|(Simple) Identifier|Dimension
317 -|(Time) Identifier|TimeDimension
318 -|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
319 -|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
316 +(% style="width:638.294px" %)
317 +|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX**
318 +|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension
319 +|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension
320 +|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
321 +|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
320 320  
321 321  At observation / data point level:
322 322  
... ... @@ -338,12 +338,13 @@
338 338  
339 339  The mapping table is the following:
340 340  
341 -|VTL|SDMX
342 -|(Simple) Identifier|Dimension
343 -|(Time) Identifier|TimeDimension
344 -|Some Measures|Measure
345 -|Other Measures|DataAttribute
346 -|Attribute|DataAttribute
343 +(% style="width:467.294px" %)
344 +|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
345 +|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
346 +|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
347 +|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
348 +|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
349 +|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
347 347  
348 348  Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the attributeRelationship for the DataAttributes, which does not exist in VTL.
349 349  
... ... @@ -381,11 +381,11 @@
381 381  
382 382  Therefore, the generic name of this kind of VTL datasets would be:
383 383  
384 -'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
387 +> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
385 385  
386 386  Where DF(1.0.0) is the Dataflow and //INDICATORvalue// and //COUNTRYvalue //are placeholders for one value of the INDICATOR and COUNTRY dimensions. Instead the specific name of one of these VTL datasets would be:
387 387  
388 -‘DF(1.0.0)/POPULATION.USA’
391 +> ‘DF(1.0.0)/POPULATION.USA’
389 389  
390 390  In particular, this is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA.
391 391  
... ... @@ -399,13 +399,11 @@
399 399  
400 400  SDMX Dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=// COUNTRYvalue//. For example, the VTL dataset ‘DF1(1.0.0)/POPULATION.USA’ would contain all the observations of DF1(1.0.0) having INDICATOR = POPULATION and COUNTRY = USA.
401 401  
402 -In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
405 +In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
403 403  
404 -basic, pivot …).
405 -
406 406  In the example above, for all the datasets of the kind
407 407  
408 -‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
409 +> ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
409 409  
410 410  It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression:
411 411