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Last modified by Artur on 2025/09/10 11:19
From version 1.23
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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... ... @@ -313,11 +313,12 @@
313 313  
314 314  The summary mapping table of the **unpivot** mapping method is the following:
315 315  
316 -|**VTL**|**SDMX**
317 -|(Simple) Identifier|Dimension
318 -|(Time) Identifier|TimeDimension
319 -|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
320 -|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
321 321  
322 322  At observation / data point level:
323 323  
... ... @@ -339,12 +339,13 @@
339 339  
340 340  The mapping table is the following:
341 341  
342 -|VTL|SDMX
343 -|(Simple) Identifier|Dimension
344 -|(Time) Identifier|TimeDimension
345 -|Some Measures|Measure
346 -|Other Measures|DataAttribute
347 -|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
348 348  
349 349  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.
350 350  
... ... @@ -382,11 +382,11 @@
382 382  
383 383  Therefore, the generic name of this kind of VTL datasets would be:
384 384  
385 -'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
387 +> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
386 386  
387 387  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:
388 388  
389 -‘DF(1.0.0)/POPULATION.USA’
391 +> ‘DF(1.0.0)/POPULATION.USA’
390 390  
391 391  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.
392 392  
... ... @@ -400,13 +400,11 @@
400 400  
401 401  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.
402 402  
403 -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 …).
404 404  
405 -basic, pivot …).
406 -
407 407  In the example above, for all the datasets of the kind
408 408  
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 +> ‘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.
410 410  
411 411  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:
412 412