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Last modified by Helena on 2025/09/10 11:19
From version 6.8
edited by Helena
on 2025/05/16 12:37
Change comment: There is no comment for this version
To version 6.7
edited by Helena
on 2025/05/16 12:35
Change comment: There is no comment for this version

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431 431  
432 432  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
433 433  
434 -[[image:1747388244829-693.png]]
434 +‘DF1(1.0.0)/POPULATION.’ :=
435 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
435 435  
436 436  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
437 437  
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458 458  
459 459  Some examples follow, for some specific values of INDICATOR and COUNTRY:
460 460  
461 -[[image:1747388222879-916.png]]
462 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
462 462  
463 -[[image:1747388206717-256.png]]
464 +… … …
465 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
466 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
467 +… … …
464 464  
465 465  As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively:
466 466  
467 -[[image:1747388148322-387.png]]
471 +VTL dataset INDICATOR value COUNTRY value
468 468  
473 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
474 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
475 +‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
476 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
477 +… … …
478 +
469 469  It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be:
470 470  
471 -[[image:1747388179021-814.png]]
481 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
482 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
483 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
484 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
485 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
486 +DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
487 +DF2bis_GDPPERCAPITA_CANADA’,
488 +… ,
489 +DF2bis_POPGROWTH_USA’,
490 +DF2bis_POPGROWTH_CANADA’
491 +…);
472 472  
473 473  In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example
474 474  
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