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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
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To version 6.4
edited by Helena
on 2025/05/16 12:31
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... ... @@ -348,7 +348,7 @@
348 348  The mapping table is the following:
349 349  
350 350  (% style="width:689.294px" %)
351 -|(% style="width:344px" %)**VTL**|(% style="width:341px" %)**SDMX**
351 +|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX
352 352  |(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension
353 353  |(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension
354 354  |(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure
... ... @@ -408,17 +408,24 @@
408 408  
409 409  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.
410 410  
411 -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 …).
411 +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.
412 412  
413 -In the example above, for all the datasets of the kind ‘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.
413 +basic, pivot …).
414 414  
415 +In the example above, for all the datasets of the kind
416 +
417 +‘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.
418 +
415 415  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:
416 416  
417 417  ‘DF1(1.0.0)/POPULATION.USA’ :=
422 +
418 418  DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
419 419  
420 420  ‘DF1(1.0.0)/POPULATION.CANADA’ :=
426 +
421 421  DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
428 +
422 422  … … …
423 423  
424 424  In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}}
... ... @@ -431,8 +431,10 @@
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]]
441 +‘DF1(1.0.0)/POPULATION.’ :=
435 435  
443 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
444 +
436 436  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
437 437  
438 438  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different
... ... @@ -458,18 +458,54 @@
458 458  
459 459  Some examples follow, for some specific values of INDICATOR and COUNTRY:
460 460  
461 -[[image:1747388222879-916.png]]
470 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
462 462  
463 -[[image:1747388206717-256.png]]
472 +… … …
464 464  
474 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
475 +
476 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
477 +
478 +… … …
479 +
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]]
482 +VTL dataset INDICATOR value COUNTRY value
468 468  
484 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
485 +
486 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
487 +
488 +‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
489 +
490 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
491 +
492 +… … …
493 +
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]]
496 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
472 472  
498 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
499 +
500 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
501 +
502 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
503 +
504 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
505 +
506 +DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
507 +
508 +DF2bis_GDPPERCAPITA_CANADA’,
509 +
510 +… ,
511 +
512 +DF2bis_POPGROWTH_USA’,
513 +
514 +DF2bis_POPGROWTH_CANADA’
515 +
516 +…);
517 +
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  
475 475  DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
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