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Last modified by Helena on 2025/09/10 11:19
From version 6.4
edited by Helena
on 2025/05/16 12:31
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To version 6.8
edited by Helena
on 2025/05/16 12:37
Change comment: There is no comment for this version

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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
... ... @@ -408,24 +408,17 @@
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.
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 …).
412 412  
413 -basic, pivot …).
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.
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 -
419 419  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:
420 420  
421 421  ‘DF1(1.0.0)/POPULATION.USA’ :=
422 -
423 423  DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
424 424  
425 425  ‘DF1(1.0.0)/POPULATION.CANADA’ :=
426 -
427 427  DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
428 -
429 429  … … …
430 430  
431 431  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}}
... ... @@ -438,10 +438,8 @@
438 438  
439 439  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
440 440  
441 -‘DF1(1.0.0)/POPULATION.’ :=
434 +[[image:1747388244829-693.png]]
442 442  
443 -DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
444 -
445 445  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
446 446  
447 447  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different
... ... @@ -467,54 +467,18 @@
467 467  
468 468  Some examples follow, for some specific values of INDICATOR and COUNTRY:
469 469  
470 -‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
461 +[[image:1747388222879-916.png]]
471 471  
472 -… … …
463 +[[image:1747388206717-256.png]]
473 473  
474 -‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
475 -
476 -‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
477 -
478 -… … …
479 -
480 480  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:
481 481  
482 -VTL dataset INDICATOR value COUNTRY value
467 +[[image:1747388148322-387.png]]
483 483  
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 -
494 494  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:
495 495  
496 -DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
471 +[[image:1747388179021-814.png]]
497 497  
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 -
518 518  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
519 519  
520 520  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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