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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 6.7
edited by Helena
on 2025/05/16 12:35
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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}}
... ... @@ -439,7 +439,6 @@
439 439  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
440 440  
441 441  ‘DF1(1.0.0)/POPULATION.’ :=
442 -
443 443  DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
444 444  
445 445  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
... ... @@ -470,11 +470,8 @@
470 470  ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
471 471  
472 472  … … …
473 -
474 474  ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
475 -
476 476  ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
477 -
478 478  … … …
479 479  
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:
... ... @@ -482,37 +482,23 @@
482 482  VTL dataset INDICATOR value COUNTRY value
483 483  
484 484  ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
485 -
486 486  ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
487 -
488 488  ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
489 -
490 490  ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
491 -
492 492  … … …
493 493  
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  
496 496  DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
497 -
498 498  DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
499 -
500 500  DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
501 -
502 502  [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
503 -
504 504  DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
505 -
506 506  DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
507 -
508 508  DF2bis_GDPPERCAPITA_CANADA’,
509 -
510 510  … ,
511 -
512 512  DF2bis_POPGROWTH_USA’,
513 -
514 514  DF2bis_POPGROWTH_CANADA’
515 -
516 516  …);
517 517  
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