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Last modified by Helena on 2025/09/10 11:19
From version 6.12
edited by Helena
on 2025/05/16 12:41
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To version 6.7
edited by Helena
on 2025/05/16 12:35
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414 414  
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 -[[image:1747388275998-621.png]]
417 +‘DF1(1.0.0)/POPULATION.USA’ :=
418 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
418 418  
420 +‘DF1(1.0.0)/POPULATION.CANADA’ :=
421 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
422 +… … …
423 +
419 419  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}}
420 420  
421 421  In the direction from SDMX to VTL it is allowed to omit the value of one or more
... ... @@ -426,7 +426,8 @@
426 426  
427 427  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
428 428  
429 -[[image:1747388244829-693.png]]
434 +‘DF1(1.0.0)/POPULATION.’ :=
435 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
430 430  
431 431  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
432 432  
... ... @@ -453,17 +453,36 @@
453 453  
454 454  Some examples follow, for some specific values of INDICATOR and COUNTRY:
455 455  
456 -[[image:1747388222879-916.png]]
462 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
457 457  
458 -[[image:1747388206717-256.png]]
464 +… … …
465 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
466 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
467 +… … …
459 459  
460 460  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:
461 461  
462 -[[image:1747388148322-387.png]]
471 +VTL dataset INDICATOR value COUNTRY value
463 463  
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 +
464 464  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:
465 465  
466 -[[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 +…);
467 467  
468 468  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
469 469  
... ... @@ -477,30 +477,38 @@
477 477  
478 478  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
479 479  
480 -(% style="width:895.294px" %)
481 -|(% style="width:278px" %)**VTL**|(% style="width:613px" %)**SDMX**
482 -|(% style="width:278px" %)**Data Set Component**|(% style="width:613px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
483 -|(% style="width:278px" %)**Represented Variable**|(% style="width:613px" %)(((
505 +(% style="width:1170.29px" %)
506 +|**VTL**|(% style="width:754px" %)**SDMX**
507 +|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
508 +|**Represented Variable**|(% style="width:754px" %)(((
484 484  **Concept** with a definite
485 485  
486 486  Representation
487 487  )))
488 -|(% style="width:278px" %)**Value Domain**|(% style="width:613px" %)(((
489 -**Representation** (see the Structure Pattern in the Base Package)
513 +|**Value Domain**|(% style="width:754px" %)(((
514 +**Representation** (see the Structure
515 +
516 +Pattern in the Base Package)
490 490  )))
491 -|(% style="width:278px" %)**Enumerated Value Domain /
492 -Code List**|(% style="width:613px" %)**Codelist**
493 -|(% style="width:278px" %)**Code**|(% style="width:613px" %)(((
494 -**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
518 +|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
519 +|**Code**|(% style="width:754px" %)(((
520 +**Code** (for enumerated
521 +
522 +DimensionComponent, Measure, DataAttribute)
495 495  )))
496 -|(% style="width:278px" %)**Described Value Domain**|(% style="width:613px" %)(((
497 -non-enumerated** Representation **(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
524 +|**Described Value Domain**|(% style="width:754px" %)(((
525 +non-enumerated** Representation**
526 +
527 +(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
498 498  )))
499 -|(% style="width:278px" %)**Value**|(% style="width:613px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or to a valid **value **(for non-enumerated** **Representations)
500 -|(% style="width:278px" %)**Value Domain Subset / Set**|(% style="width:613px" %)This abstraction does not exist in SDMX
501 -|(% style="width:278px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:613px" %)This abstraction does not exist in SDMX
502 -|(% style="width:278px" %)**Described Value Domain Subset / Described Set**|(% style="width:613px" %)This abstraction does not exist in SDMX
503 -|(% style="width:278px" %)**Set list**|(% style="width:613px" %)This abstraction does not exist in SDMX
529 +|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
530 +| |(% style="width:754px" %)(((
531 +to a valid **value **(for non-enumerated** **Representations)
532 +)))
533 +|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
534 +|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
535 +|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
536 +|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
504 504  
505 505  The main difference between VTL and SDMX relies on the fact that the VTL artefacts for defining subsets of Value Domains do not exist in SDMX, therefore the VTL features for referring to predefined subsets are not available in SDMX. These artefacts are the Value Domain Subset (or Set), either enumerated or described, the Set List (list of values belonging to enumerated subsets) and the Data Set Component (aimed at defining the set of values that the Component of a Data Set can take, possibly a subset of the codes of Value Domain).
506 506  
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526 526  
527 527  The VTL data types are sub-divided in scalar types (like integers, strings, etc.), which are the types of the scalar values, and compound types (like Data Sets, Components, Rulesets, etc.), which are the types of the compound structures. See below the diagram of the VTL data types, taken from the VTL User Manual:
528 528  
529 -[[image:1747388434672-948.png]]
562 +[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
530 530  
531 531  (% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
532 532  **Figure 22 – VTL Data Types**
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535 535  
536 536  The VTL basic scalar types are listed below and follow a hierarchical structure in terms of supersets/subsets (e.g. "scalar" is the superset of all the basic scalar types):
537 537  
538 -[[image:1747388465321-274.png]]
539 539  
540 540  **Figure 23 – VTL Basic Scalar Types**
541 541  
574 +(((
575 +
576 +)))
577 +
542 542  === 12.4.2 VTL basic scalar types and SDMX data types ===
543 543  
544 544  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
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