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Last modified by Helena on 2025/09/10 11:19
From version 6.10
edited by Helena
on 2025/05/16 12:38
Change comment: There is no comment for this version
To version 6.3
edited by Helena
on 2025/05/16 12:31
Change comment: There is no comment for this version

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... ... @@ -255,7 +255,10 @@
255 255  At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
256 256  
257 257  * The set of SDMX observations having the same values for all the Dimensions except than the MeasureDimension become one multi-measure VTL Data Point, having one Measure for each Code Cj of the SDMX MeasureDimension;
258 -* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
258 +* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple)
259 +
260 +Identifiers, (time) Identifier and Attributes.
261 +
259 259  * The value of the Measure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj
260 260  * For the SDMX DataAttributes depending on the MeasureDimension, the value of the DataAttribute DA of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Attribute DA_Cj
261 261  
... ... @@ -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**
354 +|(% 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
... ... @@ -408,14 +408,26 @@
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 …).
414 +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.
416 +basic, pivot …).
414 414  
418 +In the example above, for all the datasets of the kind
419 +
420 +‘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.
421 +
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]]
424 +‘DF1(1.0.0)/POPULATION.USA’ :=
418 418  
426 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
427 +
428 +‘DF1(1.0.0)/POPULATION.CANADA’ :=
429 +
430 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
431 +
432 +… … …
433 +
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
... ... @@ -426,8 +426,10 @@
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]]
444 +‘DF1(1.0.0)/POPULATION.’ :=
430 430  
446 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
447 +
431 431  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
432 432  
433 433  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different
... ... @@ -453,18 +453,54 @@
453 453  
454 454  Some examples follow, for some specific values of INDICATOR and COUNTRY:
455 455  
456 -[[image:1747388222879-916.png]]
473 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
457 457  
458 -[[image:1747388206717-256.png]]
475 +… … …
459 459  
477 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
478 +
479 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
480 +
481 +… … …
482 +
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]]
485 +VTL dataset INDICATOR value COUNTRY value
463 463  
487 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
488 +
489 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
490 +
491 +‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
492 +
493 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
494 +
495 +… … …
496 +
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]]
499 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
467 467  
501 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
502 +
503 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
504 +
505 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
506 +
507 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
508 +
509 +DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
510 +
511 +DF2bis_GDPPERCAPITA_CANADA’,
512 +
513 +… ,
514 +
515 +DF2bis_POPGROWTH_USA’,
516 +
517 +DF2bis_POPGROWTH_CANADA’
518 +
519 +…);
520 +
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  
470 470  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.
... ... @@ -478,30 +478,37 @@
478 478  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
479 479  
480 480  (% style="width:1170.29px" %)
481 -|(% style="width:392px" %)**VTL**|(% style="width:776px" %)**SDMX**
482 -|(% style="width:392px" %)**Data Set Component**|(% style="width:776px" %)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:392px" %)**Represented Variable**|(% style="width:776px" %)(((
534 +|**VTL**|(% style="width:754px" %)**SDMX**
535 +|**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}}
536 +|**Represented Variable**|(% style="width:754px" %)(((
484 484  **Concept** with a definite
485 485  
486 486  Representation
487 487  )))
488 -|(% style="width:392px" %)**Value Domain**|(% style="width:776px" %)(((
489 -**Representation** (see the Structure Pattern in the Base Package)
541 +|**Value Domain**|(% style="width:754px" %)(((
542 +**Representation** (see the Structure
543 +
544 +Pattern in the Base Package)
490 490  )))
491 -|(% style="width:392px" %)**Enumerated Value Domain / Code List**|(% style="width:776px" %)**Codelist**
492 -|(% style="width:392px" %)**Code**|(% style="width:776px" %)(((
546 +|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
547 +|**Code**|(% style="width:754px" %)(((
493 493  **Code** (for enumerated
494 494  
495 495  DimensionComponent, Measure, DataAttribute)
496 496  )))
497 -|(% style="width:392px" %)**Described Value Domain**|(% style="width:776px" %)(((
498 -non-enumerated** Representation **(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
552 +|**Described Value Domain**|(% style="width:754px" %)(((
553 +non-enumerated** Representation**
554 +
555 +(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
499 499  )))
500 -|(% style="width:392px" %)**Value**|(% style="width:776px" %)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)
501 -|(% style="width:392px" %)**Value Domain Subset / Set**|(% style="width:776px" %)This abstraction does not exist in SDMX
502 -|(% style="width:392px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:776px" %)This abstraction does not exist in SDMX
503 -|(% style="width:392px" %)**Described Value Domain Subset / Described Set**|(% style="width:776px" %)This abstraction does not exist in SDMX
504 -|(% style="width:392px" %)**Set list**|(% style="width:776px" %)This abstraction does not exist in SDMX
557 +|**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
558 +| |(% style="width:754px" %)(((
559 +to a valid **value **(for non-enumerated** **Representations)
560 +)))
561 +|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
562 +|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
563 +|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
564 +|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
505 505  
506 506  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).
507 507  
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