Skip to Content
Last modified by Helena on 2025/09/10 11:19
From version 6.5
edited by Helena
on 2025/05/16 12:34
Change comment: There is no comment for this version
To version 6.12
edited by Helena
on 2025/05/16 12:41
Change comment: There is no comment for this version

Summary

Details

Page properties
Content
... ... @@ -414,14 +414,8 @@
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 -‘DF1(1.0.0)/POPULATION.USA’ :=
418 -DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
417 +[[image:1747388275998-621.png]]
419 419  
420 -‘DF1(1.0.0)/POPULATION.CANADA’ :=
421 -DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
422 -
423 -… … …
424 -
425 425  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}}
426 426  
427 427  In the direction from SDMX to VTL it is allowed to omit the value of one or more
... ... @@ -432,8 +432,7 @@
432 432  
433 433  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
434 434  
435 -‘DF1(1.0.0)/POPULATION.’ :=
436 -DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
429 +[[image:1747388244829-693.png]]
437 437  
438 438  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
439 439  
... ... @@ -460,51 +460,18 @@
460 460  
461 461  Some examples follow, for some specific values of INDICATOR and COUNTRY:
462 462  
463 -‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
456 +[[image:1747388222879-916.png]]
464 464  
465 -… … …
466 -‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
467 -‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
468 -… … …
458 +[[image:1747388206717-256.png]]
469 469  
470 470  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:
471 471  
472 -VTL dataset INDICATOR value COUNTRY value
462 +[[image:1747388148322-387.png]]
473 473  
474 -‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
475 -
476 -‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
477 -
478 -‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
479 -
480 -‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
481 -
482 -… … …
483 -
484 484  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:
485 485  
486 -DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
466 +[[image:1747388179021-814.png]]
487 487  
488 -DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
489 -
490 -DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
491 -
492 -[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
493 -
494 -DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
495 -
496 -DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
497 -
498 -DF2bis_GDPPERCAPITA_CANADA’,
499 -
500 -… ,
501 -
502 -DF2bis_POPGROWTH_USA’,
503 -
504 -DF2bis_POPGROWTH_CANADA’
505 -
506 -…);
507 -
508 508  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
509 509  
510 510  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.
... ... @@ -517,38 +517,30 @@
517 517  
518 518  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
519 519  
520 -(% style="width:1170.29px" %)
521 -|**VTL**|(% style="width:754px" %)**SDMX**
522 -|**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}}
523 -|**Represented Variable**|(% style="width:754px" %)(((
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" %)(((
524 524  **Concept** with a definite
525 525  
526 526  Representation
527 527  )))
528 -|**Value Domain**|(% style="width:754px" %)(((
529 -**Representation** (see the Structure
530 -
531 -Pattern in the Base Package)
488 +|(% style="width:278px" %)**Value Domain**|(% style="width:613px" %)(((
489 +**Representation** (see the Structure Pattern in the Base Package)
532 532  )))
533 -|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
534 -|**Code**|(% style="width:754px" %)(((
535 -**Code** (for enumerated
536 -
537 -DimensionComponent, Measure, DataAttribute)
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)
538 538  )))
539 -|**Described Value Domain**|(% style="width:754px" %)(((
540 -non-enumerated** Representation**
541 -
542 -(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
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)
543 543  )))
544 -|**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
545 -| |(% style="width:754px" %)(((
546 -to a valid **value **(for non-enumerated** **Representations)
547 -)))
548 -|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
549 -|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
550 -|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
551 -|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
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
552 552  
553 553  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).
554 554  
... ... @@ -574,7 +574,7 @@
574 574  
575 575  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:
576 576  
577 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
529 +[[image:1747388434672-948.png]]
578 578  
579 579  (% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
580 580  **Figure 22 – VTL Data Types**
... ... @@ -583,13 +583,10 @@
583 583  
584 584  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):
585 585  
538 +[[image:1747388465321-274.png]]
586 586  
587 587  **Figure 23 – VTL Basic Scalar Types**
588 588  
589 -(((
590 -
591 -)))
592 -
593 593  === 12.4.2 VTL basic scalar types and SDMX data types ===
594 594  
595 595  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
1747388148322-387.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +23.0 KB
Content
1747388179021-814.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +66.2 KB
Content
1747388206717-256.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +10.3 KB
Content
1747388222879-916.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +9.9 KB
Content
1747388244829-693.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +7.4 KB
Content
1747388275998-621.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +19.2 KB
Content
1747388434672-948.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +43.2 KB
Content
1747388465321-274.png
Author
... ... @@ -1,0 +1,1 @@
1 +XWiki.helena
Size
... ... @@ -1,0 +1,1 @@
1 +17.9 KB
Content