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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 7.1
edited by Helena
on 2025/05/16 12:43
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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
... ... @@ -408,26 +408,14 @@
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 -‘DF1(1.0.0)/POPULATION.USA’ :=
417 +[[image:1747388275998-621.png]]
422 422  
423 -DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
424 -
425 -‘DF1(1.0.0)/POPULATION.CANADA’ :=
426 -
427 -DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
428 -
429 -… … …
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}}
432 432  
433 433  In the direction from SDMX to VTL it is allowed to omit the value of one or more
... ... @@ -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.’ :=
429 +[[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;
456 +[[image:1747388222879-916.png]]
471 471  
472 -… … …
458 +[[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
462 +[[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”];
466 +[[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.
... ... @@ -527,38 +527,30 @@
527 527  
528 528  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
529 529  
530 -(% style="width:1170.29px" %)
531 -|**VTL**|(% style="width:754px" %)**SDMX**
532 -|**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}}
533 -|**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" %)(((
534 534  **Concept** with a definite
535 535  
536 536  Representation
537 537  )))
538 -|**Value Domain**|(% style="width:754px" %)(((
539 -**Representation** (see the Structure
540 -
541 -Pattern in the Base Package)
488 +|(% style="width:278px" %)**Value Domain**|(% style="width:613px" %)(((
489 +**Representation** (see the Structure Pattern in the Base Package)
542 542  )))
543 -|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
544 -|**Code**|(% style="width:754px" %)(((
545 -**Code** (for enumerated
546 -
547 -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)
548 548  )))
549 -|**Described Value Domain**|(% style="width:754px" %)(((
550 -non-enumerated** Representation**
551 -
552 -(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)
553 553  )))
554 -|**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
555 -| |(% style="width:754px" %)(((
556 -to a valid **value **(for non-enumerated** **Representations)
557 -)))
558 -|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
559 -|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
560 -|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
561 -|**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
562 562  
563 563  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).
564 564  
... ... @@ -584,7 +584,7 @@
584 584  
585 585  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:
586 586  
587 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
529 +[[image:1747388434672-948.png]]
588 588  
589 589  (% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
590 590  **Figure 22 – VTL Data Types**
... ... @@ -593,13 +593,10 @@
593 593  
594 594  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):
595 595  
538 +[[image:1747388465321-274.png]]
596 596  
597 597  **Figure 23 – VTL Basic Scalar Types**
598 598  
599 -(((
600 -
601 -)))
602 -
603 603  === 12.4.2 VTL basic scalar types and SDMX data types ===
604 604  
605 605  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
... ... @@ -813,53 +813,53 @@
813 813  
814 814  The custom output formats can be specified by means of the VTL formatting mask described in the section "Type Conversion and Formatting Mask" of the VTL Reference Manual. Such a section describes the masks for the VTL basic scalar types "number", "integer", "date", "time", "time_period" and "duration" and gives examples. As for the types "string" and "boolean" the VTL conventions are extended with some other special characters as described in the following table.
815 815  
816 -|(% colspan="2" %)VTL special characters for the formatting masks
817 -|(% colspan="2" %)
818 -|(% colspan="2" %)Number
819 -|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
820 -|E|one numeric digit (for the exponent of the scientific notation)
821 -|. (dot)|possible separator between the integer and the decimal parts.
822 -|, (comma)|possible separator between the integer and the decimal parts.
823 -| |
824 -|(% colspan="2" %)Time and duration
825 -|C|century
826 -|Y|year
827 -|S|semester
828 -|Q|quarter
829 -|M|month
830 -|W|week
831 -|D|day
832 -|h|hour digit (by default on 24 hours)
833 -|M|minute
834 -|S|second
835 -|D|decimal of second
836 -|P|period indicator (representation in one digit for the duration)
837 -|P|number of the periods specified in the period indicator
838 -|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
839 -|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
840 -|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
841 -|Month|lowercase textual representation of the month (e.g., january)
842 -|Day|lowercase textual representation of the month (e.g., monday)
843 -|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
844 -|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
845 -| |
846 -|(% colspan="2" %)String
847 -|X|any string character
848 -|Z|any string character from "A" to "z"
849 -|9|any string character from "0" to "9"
850 -| |
851 -|(% colspan="2" %)Boolean
852 -|B|Boolean using "true" for True and "false" for False
853 -|1|Boolean using "1" for True and "0" for False
854 -|0|Boolean using "0" for True and "1" for False
855 -| |
856 -|(% colspan="2" %)Other qualifiers
857 -|*|an arbitrary number of digits (of the preceding type)
858 -|+|at least one digit (of the preceding type)
859 -|( )|optional digits (specified within the brackets)
860 -|\|prefix for the special characters that must appear in the mask
861 -|N|fixed number of digits used in the preceding textual representation of the month or the day
862 -| |
755 +(% style="width:713.294px" %)
756 +|(% colspan="2" style="width:710px" %)VTL special characters for the formatting masks
757 +|(% colspan="2" style="width:710px" %)
758 +|(% colspan="2" style="width:710px" %)Number
759 +|D|(% style="width:486px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
760 +|E|(% style="width:486px" %)one numeric digit (for the exponent of the scientific notation)
761 +|. (dot)|(% style="width:486px" %)possible separator between the integer and the decimal parts.
762 +|, (comma)|(% style="width:486px" %)possible separator between the integer and the decimal parts.
763 +| |(% style="width:486px" %)
764 +|(% colspan="2" style="width:710px" %)Time and duration
765 +|C|(% style="width:486px" %)century
766 +|Y|(% style="width:486px" %)year
767 +|S|(% style="width:486px" %)semester
768 +|Q|(% style="width:486px" %)quarter
769 +|M|(% style="width:486px" %)month
770 +|W|(% style="width:486px" %)week
771 +|D|(% style="width:486px" %)day
772 +|h|(% style="width:486px" %)hour digit (by default on 24 hours)
773 +|M|(% style="width:486px" %)minute
774 +|S|(% style="width:486px" %)second
775 +|D|(% style="width:486px" %)decimal of second
776 +|P|(% style="width:486px" %)period indicator (representation in one digit for the duration)
777 +|P|(% style="width:486px" %)number of the periods specified in the period indicator
778 +|AM/PM|(% style="width:486px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
779 +|MONTH|(% style="width:486px" %)uppercase textual representation of the month (e.g., JANUARY for January)
780 +|DAY|(% style="width:486px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
781 +|Month|(% style="width:486px" %)lowercase textual representation of the month (e.g., january)
782 +|Day|(% style="width:486px" %)lowercase textual representation of the month (e.g., monday)
783 +|Month|(% style="width:486px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
784 +|Day|(% style="width:486px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
785 +| |(% style="width:486px" %)
786 +|(% colspan="2" style="width:710px" %)String
787 +|X|(% style="width:486px" %)any string character
788 +|Z|(% style="width:486px" %)any string character from "A" to "z"
789 +|9|(% style="width:486px" %)any string character from "0" to "9"
790 +| |(% style="width:486px" %)
791 +|(% colspan="2" style="width:710px" %)Boolean
792 +|B|(% style="width:486px" %)Boolean using "true" for True and "false" for False
793 +|1|(% style="width:486px" %)Boolean using "1" for True and "0" for False
794 +|0|(% style="width:486px" %)Boolean using "0" for True and "1" for False
795 +| |(% style="width:486px" %)
796 +|(% colspan="2" style="width:710px" %)Other qualifiers
797 +|*|(% style="width:486px" %)an arbitrary number of digits (of the preceding type)
798 +|+|(% style="width:486px" %)at least one digit (of the preceding type)
799 +|( )|(% style="width:486px" %)optional digits (specified within the brackets)
800 +|\|(% style="width:486px" %)prefix for the special characters that must appear in the mask
801 +|N|(% style="width:486px" %)fixed number of digits used in the preceding textual representation of the month or the day
863 863  
864 864  The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion{{footnote}}The representation given in the DSD should obviously be compatible with the VTL data type.{{/footnote}}.
865 865  
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