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Last modified by Artur on 2025/09/10 11:19
From version 3.4
edited by Helena
on 2025/06/16 13:45
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To version 1.21
edited by Helena
on 2025/06/16 13:26
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... ... @@ -18,7 +18,7 @@
18 18  
19 19  This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts.
20 20  
21 -== 12.2 References to SDMX artefacts from VTL statements ==
21 +== 12.2 References to SDMX artefacts from VTL statements ==
22 22  
23 23  === 12.2.1 Introduction ===
24 24  
... ... @@ -116,7 +116,7 @@
116 116  
117 117  by omitting all the non-essential parts would become simply:
118 118  
119 -> DFR  : = DF1 + DF2
119 +> DFR  : =  DF1 + DF2
120 120  
121 121  The references to the Codelists can be simplified similarly. For example, given the non-abbreviated reference to the Codelist AG:CL_FREQ(1.0.0), which is{{footnote}}Single quotes are needed because this reference is not a VTL regular name. 19 Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}:
122 122  
... ... @@ -256,14 +256,19 @@
256 256  At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
257 257  
258 258  * 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;
259 -* 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.
259 +* 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)
260 +
261 +Identifiers, (time) Identifier and Attributes.
262 +
260 260  * 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
261 261  * 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
262 262  
263 263  ==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
264 264  
265 -* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain Attributes.
268 +* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain
266 266  
270 +Attributes.
271 +
267 267  The Basic_A2M and Pivot_A2M behaves respectively like the Basic and Pivot methods, except that the final VTL components, which according to the Basic and Pivot methods would have had the role of Attribute, assume instead the role of Measure.
268 268  
269 269  Proper VTL features allow changing the role of specific attributes even after the SDMX to VTL mapping: they can be useful when only some of the DataAttributes need to be managed as VTL Measures.
... ... @@ -280,12 +280,11 @@
280 280  
281 281  Mapping table:
282 282  
283 -(% style="width:470.294px" %)
284 -|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX**
285 -|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension
286 -|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension
287 -|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure
288 -|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute
288 +|**VTL**|**SDMX**
289 +|(Simple) Identifier|Dimension
290 +|(Time) Identifier|TimeDimension
291 +|Measure|Measure
292 +|Attribute|DataAttribute
289 289  
290 290  If the distinction between simple identifier and time identifier is not maintained in the VTL environment, the classification between Dimension and TimeDimension exists only in SDMX, as declared in the relevant DataStructureDefinition.
291 291  
... ... @@ -313,12 +313,11 @@
313 313  
314 314  The summary mapping table of the **unpivot** mapping method is the following:
315 315  
316 -(% style="width:638.294px" %)
317 -|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX**
318 -|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension
319 -|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension
320 -|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
321 -|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
320 +|**VTL**|**SDMX**
321 +|(Simple) Identifier|Dimension
322 +|(Time) Identifier|TimeDimension
323 +|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
324 +|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
322 322  
323 323  At observation / data point level:
324 324  
... ... @@ -340,13 +340,12 @@
340 340  
341 341  The mapping table is the following:
342 342  
343 -(% style="width:467.294px" %)
344 -|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
345 -|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
346 -|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
347 -|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
348 -|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
349 -|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
346 +|VTL|SDMX
347 +|(Simple) Identifier|Dimension
348 +|(Time) Identifier|TimeDimension
349 +|Some Measures|Measure
350 +|Other Measures|DataAttribute
351 +|Attribute|DataAttribute
350 350  
351 351  Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the attributeRelationship for the DataAttributes, which does not exist in VTL.
352 352  
... ... @@ -384,11 +384,11 @@
384 384  
385 385  Therefore, the generic name of this kind of VTL datasets would be:
386 386  
387 -> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
389 +'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
388 388  
389 389  Where DF(1.0.0) is the Dataflow and //INDICATORvalue// and //COUNTRYvalue //are placeholders for one value of the INDICATOR and COUNTRY dimensions. Instead the specific name of one of these VTL datasets would be:
390 390  
391 -> ‘DF(1.0.0)/POPULATION.USA’
393 +‘DF(1.0.0)/POPULATION.USA’
392 392  
393 393  In particular, this is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA.
394 394  
... ... @@ -402,22 +402,26 @@
402 402  
403 403  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.
404 404  
405 -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 …).
407 +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.
406 406  
409 +basic, pivot …).
410 +
407 407  In the example above, for all the datasets of the kind
408 408  
409 -> ‘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.
413 +‘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.
410 410  
411 411  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:
412 412  
413 -> ‘DF1(1.0.0)/POPULATION.USA’ :=
414 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
415 ->
416 -> ‘DF1(1.0.0)/POPULATION.CANADA’ :=
417 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
418 ->
419 -> … … …
417 +‘DF1(1.0.0)/POPULATION.USA’ :=
420 420  
419 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
420 +
421 +‘DF1(1.0.0)/POPULATION.CANADA’ :=
422 +
423 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
424 +
425 +… … …
426 +
421 421  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}}
422 422  
423 423  In the direction from SDMX to VTL it is allowed to omit the value of one or more DimensionComponents on which the mapping is based, but maintaining all the separating dots (therefore it may happen to find two or more consecutive dots and dots in the beginning or in the end). The absence of value means that for the corresponding Dimension all the values are kept and the Dimension is not dropped.
... ... @@ -426,9 +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 -> ‘DF1(1.0.0)/POPULATION.’ :=
430 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
435 +‘DF1(1.0.0)/POPULATION.’ :=
431 431  
437 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
438 +
432 432  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
433 433  
434 434  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
... ... @@ -446,33 +446,41 @@
446 446  
447 447  The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:{{footnote}}the symbol of the VTL persistent assignment is used (<-){{/footnote}}
448 448  
449 -> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
456 +‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
450 450  
451 451  Some examples follow, for some specific values of INDICATOR and COUNTRY:
452 452  
453 -> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
454 -> … … …
455 -> ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
456 -> ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
457 -> … … …
460 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
461 +… … …
458 458  
463 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
464 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
465 +… … …
466 +
459 459  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:
460 460  
461 -> VTL dataset  INDICATOR value COUNTRY value
462 ->
463 -> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
464 -> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
465 ->
466 -> ‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
467 -> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
468 -> … … …
469 +VTL dataset   INDICATOR value COUNTRY value
469 469  
471 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
472 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
473 +‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
474 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
475 +
476 +… … …
477 +
470 470  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:
471 471  
472 -> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”];… … … DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’  [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”];… … … DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’, DF2bis_GDPPERCAPITA_CANADA’,
473 -> … ,
474 -> DF2bis_POPGROWTH_USA’, DF2bis_POPGROWTH_CANADA’
475 -> …);
480 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
481 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
482 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
483 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
484 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
485 +DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
486 +DF2bis_GDPPERCAPITA_CANADA’,
487 +… ,
488 +DF2bis_POPGROWTH_USA’,
489 +DF2bis_POPGROWTH_CANADA’
490 +…);
476 476  
477 477  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 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.
478 478  
... ... @@ -484,26 +484,25 @@
484 484  
485 485  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
486 486  
487 -(% style="width:706.294px" %)
488 -|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX
489 -|(% style="width:257px" %)**Data Set Component**|(% style="width:446px" %)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^^43^^
490 -|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation
491 -|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)(((
502 +|VTL|SDMX
503 +|**Data Set Component**|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^^43^^
504 +|**Represented Variable**|**Concept** with a definite Representation
505 +|**Value Domain**|(((
492 492  **Representation** (see the Structure
493 493  Pattern in the Base Package)
494 494  )))
495 -|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
496 -|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
497 -|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
509 +|**Enumerated Value Domain / Code List**|**Codelist**
510 +|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
511 +|**Described Value Domain**|(((
498 498  non-enumerated** Representation**
499 499  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
500 500  )))
501 -|(% style="width:257px" %)**Value**|(% style="width:446px" %)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
502 -|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)
503 -|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
504 -|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
505 -|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
506 -|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX
515 +|**Value**|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
516 +| |to a valid **value **(for non-enumerated** **Representations)
517 +|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
518 +|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
519 +|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
520 +|**Set list**|This abstraction does not exist in SDMX
507 507  
508 508  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).
509 509  
... ... @@ -511,10 +511,8 @@
511 511  
512 512  Therefore, it is important to be aware that some VTL operations (for example the binary operations at data set level) are consistent only if the components having the same names in the operated VTL Data Sets have also the same representation (i.e. the same Value Domain as for VTL). For example, it is possible to obtain correct results from the VTL expression
513 513  
514 -> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
528 +DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
515 515  
516 -if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
517 -
518 518  As mentioned, the property above is not enforced by construction in SDMX, and different representations of the same Concept can be not compatible one another (for example, it may happen that geo_area is represented by ISO-alpha-3 codes in DS_a and by ISO alpha-2 codes in DS_b). Therefore, it will be up to the definer of VTL
519 519  
520 520  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
... ... @@ -529,9 +529,8 @@
529 529  
530 530  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:
531 531  
544 +[[image:1750067055028-964.png]]
532 532  
533 -[[image:1750070288958-132.png]]
534 -
535 535  **Figure 22 – VTL Data Types**
536 536  
537 537  The VTL scalar types are in turn subdivided in basic scalar types, which are elementary (not defined in term of other data types) and Value Domain and Set scalar types, which are defined in terms of the basic scalar types.
... ... @@ -538,8 +538,6 @@
538 538  
539 539  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):
540 540  
541 -[[image:1750070310572-584.png]]
542 -
543 543  **Figure 23 – VTL Basic Scalar Types**
544 544  
545 545  === 12.4.2 VTL basic scalar types and SDMX data types ===
... ... @@ -564,157 +564,158 @@
564 564  
565 565  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
566 566  
567 -(% style="width:583.294px" %)
568 -|(% style="width:360px" %)SDMX data type (BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type
569 -|(% style="width:360px" %)(((
576 +|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
577 +|(((
570 570  String
571 571  (string allowing any character)
572 -)))|(% style="width:221px" %)string
573 -|(% style="width:360px" %)(((
574 -Alpha
580 +)))|string
581 +|(((
582 +Alpha 
583 +
575 575  (string which only allows A-z)
576 -)))|(% style="width:221px" %)string
577 -|(% style="width:360px" %)(((
585 +)))|string
586 +|(((
578 578  AlphaNumeric
579 579  (string which only allows A-z and 0-9)
580 -)))|(% style="width:221px" %)string
581 -|(% style="width:360px" %)(((
589 +)))|string
590 +|(((
582 582  Numeric
592 +
583 583  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
584 -)))|(% style="width:221px" %)string
585 -|(% style="width:360px" %)(((
594 +)))|string
595 +|(((
586 586  BigInteger
587 587  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
588 -)))|(% style="width:221px" %)integer
589 -|(% style="width:360px" %)(((
598 +)))|integer
599 +|(((
590 590  Integer
591 591  (corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
592 592  (inclusive))
593 -)))|(% style="width:221px" %)integer
594 -|(% style="width:360px" %)(((
603 +)))|integer
604 +|(((
595 595  Long
596 596  (corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
597 597  +9223372036854775807 (inclusive))
598 -)))|(% style="width:221px" %)integer
599 -|(% style="width:360px" %)(((
608 +)))|integer
609 +|(((
600 600  Short
601 601  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
602 -)))|(% style="width:221px" %)integer
603 -|(% style="width:360px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:221px" %)number
604 -|(% style="width:360px" %)(((
612 +)))|integer
613 +|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
614 +|(((
605 605  Float
606 606  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
607 -)))|(% style="width:221px" %)number
608 -|(% style="width:360px" %)(((
617 +)))|number
618 +|(((
609 609  Double
610 610  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
611 -)))|(% style="width:221px" %)number
612 -|(% style="width:360px" %)(((
621 +)))|number
622 +|(((
613 613  Boolean
614 614  (corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
615 615  binary-valued logic: {true, false})
616 -)))|(% style="width:221px" %)boolean
617 -|(% style="width:360px" %)(((
626 +)))|boolean
627 +|(((
618 618  URI
619 619  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
620 -)))|(% style="width:221px" %)string
621 -|(% style="width:360px" %)(((
630 +)))|string
631 +|(((
622 622  Count
623 623  (an integer following a sequential pattern, increasing by 1 for each occurrence)
624 -)))|(% style="width:221px" %)integer
625 -|(% style="width:360px" %)(((
634 +)))|integer
635 +|(((
626 626  InclusiveValueRange
627 627  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
628 -)))|(% style="width:221px" %)number
629 -|(% style="width:360px" %)(((
638 +)))|number
639 +|(((
630 630  ExclusiveValueRange
631 631  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
632 -)))|(% style="width:221px" %)number
633 -|(% style="width:360px" %)(((
642 +)))|number
643 +|(((
634 634  Incremental
635 635  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
636 -)))|(% style="width:221px" %)number
637 -|(% style="width:360px" %)(((
646 +)))|number
647 +|(((
638 638  ObservationalTimePeriod
639 639  (superset of StandardTimePeriod and TimeRange)
640 -)))|(% style="width:221px" %)time
641 -|(% style="width:360px" %)(((
650 +)))|time
651 +|(((
642 642  StandardTimePeriod
643 643  (superset of BasicTimePeriod and ReportingTimePeriod)
644 -)))|(% style="width:221px" %)time
645 -|(% style="width:360px" %)(((
654 +)))|time
655 +|(((
646 646  BasicTimePeriod
647 647  (superset of GregorianTimePeriod and DateTime)
648 -)))|(% style="width:221px" %)date
649 -|(% style="width:360px" %)(((
658 +)))|date
659 +|(((
650 650  GregorianTimePeriod
651 651  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
652 -)))|(% style="width:221px" %)date
653 -|(% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date
654 -|(% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date
655 -|(% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date
656 -|(% style="width:360px" %)(((
662 +)))|date
663 +|GregorianYear (YYYY)|date
664 +|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
665 +|GregorianDay (YYYY-MM-DD)|date
666 +|(((
657 657  ReportingTimePeriod
658 658  (superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
659 -)))|(% style="width:221px" %)time_period
660 -|(% style="width:360px" %)(((
669 +)))|time_period
670 +|(((
661 661  ReportingYear
662 662  (YYYY-A1 – 1 year period)
663 -)))|(% style="width:221px" %)time_period
664 -|(% style="width:360px" %)(((
673 +)))|time_period
674 +|(((
665 665  ReportingSemester
666 666  (YYYY-Ss – 6 month period)
667 -)))|(% style="width:221px" %)time_period
668 -|(% style="width:360px" %)(((
677 +)))|time_period
678 +|(((
669 669  ReportingTrimester
670 670  (YYYY-Tt – 4 month period)
671 -)))|(% style="width:221px" %)time_period
672 -|(% style="width:360px" %)(((
681 +)))|time_period
682 +|(((
673 673  ReportingQuarter
674 674  (YYYY-Qq – 3 month period)
675 -)))|(% style="width:221px" %)time_period
676 -|(% style="width:360px" %)(((
685 +)))|time_period
686 +|(((
677 677  ReportingMonth
678 678  (YYYY-Mmm – 1 month period)
679 -)))|(% style="width:221px" %)time_period
680 -|(% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period
681 -|(% style="width:360px" %) (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% style="width:221px" %)
682 -|(% style="width:360px" %)(((
689 +)))|time_period
690 +|ReportingWeek|time_period
691 +| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
692 +|(((
683 683  ReportingDay
684 684  (YYYY-Dddd – 1 day period)
685 -)))|(% style="width:221px" %)time_period
686 -|(% style="width:360px" %)(((
695 +)))|time_period
696 +|(((
687 687  DateTime
688 688  (YYYY-MM-DDThh:mm:ss)
689 -)))|(% style="width:221px" %)date
690 -|(% style="width:360px" %)(((
699 +)))|date
700 +|(((
691 691  TimeRange
692 692  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
693 -)))|(% style="width:221px" %)time
694 -|(% style="width:360px" %)(((
703 +)))|time
704 +|(((
695 695  Month
696 696  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
697 -)))|(% style="width:221px" %)string
698 -|(% style="width:360px" %)(((
707 +)))|string
708 +|(((
699 699  MonthDay
700 700  (~-~-MM-DD; specifies a day within a month independent of a year; e.g. Christmas is December 25^^th^^; used to specify reporting year start day)
701 -)))|(% style="width:221px" %)string
702 -|(% style="width:360px" %)(((
711 +)))|string
712 +|(((
703 703  Day
704 704  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
705 -)))|(% style="width:221px" %)string
706 -|(% style="width:360px" %)(((
715 +)))|string
716 +|(((
707 707  Time
708 708  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
709 -)))|(% style="width:221px" %)string
710 -|(% style="width:360px" %)(((
719 +)))|string
720 +|(((
711 711  Duration
712 712  (corresponds to XML Schema xs:duration datatype)
713 -)))|(% style="width:221px" %)duration
714 -|(% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable
715 -|(% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable
716 -|(% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable
717 -|(% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable
723 +)))|duration
724 +|XHTML|Metadata type – not applicable
725 +|KeyValues|Metadata type – not applicable
726 +|IdentifiableReference|Metadata type – not applicable
727 +|DataSetReference|Metadata type – not applicable
718 718  
719 719  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
720 720  
... ... @@ -724,82 +724,84 @@
724 724  
725 725  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
726 726  
727 -(% style="width:748.294px" %)
728 -|(% style="width:164px" %)(((
729 -VTL basic scalar type
730 -)))|(% style="width:304px" %)(((
737 +|(((
738 +VTL basic
739 +scalar type
740 +)))|(((
731 731  Default SDMX data type
732 -(BasicComponentDataType)
733 -)))|(% style="width:277px" %)Default output format
734 -|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string)
735 -|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float)
736 -|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int)
737 -|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z
738 -|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above)
739 -|(% style="width:164px" %)time_period|(% style="width:304px" %)(((
742 +(BasicComponentDataType
743 +)
744 +)))|Default output format
745 +|String|String|Like XML (xs:string)
746 +|Number|Float|Like XML (xs:float)
747 +|Integer|Integer|Like XML (xs:int)
748 +|Date|DateTime|YYYY-MM-DDT00:00:00Z
749 +|Time|StandardTimePeriod|<date>/<date> (as defined above)
750 +|time_period|(((
740 740  ReportingTimePeriod
741 741  (StandardReportingPeriod)
742 -)))|(% style="width:277px" %)(((
753 +)))|(((
743 743   YYYY-Pppp
744 744  (according to SDMX )
745 745  )))
746 -|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS
747 -|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"
757 +|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
758 +|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
748 748  
749 749  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
750 750  
751 -In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
762 +In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
752 752  
764 +Transformations and Expressions of the SDMX information model).
765 +
753 753  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.
754 754  
755 -(% style="width:717.294px" %)
756 -|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks
757 -|(% colspan="2" style="width:714px" %)
758 -|(% colspan="2" style="width:714px" %)Number
759 -|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
760 -|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation)
761 -|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
762 -|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
763 -|(% style="width:122px" %) |(% style="width:591px" %)
764 -|(% colspan="2" style="width:714px" %)Time and duration
765 -|(% style="width:122px" %)C|(% style="width:591px" %)century
766 -|(% style="width:122px" %)Y|(% style="width:591px" %)year
767 -|(% style="width:122px" %)S|(% style="width:591px" %)semester
768 -|(% style="width:122px" %)Q|(% style="width:591px" %)quarter
769 -|(% style="width:122px" %)M|(% style="width:591px" %)month
770 -|(% style="width:122px" %)W|(% style="width:591px" %)week
771 -|(% style="width:122px" %)D|(% style="width:591px" %)day
772 -|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours)
773 -|(% style="width:122px" %)M|(% style="width:591px" %)minute
774 -|(% style="width:122px" %)S|(% style="width:591px" %)second
775 -|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second
776 -|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration)
777 -|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator
778 -|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
779 -|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January)
780 -|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
781 -|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january)
782 -|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday)
783 -|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
784 -|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
785 -|(% style="width:122px" %) |(% style="width:591px" %)
786 -|(% colspan="2" style="width:714px" %)String
787 -|(% style="width:122px" %)X|(% style="width:591px" %)any string character
788 -|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z"
789 -|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9"
790 -|(% style="width:122px" %) |(% style="width:591px" %)
791 -|(% colspan="2" style="width:714px" %)Boolean
792 -|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False
793 -|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False
794 -|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False
795 -|(% style="width:122px" %) |(% style="width:591px" %)
796 -|(% colspan="2" style="width:714px" %)Other qualifiers
797 -|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type)
798 -|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type)
799 -|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets)
800 -|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask
801 -|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day
802 -|(% style="width:122px" %) |(% style="width:591px" %)
768 +|(% colspan="2" %)VTL special characters for the formatting masks
769 +|(% colspan="2" %)
770 +|(% colspan="2" %)Number
771 +|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
772 +|E|one numeric digit (for the exponent of the scientific notation)
773 +|. (dot)|possible separator between the integer and the decimal parts.
774 +|, (comma)|possible separator between the integer and the decimal parts.
775 +| |
776 +|(% colspan="2" %)Time and duration
777 +|C|century
778 +|Y|year
779 +|S|semester
780 +|Q|quarter
781 +|M|month
782 +|W|week
783 +|D|day
784 +|h|hour digit (by default on 24 hours)
785 +|M|minute
786 +|S|second
787 +|D|decimal of second
788 +|P|period indicator (representation in one digit for the duration)
789 +|P|number of the periods specified in the period indicator
790 +|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
791 +|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
792 +|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
793 +|Month|lowercase textual representation of the month (e.g., january)
794 +|Day|lowercase textual representation of the month (e.g., monday)
795 +|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
796 +|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
797 +| |
798 +|(% colspan="2" %)String
799 +|X|any string character
800 +|Z|any string character from "A" to "z"
801 +|9|any string character from "0" to "9"
802 +| |
803 +|(% colspan="2" %)Boolean
804 +|B|Boolean using "true" for True and "false" for False
805 +|1|Boolean using "1" for True and "0" for False
806 +|0|Boolean using "0" for True and "1" for False
807 +| |
808 +|(% colspan="2" %)Other qualifiers
809 +|*|an arbitrary number of digits (of the preceding type)
810 +|+|at least one digit (of the preceding type)
811 +|( )|optional digits (specified within the brackets)
812 +|\|prefix for the special characters that must appear in the mask
813 +|N|fixed number of digits used in the preceding textual representation of the month or the day
814 +| |
803 803  
804 804  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}}.
805 805  
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