Last modified by Artur on 2025/09/10 11:19

From version 1.20
edited by Helena
on 2025/06/16 13:26
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To version 3.4
edited by Helena
on 2025/06/16 13:45
Change comment: There is no comment for this version

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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  
... ... @@ -235,16 +235,18 @@
235 235  * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
236 236  * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
237 237  ** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension;
238 -** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators). o Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship.
238 +** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators).
239 +** Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship.
239 239  
240 240  The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
241 241  
242 -|**SDMX**|**VTL**
243 -|Dimension|(Simple) Identifier
244 -|TimeDimension|(Time) Identifier
245 -|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension
246 -|DataAttribute not depending on the MeasureDimension|Attribute
247 -|DataAttribute depending on the MeasureDimension|(((
243 +(% style="width:739.294px" %)
244 +|(% style="width:335px" %)**SDMX**|(% style="width:400px" %)**VTL**
245 +|(% style="width:335px" %)Dimension|(% style="width:400px" %)(Simple) Identifier
246 +|(% style="width:335px" %)TimeDimension|(% style="width:400px" %)(Time) Identifier
247 +|(% style="width:335px" %)MeasureDimension & one Measure|(% style="width:400px" %)One Measure for each Code of the SDMX MeasureDimension
248 +|(% style="width:335px" %)DataAttribute not depending on the MeasureDimension|(% style="width:400px" %)Attribute
249 +|(% style="width:335px" %)DataAttribute depending on the MeasureDimension|(% style="width:400px" %)(((
248 248  One Attribute for each Code of the
249 249  SDMX MeasureDimension
250 250  )))
... ... @@ -254,19 +254,14 @@
254 254  At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
255 255  
256 256  * 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;
257 -* 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)
258 -
259 -Identifiers, (time) Identifier and Attributes.
260 -
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.
261 261  * 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
262 262  * 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
263 263  
264 264  ==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
265 265  
266 -* 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
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.
267 267  
268 -Attributes.
269 -
270 270  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.
271 271  
272 272  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.
... ... @@ -283,11 +283,12 @@
283 283  
284 284  Mapping table:
285 285  
286 -|**VTL**|**SDMX**
287 -|(Simple) Identifier|Dimension
288 -|(Time) Identifier|TimeDimension
289 -|Measure|Measure
290 -|Attribute|DataAttribute
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
291 291  
292 292  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.
293 293  
... ... @@ -315,11 +315,12 @@
315 315  
316 316  The summary mapping table of the **unpivot** mapping method is the following:
317 317  
318 -|**VTL**|**SDMX**
319 -|(Simple) Identifier|Dimension
320 -|(Time) Identifier|TimeDimension
321 -|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
322 -|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
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
323 323  
324 324  At observation / data point level:
325 325  
... ... @@ -341,12 +341,13 @@
341 341  
342 342  The mapping table is the following:
343 343  
344 -|VTL|SDMX
345 -|(Simple) Identifier|Dimension
346 -|(Time) Identifier|TimeDimension
347 -|Some Measures|Measure
348 -|Other Measures|DataAttribute
349 -|Attribute|DataAttribute
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
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'
387 +> '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’
391 +> ‘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  
... ... @@ -402,26 +402,22 @@
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.
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 …).
406 406  
407 -basic, pivot …).
408 -
409 409  In the example above, for all the datasets of the kind
410 410  
411 -‘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.
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.
412 412  
413 413  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:
414 414  
415 -‘DF1(1.0.0)/POPULATION.USA’ :=
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 +> … … …
416 416  
417 -DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
418 -
419 -‘DF1(1.0.0)/POPULATION.CANADA’ :=
420 -
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 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.
... ... @@ -430,10 +430,9 @@
430 430  
431 431  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
432 432  
433 -‘DF1(1.0.0)/POPULATION.’ :=
429 +> ‘DF1(1.0.0)/POPULATION.’ :=
430 +> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
434 434  
435 -DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
436 -
437 437  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
438 438  
439 439  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
... ... @@ -451,41 +451,33 @@
451 451  
452 452  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}}
453 453  
454 -‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
449 +> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
455 455  
456 456  Some examples follow, for some specific values of INDICATOR and COUNTRY:
457 457  
458 -‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
459 -… … …
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 +> … … …
460 460  
461 -‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
462 -‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
463 -… … …
464 -
465 465  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:
466 466  
467 -VTL dataset   INDICATOR value COUNTRY value
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 +> … … …
468 468  
469 -‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
470 -‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
471 -‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
472 -‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
473 -
474 -… … …
475 -
476 476  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:
477 477  
478 -DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
479 -DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
480 -DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
481 -[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
482 -DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
483 -DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
484 -DF2bis_GDPPERCAPITA_CANADA’,
485 -… ,
486 -DF2bis_POPGROWTH_USA’,
487 -DF2bis_POPGROWTH_CANADA’
488 -…);
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 +> …);
489 489  
490 490  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.
491 491  
... ... @@ -497,25 +497,26 @@
497 497  
498 498  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
499 499  
500 -|VTL|SDMX
501 -|**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^^
502 -|**Represented Variable**|**Concept** with a definite Representation
503 -|**Value Domain**|(((
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" %)(((
504 504  **Representation** (see the Structure
505 505  Pattern in the Base Package)
506 506  )))
507 -|**Enumerated Value Domain / Code List**|**Codelist**
508 -|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
509 -|**Described Value Domain**|(((
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" %)(((
510 510  non-enumerated** Representation**
511 511  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
512 512  )))
513 -|**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
514 -| |to a valid **value **(for non-enumerated** **Representations)
515 -|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
516 -|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
517 -|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
518 -|**Set list**|This abstraction does not exist in SDMX
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
519 519  
520 520  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).
521 521  
... ... @@ -523,8 +523,10 @@
523 523  
524 524  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
525 525  
526 -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.
514 +> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
527 527  
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 +
528 528  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
529 529  
530 530  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
... ... @@ -539,8 +539,9 @@
539 539  
540 540  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:
541 541  
542 -[[image:1750067055028-964.png]]
543 543  
533 +[[image:1750070288958-132.png]]
534 +
544 544  **Figure 22 – VTL Data Types**
545 545  
546 546  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.
... ... @@ -547,6 +547,8 @@
547 547  
548 548  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):
549 549  
541 +[[image:1750070310572-584.png]]
542 +
550 550  **Figure 23 – VTL Basic Scalar Types**
551 551  
552 552  === 12.4.2 VTL basic scalar types and SDMX data types ===
... ... @@ -571,158 +571,157 @@
571 571  
572 572  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
573 573  
574 -|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
575 -|(((
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" %)(((
576 576  String
577 577  (string allowing any character)
578 -)))|string
579 -|(((
580 -Alpha 
581 -
572 +)))|(% style="width:221px" %)string
573 +|(% style="width:360px" %)(((
574 +Alpha
582 582  (string which only allows A-z)
583 -)))|string
584 -|(((
576 +)))|(% style="width:221px" %)string
577 +|(% style="width:360px" %)(((
585 585  AlphaNumeric
586 586  (string which only allows A-z and 0-9)
587 -)))|string
588 -|(((
580 +)))|(% style="width:221px" %)string
581 +|(% style="width:360px" %)(((
589 589  Numeric
590 -
591 591  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
592 -)))|string
593 -|(((
584 +)))|(% style="width:221px" %)string
585 +|(% style="width:360px" %)(((
594 594  BigInteger
595 595  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
596 -)))|integer
597 -|(((
588 +)))|(% style="width:221px" %)integer
589 +|(% style="width:360px" %)(((
598 598  Integer
599 599  (corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
600 600  (inclusive))
601 -)))|integer
602 -|(((
593 +)))|(% style="width:221px" %)integer
594 +|(% style="width:360px" %)(((
603 603  Long
604 604  (corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
605 605  +9223372036854775807 (inclusive))
606 -)))|integer
607 -|(((
598 +)))|(% style="width:221px" %)integer
599 +|(% style="width:360px" %)(((
608 608  Short
609 609  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
610 -)))|integer
611 -|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
612 -|(((
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" %)(((
613 613  Float
614 614  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
615 -)))|number
616 -|(((
607 +)))|(% style="width:221px" %)number
608 +|(% style="width:360px" %)(((
617 617  Double
618 618  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
619 -)))|number
620 -|(((
611 +)))|(% style="width:221px" %)number
612 +|(% style="width:360px" %)(((
621 621  Boolean
622 622  (corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
623 623  binary-valued logic: {true, false})
624 -)))|boolean
625 -|(((
616 +)))|(% style="width:221px" %)boolean
617 +|(% style="width:360px" %)(((
626 626  URI
627 627  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
628 -)))|string
629 -|(((
620 +)))|(% style="width:221px" %)string
621 +|(% style="width:360px" %)(((
630 630  Count
631 631  (an integer following a sequential pattern, increasing by 1 for each occurrence)
632 -)))|integer
633 -|(((
624 +)))|(% style="width:221px" %)integer
625 +|(% style="width:360px" %)(((
634 634  InclusiveValueRange
635 635  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
636 -)))|number
637 -|(((
628 +)))|(% style="width:221px" %)number
629 +|(% style="width:360px" %)(((
638 638  ExclusiveValueRange
639 639  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
640 -)))|number
641 -|(((
632 +)))|(% style="width:221px" %)number
633 +|(% style="width:360px" %)(((
642 642  Incremental
643 643  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
644 -)))|number
645 -|(((
636 +)))|(% style="width:221px" %)number
637 +|(% style="width:360px" %)(((
646 646  ObservationalTimePeriod
647 647  (superset of StandardTimePeriod and TimeRange)
648 -)))|time
649 -|(((
640 +)))|(% style="width:221px" %)time
641 +|(% style="width:360px" %)(((
650 650  StandardTimePeriod
651 651  (superset of BasicTimePeriod and ReportingTimePeriod)
652 -)))|time
653 -|(((
644 +)))|(% style="width:221px" %)time
645 +|(% style="width:360px" %)(((
654 654  BasicTimePeriod
655 655  (superset of GregorianTimePeriod and DateTime)
656 -)))|date
657 -|(((
648 +)))|(% style="width:221px" %)date
649 +|(% style="width:360px" %)(((
658 658  GregorianTimePeriod
659 659  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
660 -)))|date
661 -|GregorianYear (YYYY)|date
662 -|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
663 -|GregorianDay (YYYY-MM-DD)|date
664 -|(((
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" %)(((
665 665  ReportingTimePeriod
666 666  (superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
667 -)))|time_period
668 -|(((
659 +)))|(% style="width:221px" %)time_period
660 +|(% style="width:360px" %)(((
669 669  ReportingYear
670 670  (YYYY-A1 – 1 year period)
671 -)))|time_period
672 -|(((
663 +)))|(% style="width:221px" %)time_period
664 +|(% style="width:360px" %)(((
673 673  ReportingSemester
674 674  (YYYY-Ss – 6 month period)
675 -)))|time_period
676 -|(((
667 +)))|(% style="width:221px" %)time_period
668 +|(% style="width:360px" %)(((
677 677  ReportingTrimester
678 678  (YYYY-Tt – 4 month period)
679 -)))|time_period
680 -|(((
671 +)))|(% style="width:221px" %)time_period
672 +|(% style="width:360px" %)(((
681 681  ReportingQuarter
682 682  (YYYY-Qq – 3 month period)
683 -)))|time_period
684 -|(((
675 +)))|(% style="width:221px" %)time_period
676 +|(% style="width:360px" %)(((
685 685  ReportingMonth
686 686  (YYYY-Mmm – 1 month period)
687 -)))|time_period
688 -|ReportingWeek|time_period
689 -| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
690 -|(((
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" %)(((
691 691  ReportingDay
692 692  (YYYY-Dddd – 1 day period)
693 -)))|time_period
694 -|(((
685 +)))|(% style="width:221px" %)time_period
686 +|(% style="width:360px" %)(((
695 695  DateTime
696 696  (YYYY-MM-DDThh:mm:ss)
697 -)))|date
698 -|(((
689 +)))|(% style="width:221px" %)date
690 +|(% style="width:360px" %)(((
699 699  TimeRange
700 700  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
701 -)))|time
702 -|(((
693 +)))|(% style="width:221px" %)time
694 +|(% style="width:360px" %)(((
703 703  Month
704 704  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
705 -)))|string
706 -|(((
697 +)))|(% style="width:221px" %)string
698 +|(% style="width:360px" %)(((
707 707  MonthDay
708 708  (~-~-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)
709 -)))|string
710 -|(((
701 +)))|(% style="width:221px" %)string
702 +|(% style="width:360px" %)(((
711 711  Day
712 712  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
713 -)))|string
714 -|(((
705 +)))|(% style="width:221px" %)string
706 +|(% style="width:360px" %)(((
715 715  Time
716 716  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
717 -)))|string
718 -|(((
709 +)))|(% style="width:221px" %)string
710 +|(% style="width:360px" %)(((
719 719  Duration
720 720  (corresponds to XML Schema xs:duration datatype)
721 -)))|duration
722 -|XHTML|Metadata type – not applicable
723 -|KeyValues|Metadata type – not applicable
724 -|IdentifiableReference|Metadata type – not applicable
725 -|DataSetReference|Metadata type – not applicable
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
726 726  
727 727  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
728 728  
... ... @@ -732,84 +732,82 @@
732 732  
733 733  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
734 734  
735 -|(((
736 -VTL basic
737 -scalar type
738 -)))|(((
727 +(% style="width:748.294px" %)
728 +|(% style="width:164px" %)(((
729 +VTL basic scalar type
730 +)))|(% style="width:304px" %)(((
739 739  Default SDMX data type
740 -(BasicComponentDataType
741 -)
742 -)))|Default output format
743 -|String|String|Like XML (xs:string)
744 -|Number|Float|Like XML (xs:float)
745 -|Integer|Integer|Like XML (xs:int)
746 -|Date|DateTime|YYYY-MM-DDT00:00:00Z
747 -|Time|StandardTimePeriod|<date>/<date> (as defined above)
748 -|time_period|(((
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" %)(((
749 749  ReportingTimePeriod
750 750  (StandardReportingPeriod)
751 -)))|(((
742 +)))|(% style="width:277px" %)(((
752 752   YYYY-Pppp
753 753  (according to SDMX )
754 754  )))
755 -|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
756 -|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
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"
757 757  
758 758  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
759 759  
760 -In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
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).
761 761  
762 -Transformations and Expressions of the SDMX information model).
763 -
764 764  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.
765 765  
766 -|(% colspan="2" %)VTL special characters for the formatting masks
767 -|(% colspan="2" %)
768 -|(% colspan="2" %)Number
769 -|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
770 -|E|one numeric digit (for the exponent of the scientific notation)
771 -|. (dot)|possible separator between the integer and the decimal parts.
772 -|, (comma)|possible separator between the integer and the decimal parts.
773 -| |
774 -|(% colspan="2" %)Time and duration
775 -|C|century
776 -|Y|year
777 -|S|semester
778 -|Q|quarter
779 -|M|month
780 -|W|week
781 -|D|day
782 -|h|hour digit (by default on 24 hours)
783 -|M|minute
784 -|S|second
785 -|D|decimal of second
786 -|P|period indicator (representation in one digit for the duration)
787 -|P|number of the periods specified in the period indicator
788 -|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
789 -|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
790 -|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
791 -|Month|lowercase textual representation of the month (e.g., january)
792 -|Day|lowercase textual representation of the month (e.g., monday)
793 -|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
794 -|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
795 -| |
796 -|(% colspan="2" %)String
797 -|X|any string character
798 -|Z|any string character from "A" to "z"
799 -|9|any string character from "0" to "9"
800 -| |
801 -|(% colspan="2" %)Boolean
802 -|B|Boolean using "true" for True and "false" for False
803 -|1|Boolean using "1" for True and "0" for False
804 -|0|Boolean using "0" for True and "1" for False
805 -| |
806 -|(% colspan="2" %)Other qualifiers
807 -|*|an arbitrary number of digits (of the preceding type)
808 -|+|at least one digit (of the preceding type)
809 -|( )|optional digits (specified within the brackets)
810 -|\|prefix for the special characters that must appear in the mask
811 -|N|fixed number of digits used in the preceding textual representation of the month or the day
812 -| |
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" %)
813 813  
814 814  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}}.
815 815  
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