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

From version 7.1
edited by Helena
on 2025/05/16 12:43
Change comment: There is no comment for this version
To version 5.21
edited by Helena
on 2025/05/16 08:58
Change comment: There is no comment for this version

Summary

Details

Page properties
Content
... ... @@ -14,8 +14,10 @@
14 14  
15 15  The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate{{footnote}}In this chapter, in order to distinguish VTL and SDMX model artefacts, the VTL ones are written in the Arial font while the SDMX ones in Courier New{{/footnote}}. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of Transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL "Data Set", which do not correspond one another: as a matter of fact, the VTL "Data Set" maps to the SDMX "Dataflow", while the SDMX "Dataset" has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL Transformations). A SDMX "Dataset", however, is an instance of a SDMX "Dataflow" and can be the artefact on which the VTL transformations are executed (i.e., the Transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
16 16  
17 -The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
17 +The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of
18 18  
19 +Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
20 +
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 21  == 12.2 References to SDMX artefacts from VTL statements ==
... ... @@ -26,8 +26,10 @@
26 26  
27 27  The alias of an SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name.
28 28  
29 -In any case, the aliases used in the VTL Transformations have to be mapped to the SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
31 +In any case, the aliases used in the VTL Transformations have to be mapped to the
30 30  
33 +SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
34 +
31 31  The correspondence between an alias and a SDMX artefact must be one-to-one, meaning that a generic alias identifies one and just one SDMX artefact while a SDMX artefact is identified by one and just one alias. In other words, within a VtlMappingScheme an artefact can have just one alias and different artefacts cannot have the same alias.
32 32  
33 33  The references through the URN and the abbreviated URN are described in the following paragraphs.
... ... @@ -198,7 +198,7 @@
198 198  
199 199  === 12.3.3 Mapping from SDMX to VTL data structures ===
200 200  
201 -==== 12.3.3.1 Basic Mapping ====
205 +**12.3.3.1 Basic Mapping**
202 202  
203 203  The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes. When transforming **from SDMX to VTL**, this method consists in leaving the components unchanged and maintaining their names and roles, according to the following table:
204 204  
... ... @@ -228,11 +228,18 @@
228 228  The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation):
229 229  
230 230  * A SDMX simple dimension becomes a VTL (simple) identifier and a SDMX TimeDimension becomes a VTL (time) identifier;
231 -* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a Component;
235 +* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a
236 +
237 +Component;
238 +
232 232  * The SDMX MeasureDimension is not mapped to VTL (it disappears in the VTL Data Structure);
233 233  * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
234 234  * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
235 -** 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;
242 +** 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
243 +
244 +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;
245 +
246 +*
236 236  ** 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).
237 237  ** 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.
238 238  
... ... @@ -255,7 +255,10 @@
255 255  At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
256 256  
257 257  * The set of SDMX observations having the same values for all the Dimensions except than the MeasureDimension become one multi-measure VTL Data Point, having one Measure for each Code Cj of the SDMX MeasureDimension;
258 -* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
269 +* 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)
270 +
271 +Identifiers, (time) Identifier and Attributes.
272 +
259 259  * The value of the Measure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj
260 260  * For the SDMX DataAttributes depending on the MeasureDimension, the value of the DataAttribute DA of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Attribute DA_Cj
261 261  
... ... @@ -348,7 +348,7 @@
348 348  The mapping table is the following:
349 349  
350 350  (% style="width:689.294px" %)
351 -|(% style="width:344px" %)**VTL**|(% style="width:341px" %)**SDMX**
365 +|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX
352 352  |(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension
353 353  |(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension
354 354  |(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure
... ... @@ -408,14 +408,26 @@
408 408  
409 409  SDMX Dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=// COUNTRYvalue//. For example, the VTL dataset ‘DF1(1.0.0)/POPULATION.USA’ would contain all the observations of DF1(1.0.0) having INDICATOR = POPULATION and COUNTRY = USA.
410 410  
411 -In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
425 +In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
412 412  
413 -In the example above, for all the datasets of the kind ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
427 +basic, pivot …).
414 414  
429 +In the example above, for all the datasets of the kind
430 +
431 +‘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.
432 +
415 415  It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression:
416 416  
417 -[[image:1747388275998-621.png]]
435 +‘DF1(1.0.0)/POPULATION.USA’ :=
418 418  
437 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
438 +
439 +‘DF1(1.0.0)/POPULATION.CANADA’ :=
440 +
441 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
442 +
443 +… … …
444 +
419 419  In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}}
420 420  
421 421  In the direction from SDMX to VTL it is allowed to omit the value of one or more
... ... @@ -426,8 +426,10 @@
426 426  
427 427  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
428 428  
429 -[[image:1747388244829-693.png]]
455 +‘DF1(1.0.0)/POPULATION.’ :=
430 430  
457 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
458 +
431 431  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
432 432  
433 433  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different
... ... @@ -453,18 +453,54 @@
453 453  
454 454  Some examples follow, for some specific values of INDICATOR and COUNTRY:
455 455  
456 -[[image:1747388222879-916.png]]
484 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
457 457  
458 -[[image:1747388206717-256.png]]
486 +… … …
459 459  
488 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
489 +
490 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
491 +
492 +… … …
493 +
460 460  As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively:
461 461  
462 -[[image:1747388148322-387.png]]
496 +VTL dataset INDICATOR value COUNTRY value
463 463  
498 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
499 +
500 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
501 +
502 +‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
503 +
504 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
505 +
506 +… … …
507 +
464 464  It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be:
465 465  
466 -[[image:1747388179021-814.png]]
510 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
467 467  
512 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
513 +
514 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
515 +
516 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
517 +
518 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
519 +
520 +DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
521 +
522 +DF2bis_GDPPERCAPITA_CANADA’,
523 +
524 +… ,
525 +
526 +DF2bis_POPGROWTH_USA’,
527 +
528 +DF2bis_POPGROWTH_CANADA’
529 +
530 +…);
531 +
468 468  In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example
469 469  
470 470  DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
... ... @@ -477,43 +477,51 @@
477 477  
478 478  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
479 479  
480 -(% style="width:895.294px" %)
481 -|(% style="width:278px" %)**VTL**|(% style="width:613px" %)**SDMX**
482 -|(% style="width:278px" %)**Data Set Component**|(% style="width:613px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
483 -|(% style="width:278px" %)**Represented Variable**|(% style="width:613px" %)(((
544 +(% style="width:1170.29px" %)
545 +|**VTL**|(% style="width:754px" %)**SDMX**
546 +|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
547 +|**Represented Variable**|(% style="width:754px" %)(((
484 484  **Concept** with a definite
485 485  
486 486  Representation
487 487  )))
488 -|(% style="width:278px" %)**Value Domain**|(% style="width:613px" %)(((
489 -**Representation** (see the Structure Pattern in the Base Package)
552 +|**Value Domain**|(% style="width:754px" %)(((
553 +**Representation** (see the Structure
554 +
555 +Pattern in the Base Package)
490 490  )))
491 -|(% style="width:278px" %)**Enumerated Value Domain /
492 -Code List**|(% style="width:613px" %)**Codelist**
493 -|(% style="width:278px" %)**Code**|(% style="width:613px" %)(((
494 -**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
557 +|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
558 +|**Code**|(% style="width:754px" %)(((
559 +**Code** (for enumerated
560 +
561 +DimensionComponent, Measure, DataAttribute)
495 495  )))
496 -|(% style="width:278px" %)**Described Value Domain**|(% style="width:613px" %)(((
497 -non-enumerated** Representation **(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
563 +|**Described Value Domain**|(% style="width:754px" %)(((
564 +non-enumerated** Representation**
565 +
566 +(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
498 498  )))
499 -|(% style="width:278px" %)**Value**|(% style="width:613px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or to a valid **value **(for non-enumerated** **Representations)
500 -|(% style="width:278px" %)**Value Domain Subset / Set**|(% style="width:613px" %)This abstraction does not exist in SDMX
501 -|(% style="width:278px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:613px" %)This abstraction does not exist in SDMX
502 -|(% style="width:278px" %)**Described Value Domain Subset / Described Set**|(% style="width:613px" %)This abstraction does not exist in SDMX
503 -|(% style="width:278px" %)**Set list**|(% style="width:613px" %)This abstraction does not exist in SDMX
568 +|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
569 +| |(% style="width:754px" %)(((
570 +to a valid **value **(for non-enumerated** **Representations)
571 +)))
572 +|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
573 +|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
574 +|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
575 +|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
504 504  
505 505  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).
506 506  
507 -Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear{{footnote}}By using represented variables, VTL can assume that data structures having the same variables as identifiers can be composed one another because the correspondent values can match.{{/footnote}}, while the SDMX Concepts can have different Representations in different DataStructures.{{footnote}}A Concept becomes a Component in a DataStructureDefinition, and Components can have different LocalRepresentations in different DataStructureDefinitions, also overriding the (possible) base representation of the Concept.{{/footnote}} This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
579 +Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^40^^>>path:#sdfootnote40sym||name="sdfootnote40anc"]](%%)^^, while the SDMX Concepts can have different Representations in different DataStructures.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
508 508  
509 509  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
510 510  
511 -DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
583 +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.
512 512  
513 -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 -
515 515  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
516 516  
587 +[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape5" height="1" width="192"]]
588 +
517 517  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
518 518  
519 519  It remains up to the SDMX-VTL definer also the assurance of the consistency between a VTL Ruleset defined on Variables and the SDMX Components on which the Ruleset is applied. In fact, a VTL Ruleset is expressed by means of the values of the Variables (i.e. SDMX Concepts), i.e. assuming definite representations for them (e.g. ISOalpha-3 for country). If the Ruleset is applied to SDMX Components that have the same name of the Concept they refer to but different representations (e.g. ISO-alpha-2 for country), the Ruleset cannot work properly.
... ... @@ -526,19 +526,140 @@
526 526  
527 527  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:
528 528  
529 -[[image:1747388434672-948.png]]
601 +[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
530 530  
531 -(% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
532 -**Figure 22 – VTL Data Types**
603 +==== Figure 22 – VTL Data Types ====
533 533  
534 534  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.
535 535  
536 536  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):
537 537  
538 -[[image:1747388465321-274.png]]
539 539  
540 -**Figure 23 – VTL Basic Scalar Types**
541 541  
611 +(((
612 +//n//
613 +
614 +//a//
615 +
616 +//e//
617 +
618 +//l//
619 +
620 +//o//
621 +
622 +//o//
623 +
624 +//B//
625 +
626 +//n//
627 +
628 +//o//
629 +
630 +//i//
631 +
632 +//t//
633 +
634 +//a//
635 +
636 +//r//
637 +
638 +//u//
639 +
640 +//D//
641 +
642 +//d//
643 +
644 +//o//
645 +
646 +//i//
647 +
648 +//r//
649 +
650 +//e//
651 +
652 +//p//
653 +
654 +//_//
655 +
656 +//e//
657 +
658 +//m//
659 +
660 +//i//
661 +
662 +//T//
663 +
664 +//e//
665 +
666 +//t//
667 +
668 +//a//
669 +
670 +//D//
671 +
672 +//e//
673 +
674 +//m//
675 +
676 +//i//
677 +
678 +//T//
679 +
680 +//r//
681 +
682 +//e//
683 +
684 +//g//
685 +
686 +//e//
687 +
688 +//t//
689 +
690 +//n//
691 +
692 +//I//
693 +
694 +//r//
695 +
696 +//e//
697 +
698 +//b//
699 +
700 +//m//
701 +
702 +//u//
703 +
704 +//N//
705 +
706 +//g//
707 +
708 +//n//
709 +
710 +//i//
711 +
712 +//r//
713 +
714 +//t//
715 +
716 +//S//
717 +
718 +//r//
719 +
720 +//a//
721 +
722 +//l//
723 +
724 +//a//
725 +
726 +//c//
727 +
728 +//S//
729 +
730 +[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_82d45833.gif||alt="Shape6" height="231" width="184"]]
731 +)))
732 +
733 +==== Figure 23 – VTL Basic Scalar Types ====
734 +
542 542  === 12.4.2 VTL basic scalar types and SDMX data types ===
543 543  
544 544  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
... ... @@ -561,159 +561,204 @@
561 561  
562 562  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
563 563  
564 -(% style="width:823.294px" %)
565 -|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type**
566 -|(% style="width:509px" %)(((
757 +|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
758 +|(((
567 567  String
760 +
568 568  (string allowing any character)
569 -)))|(% style="width:312px" %)string
570 -|(% style="width:509px" %)(((
762 +)))|string
763 +|(((
571 571  Alpha
765 +
572 572  (string which only allows A-z)
573 -)))|(% style="width:312px" %)string
574 -|(% style="width:509px" %)(((
767 +)))|string
768 +|(((
575 575  AlphaNumeric
770 +
576 576  (string which only allows A-z and 0-9)
577 -)))|(% style="width:312px" %)string
578 -|(% style="width:509px" %)(((
772 +)))|string
773 +|(((
579 579  Numeric
775 +
580 580  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
581 -)))|(% style="width:312px" %)string
582 -|(% style="width:509px" %)(((
777 +)))|string
778 +|(((
583 583  BigInteger
780 +
584 584  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
585 -)))|(% style="width:312px" %)integer
586 -|(% style="width:509px" %)(((
782 +)))|integer
783 +|(((
587 587  Integer
588 -(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
589 -)))|(% style="width:312px" %)integer
590 -|(% style="width:509px" %)(((
785 +
786 +(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
787 +
788 +(inclusive))
789 +)))|integer
790 +|(((
591 591  Long
592 -(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
593 -)))|(% style="width:312px" %)integer
594 -|(% style="width:509px" %)(((
792 +
793 +(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
794 +
795 ++9223372036854775807 (inclusive))
796 +)))|integer
797 +|(((
595 595  Short
799 +
596 596  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
597 -)))|(% style="width:312px" %)integer
598 -|(% style="width:509px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:312px" %)number
599 -|(% style="width:509px" %)(((
801 +)))|integer
802 +|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
803 +|(((
600 600  Float
805 +
601 601  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
602 -)))|(% style="width:312px" %)number
603 -|(% style="width:509px" %)(((
807 +)))|number
808 +|(((
604 604  Double
810 +
605 605  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
606 -)))|(% style="width:312px" %)number
607 -|(% style="width:509px" %)(((
812 +)))|number
813 +|(((
608 608  Boolean
609 -(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
610 -)))|(% style="width:312px" %)boolean
611 611  
612 -(% style="width:822.294px" %)
613 -|(% colspan="2" style="width:507px" %)(((
816 +(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
817 +
818 +binary-valued logic: {true, false})
819 +)))|boolean
820 +
821 +| |(% colspan="2" %)(((
614 614  URI
823 +
615 615  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
616 -)))|(% colspan="1" style="width:311px" %)string
617 -|(% colspan="2" style="width:507px" %)(((
825 +)))|(% colspan="2" %)string
826 +| |(% colspan="2" %)(((
618 618  Count
828 +
619 619  (an integer following a sequential pattern, increasing by 1 for each occurrence)
620 -)))|(% colspan="1" style="width:311px" %)integer
621 -|(% colspan="2" style="width:507px" %)(((
830 +)))|(% colspan="2" %)integer
831 +| |(% colspan="2" %)(((
622 622  InclusiveValueRange
833 +
623 623  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
624 -)))|(% colspan="1" style="width:311px" %)number
625 -|(% colspan="2" style="width:507px" %)(((
835 +)))|(% colspan="2" %)number
836 +| |(% colspan="2" %)(((
626 626  ExclusiveValueRange
838 +
627 627  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
628 -)))|(% colspan="1" style="width:311px" %)number
629 -|(% colspan="2" style="width:507px" %)(((
840 +)))|(% colspan="2" %)number
841 +| |(% colspan="2" %)(((
630 630  Incremental
843 +
631 631  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
632 -)))|(% colspan="1" style="width:311px" %)number
633 -|(% colspan="2" style="width:507px" %)(((
845 +)))|(% colspan="2" %)number
846 +| |(% colspan="2" %)(((
634 634  ObservationalTimePeriod
848 +
635 635  (superset of StandardTimePeriod and TimeRange)
636 -)))|(% colspan="1" style="width:311px" %)time
637 -|(% colspan="2" style="width:507px" %)(((
850 +)))|(% colspan="2" %)time
851 +| |(% colspan="2" %)(((
638 638  StandardTimePeriod
639 -(superset of BasicTimePeriod and ReportingTimePeriod)
640 -)))|(% colspan="1" style="width:311px" %)time
641 -|(% colspan="2" style="width:507px" %)(((
853 +
854 +(superset of BasicTimePeriod and
855 +
856 +ReportingTimePeriod)
857 +)))|(% colspan="2" %)time
858 +| |(% colspan="2" %)(((
642 642  BasicTimePeriod
860 +
643 643  (superset of GregorianTimePeriod and DateTime)
644 -)))|(% colspan="1" style="width:311px" %)date
645 -|(% colspan="2" style="width:507px" %)(((
862 +)))|(% colspan="2" %)date
863 +| |(% colspan="2" %)(((
646 646  GregorianTimePeriod
865 +
647 647  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
648 -)))|(% colspan="1" style="width:311px" %)date
649 -|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date
650 -|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date
651 -|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date
652 -|(% colspan="2" style="width:507px" %)(((
867 +)))|(% colspan="2" %)date
868 +| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
869 +| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
870 +| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
871 +| |(% colspan="2" %)(((
653 653  ReportingTimePeriod
654 -(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
655 -)))|(% colspan="1" style="width:311px" %)time_period
656 -|(% colspan="2" style="width:507px" %)(((
873 +
874 +(superset of RepostingYear, ReportingSemester,
875 +
876 +ReportingTrimester, ReportingQuarter,
877 +
878 +ReportingMonth, ReportingWeek, ReportingDay)
879 +)))|(% colspan="2" %)time_period
880 +| |(% colspan="2" %)(((
657 657  ReportingYear
882 +
658 658  (YYYY-A1 – 1 year period)
659 -)))|(% colspan="1" style="width:311px" %)time_period
660 -|(% colspan="2" style="width:507px" %)(((
884 +)))|(% colspan="2" %)time_period
885 +| |(% colspan="2" %)(((
661 661  ReportingSemester
887 +
662 662  (YYYY-Ss – 6 month period)
663 -)))|(% colspan="1" style="width:311px" %)time_period
664 -|(% colspan="2" style="width:507px" %)(((
889 +)))|(% colspan="2" %)time_period
890 +| |(% colspan="2" %)(((
665 665  ReportingTrimester
892 +
666 666  (YYYY-Tt – 4 month period)
667 -)))|(% colspan="1" style="width:311px" %)time_period
668 -|(% colspan="2" style="width:507px" %)(((
894 +)))|(% colspan="2" %)time_period
895 +| |(% colspan="2" %)(((
669 669  ReportingQuarter
897 +
670 670  (YYYY-Qq – 3 month period)
671 -)))|(% colspan="1" style="width:311px" %)time_period
672 -|(% colspan="2" style="width:507px" %)(((
899 +)))|(% colspan="2" %)time_period
900 +| |(% colspan="2" %)(((
673 673  ReportingMonth
902 +
674 674  (YYYY-Mmm – 1 month period)
675 -)))|(% colspan="1" style="width:311px" %)time_period
676 -|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period
677 -|(% colspan="1" style="width:507px" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" style="width:312px" %)
678 -|(% colspan="1" style="width:507px" %)(((
904 +)))|(% colspan="2" %)time_period
905 +| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
906 +| |(% colspan="2" %) |(% colspan="2" %)
907 +| |(% colspan="2" %) |(% colspan="2" %)
908 +|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) |
909 +|(% colspan="2" %)(((
679 679  ReportingDay
911 +
680 680  (YYYY-Dddd – 1 day period)
681 -)))|(% colspan="2" style="width:312px" %)time_period
682 -|(% colspan="1" style="width:507px" %)(((
913 +)))|(% colspan="2" %)time_period|
914 +|(% colspan="2" %)(((
683 683  DateTime
916 +
684 684  (YYYY-MM-DDThh:mm:ss)
685 -)))|(% colspan="2" style="width:312px" %)date
686 -|(% colspan="1" style="width:507px" %)(((
918 +)))|(% colspan="2" %)date|
919 +|(% colspan="2" %)(((
687 687  TimeRange
921 +
688 688  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
689 -)))|(% colspan="2" style="width:312px" %)time
690 -|(% colspan="1" style="width:507px" %)(((
923 +)))|(% colspan="2" %)time|
924 +|(% colspan="2" %)(((
691 691  Month
926 +
692 692  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
693 -)))|(% colspan="2" style="width:312px" %)string
694 -|(% colspan="1" style="width:507px" %)(((
928 +)))|(% colspan="2" %)string|
929 +|(% colspan="2" %)(((
695 695  MonthDay
931 +
696 696  (~-~-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)
697 -)))|(% colspan="2" style="width:312px" %)string
698 -|(% colspan="1" style="width:507px" %)(((
933 +)))|(% colspan="2" %)string|
934 +|(% colspan="2" %)(((
699 699  Day
936 +
700 700  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
701 -)))|(% colspan="2" style="width:312px" %)string
702 -|(% colspan="1" style="width:507px" %)(((
938 +)))|(% colspan="2" %)string|
939 +|(% colspan="2" %)(((
703 703  Time
941 +
704 704  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
705 -)))|(% colspan="2" style="width:312px" %)string
706 -|(% colspan="1" style="width:507px" %)(((
943 +)))|(% colspan="2" %)string|
944 +|(% colspan="2" %)(((
707 707  Duration
946 +
708 708  (corresponds to XML Schema xs:duration datatype)
709 -)))|(% colspan="2" style="width:312px" %)duration
710 -|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable
711 -|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable
712 -|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
713 -|(% colspan="1" style="width:507px" %)DataSetReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
948 +)))|(% colspan="2" %)duration|
949 +|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
950 +|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
951 +|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
952 +|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
714 714  
715 -(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %)
716 -**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
954 +==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
717 717  
718 718  When VTL takes in input SDMX artefacts, it is assumed that a type conversion according to the table above always happens. In case a different VTL basic scalar type is desired, it can be achieved in the VTL program taking in input the default VTL basic scalar type above and applying to it the VTL type conversion features (see the implicit and explicit type conversion and the "cast" operator in the VTL Reference Manual).
719 719  
... ... @@ -721,86 +721,93 @@
721 721  
722 722  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
723 723  
724 -(% style="width:1073.29px" %)
725 -|(% style="width:207px" %)(((
726 -**VTL basic scalar type**
727 -)))|(% style="width:462px" %)(((
728 -**Default SDMX data type (BasicComponentDataType)**
729 -)))|(% style="width:402px" %)**Default output format**
730 -|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string)
731 -|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float)
732 -|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int)
733 -|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z
734 -|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above)
735 -|(% style="width:207px" %)time_period|(% style="width:462px" %)(((
962 +|(((
963 +VTL basic
964 +
965 +scalar type
966 +)))|(((
967 +Default SDMX data type
968 +
969 +(BasicComponentDataType
970 +
971 +)
972 +)))|Default output format
973 +|String|String|Like XML (xs:string)
974 +|Number|Float|Like XML (xs:float)
975 +|Integer|Integer|Like XML (xs:int)
976 +|Date|DateTime|YYYY-MM-DDT00:00:00Z
977 +|Time|StandardTimePeriod|<date>/<date> (as defined above)
978 +|time_period|(((
736 736  ReportingTimePeriod
980 +
737 737  (StandardReportingPeriod)
738 -)))|(% style="width:402px" %)(((
982 +)))|(((
739 739  YYYY-Pppp
984 +
740 740  (according to SDMX )
741 741  )))
742 -|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)(((
987 +|Duration|Duration|(((
743 743  Like XML (xs:duration)
989 +
744 744  PnYnMnDTnHnMnS
745 745  )))
746 -|(% style="width:207px" %)Boolean|(% style="width:462px" %)Boolean|(% style="width:402px" %)Like XML (xs:boolean) with the values "true" or "false"
992 +|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
747 747  
748 -(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes-1" %)
749 -**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
994 +==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
750 750  
751 751  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).
752 752  
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:713.294px" %)
756 -|(% colspan="2" style="width:710px" %)VTL special characters for the formatting masks
757 -|(% colspan="2" style="width:710px" %)
758 -|(% colspan="2" style="width:710px" %)Number
759 -|D|(% style="width:486px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
760 -|E|(% style="width:486px" %)one numeric digit (for the exponent of the scientific notation)
761 -|. (dot)|(% style="width:486px" %)possible separator between the integer and the decimal parts.
762 -|, (comma)|(% style="width:486px" %)possible separator between the integer and the decimal parts.
763 -| |(% style="width:486px" %)
764 -|(% colspan="2" style="width:710px" %)Time and duration
765 -|C|(% style="width:486px" %)century
766 -|Y|(% style="width:486px" %)year
767 -|S|(% style="width:486px" %)semester
768 -|Q|(% style="width:486px" %)quarter
769 -|M|(% style="width:486px" %)month
770 -|W|(% style="width:486px" %)week
771 -|D|(% style="width:486px" %)day
772 -|h|(% style="width:486px" %)hour digit (by default on 24 hours)
773 -|M|(% style="width:486px" %)minute
774 -|S|(% style="width:486px" %)second
775 -|D|(% style="width:486px" %)decimal of second
776 -|P|(% style="width:486px" %)period indicator (representation in one digit for the duration)
777 -|P|(% style="width:486px" %)number of the periods specified in the period indicator
778 -|AM/PM|(% style="width:486px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
779 -|MONTH|(% style="width:486px" %)uppercase textual representation of the month (e.g., JANUARY for January)
780 -|DAY|(% style="width:486px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
781 -|Month|(% style="width:486px" %)lowercase textual representation of the month (e.g., january)
782 -|Day|(% style="width:486px" %)lowercase textual representation of the month (e.g., monday)
783 -|Month|(% style="width:486px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
784 -|Day|(% style="width:486px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
785 -| |(% style="width:486px" %)
786 -|(% colspan="2" style="width:710px" %)String
787 -|X|(% style="width:486px" %)any string character
788 -|Z|(% style="width:486px" %)any string character from "A" to "z"
789 -|9|(% style="width:486px" %)any string character from "0" to "9"
790 -| |(% style="width:486px" %)
791 -|(% colspan="2" style="width:710px" %)Boolean
792 -|B|(% style="width:486px" %)Boolean using "true" for True and "false" for False
793 -|1|(% style="width:486px" %)Boolean using "1" for True and "0" for False
794 -|0|(% style="width:486px" %)Boolean using "0" for True and "1" for False
795 -| |(% style="width:486px" %)
796 -|(% colspan="2" style="width:710px" %)Other qualifiers
797 -|*|(% style="width:486px" %)an arbitrary number of digits (of the preceding type)
798 -|+|(% style="width:486px" %)at least one digit (of the preceding type)
799 -|( )|(% style="width:486px" %)optional digits (specified within the brackets)
800 -|\|(% style="width:486px" %)prefix for the special characters that must appear in the mask
801 -|N|(% style="width:486px" %)fixed number of digits used in the preceding textual representation of the month or the day
1000 +|(% colspan="2" %)VTL special characters for the formatting masks
1001 +|(% colspan="2" %)
1002 +|(% colspan="2" %)Number
1003 +|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
1004 +|E|one numeric digit (for the exponent of the scientific notation)
1005 +|. (dot)|possible separator between the integer and the decimal parts.
1006 +|, (comma)|possible separator between the integer and the decimal parts.
1007 +| |
1008 +|(% colspan="2" %)Time and duration
1009 +|C|century
1010 +|Y|year
1011 +|S|semester
1012 +|Q|quarter
1013 +|M|month
1014 +|W|week
1015 +|D|day
1016 +|h|hour digit (by default on 24 hours)
1017 +|M|minute
1018 +|S|second
1019 +|D|decimal of second
1020 +|P|period indicator (representation in one digit for the duration)
1021 +|P|number of the periods specified in the period indicator
1022 +|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
1023 +|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
1024 +|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
1025 +|Month|lowercase textual representation of the month (e.g., january)
1026 +|Day|lowercase textual representation of the month (e.g., monday)
1027 +|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
1028 +|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
1029 +| |
1030 +|(% colspan="2" %)String
1031 +|X|any string character
1032 +|Z|any string character from "A" to "z"
1033 +|9|any string character from "0" to "9"
1034 +| |
1035 +|(% colspan="2" %)Boolean
1036 +|B|Boolean using "true" for True and "false" for False
1037 +|1|Boolean using "1" for True and "0" for False
1038 +|0|Boolean using "0" for True and "1" for False
1039 +| |
1040 +|(% colspan="2" %)Other qualifiers
1041 +|*|an arbitrary number of digits (of the preceding type)
1042 +|+|at least one digit (of the preceding type)
1043 +|( )|optional digits (specified within the brackets)
1044 +|\|prefix for the special characters that must appear in the mask
1045 +|N|fixed number of digits used in the preceding textual representation of the month or the day
1046 +| |
802 802  
803 -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}}.
1048 +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^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
804 804  
805 805  === 12.4.5 Null Values ===
806 806  
... ... @@ -818,8 +818,10 @@
818 818  
819 819  A different format can be specified in the attribute "vtlLiteralFormat" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model).
820 820  
821 -Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL TransformationScheme.
1066 +Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL
822 822  
1068 +TransformationScheme.
1069 +
823 823  In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
824 824  
825 825  {{putFootnotes/}}
1747388148322-387.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -23.0 KB
Content
1747388179021-814.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -66.2 KB
Content
1747388206717-256.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -10.3 KB
Content
1747388222879-916.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -9.9 KB
Content
1747388244829-693.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -7.4 KB
Content
1747388275998-621.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -19.2 KB
Content
1747388434672-948.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -43.2 KB
Content
1747388465321-274.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -17.9 KB
Content