Changes for page 12 Validation and Transformation Language (VTL)

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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
...	...	@@ -198,7 +198,7 @@
198	198
199	199	The possible mapping options are described in more detail in the following sections.
200	200
201		-=== 12.3.3 Mapping from SDMX to VTL data structures ===
	201	+=== 12.3.2 Mapping from SDMX to VTL data structures ===
202	202
203	203	==== 12.3.3.1 Basic Mapping ====
204	204
...	...	@@ -206,12 +206,11 @@
206	206
207	207	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:
208	208
209		-(% style="width:468.294px" %)
210		-|(% style="width:196px" %)**SDMX**|(% style="width:269px" %)**VTL**
211		-|(% style="width:196px" %)Dimension|(% style="width:269px" %)(Simple) Identifier
212		-|(% style="width:196px" %)TimeDimension|(% style="width:269px" %)(Time) Identifier
213		-|(% style="width:196px" %)Measure|(% style="width:269px" %)Measure
214		-|(% style="width:196px" %)DataAttribute|(% style="width:269px" %)Attribute
	209	+|**SDMX**|**VTL**
	210	+|Dimension|(Simple) Identifier
	211	+|TimeDimension|(Time) Identifier
	212	+|Measure|Measure
	213	+|DataAttribute|Attribute
215	215
216	216	The SDMX DataAttributes, in VTL they are all considered "at data point / observation level" (i.e. dependent on all the VTL Identifiers), because VTL does not have the SDMX AttributeRelationships, which defines the construct to which the DataAttribute is related (e.g. observation, dimension or set or group of dimensions, whole data set).
217	217
...	...	@@ -221,8 +221,10 @@
221	221
222	222	An alternative mapping method from SDMX to VTL is the **Pivot **mapping, which makes sense and is different from the Basic method only for the SDMX data structures that contain a Dimension that plays the role of measure dimension (like in SDMX 2.1) and just one Measure. Through this method, these structures can be mapped to multimeasure VTL data structures. Besides that, a user may choose to use any Dimension acting as a list of Measures (e.g., a Dimension with indicators), either by considering the “Measure” role of a Dimension, or at will using any coded Dimension. Of course, in SDMX 3.0, this can only work when only one Measure is defined in the DSD.
223	223
224		-In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.
	223	+In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the
225	225
	225	+MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.
	226	+
226	226	Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
227	227
228	228	If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
...	...	@@ -235,18 +235,16 @@
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).
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	+** 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.
240	240
241	241	The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
242	242
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" %)(((
	243	+|**SDMX**|**VTL**
	244	+|Dimension|(Simple) Identifier
	245	+|TimeDimension|(Time) Identifier
	246	+|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension
	247	+|DataAttribute not depending on the MeasureDimension|Attribute
	248	+|DataAttribute depending on the MeasureDimension|(((
250	250	One Attribute for each Code of the
251	251	SDMX MeasureDimension
252	252	)))
...	...	@@ -256,14 +256,19 @@
256	256	At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
257	257
258	258	* The set of SDMX observations having the same values for all the Dimensions except than the MeasureDimension become one multi-measure VTL Data Point, having one Measure for each Code Cj of the SDMX MeasureDimension;
259		-* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
	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)
	259	+
	260	+Identifiers, (time) Identifier and Attributes.
	261	+
260	260	* The value of the Measure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj
261	261	* For the SDMX DataAttributes depending on the MeasureDimension, the value of the DataAttribute DA of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Attribute DA_Cj
262	262
263	263	==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
264	264
265		-* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain Attributes.
	267	+* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain
266	266
	269	+Attributes.
	270	+
267	267	The Basic_A2M and Pivot_A2M behaves respectively like the Basic and Pivot methods, except that the final VTL components, which according to the Basic and Pivot methods would have had the role of Attribute, assume instead the role of Measure.
268	268
269	269	Proper VTL features allow changing the role of specific attributes even after the SDMX to VTL mapping: they can be useful when only some of the DataAttributes need to be managed as VTL Measures.
...	...	@@ -280,12 +280,11 @@
280	280
281	281	Mapping table:
282	282
283		-(% style="width:470.294px" %)
284		-|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX**
285		-|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension
286		-|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension
287		-|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure
288		-|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute
	287	+|**VTL**|**SDMX**
	288	+|(Simple) Identifier|Dimension
	289	+|(Time) Identifier|TimeDimension
	290	+|Measure|Measure
	291	+|Attribute|DataAttribute
289	289
290	290	If the distinction between simple identifier and time identifier is not maintained in the VTL environment, the classification between Dimension and TimeDimension exists only in SDMX, as declared in the relevant DataStructureDefinition.
291	291
...	...	@@ -313,12 +313,11 @@
313	313
314	314	The summary mapping table of the **unpivot** mapping method is the following:
315	315
316		-(% style="width:638.294px" %)
317		-|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX**
318		-|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension
319		-|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension
320		-|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
321		-|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
	319	+|**VTL**|**SDMX**
	320	+|(Simple) Identifier|Dimension
	321	+|(Time) Identifier|TimeDimension
	322	+|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
	323	+|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
322	322
323	323	At observation / data point level:
324	324
...	...	@@ -340,13 +340,12 @@
340	340
341	341	The mapping table is the following:
342	342
343		-(% style="width:467.294px" %)
344		-|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
345		-|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
346		-|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
347		-|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
348		-|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
349		-|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
	345	+|VTL|SDMX
	346	+|(Simple) Identifier|Dimension
	347	+|(Time) Identifier|TimeDimension
	348	+|Some Measures|Measure
	349	+|Other Measures|DataAttribute
	350	+|Attribute|DataAttribute
350	350
351	351	Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the attributeRelationship for the DataAttributes, which does not exist in VTL.
352	352
...	...	@@ -384,11 +384,11 @@
384	384
385	385	Therefore, the generic name of this kind of VTL datasets would be:
386	386
387		-> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
	388	+'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’
	392	+‘DF(1.0.0)/POPULATION.USA’
392	392
393	393	In particular, this is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA.
394	394
...	...	@@ -402,22 +402,26 @@
402	402
403	403	SDMX Dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=// COUNTRYvalue//. For example, the VTL dataset ‘DF1(1.0.0)/POPULATION.USA’ would contain all the observations of DF1(1.0.0) having INDICATOR = POPULATION and COUNTRY = USA.
404	404
405		-In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
	406	+In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
406	406
	408	+basic, pivot …).
	409	+
407	407	In the example above, for all the datasets of the kind
408	408
409		-> ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
	412	+‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
410	410
411	411	It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression:
412	412
413		-> ‘DF1(1.0.0)/POPULATION.USA’ :=
414		-> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
415		->
416		-> ‘DF1(1.0.0)/POPULATION.CANADA’ :=
417		-> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
418		->
419		-> … … …
	416	+‘DF1(1.0.0)/POPULATION.USA’ :=
420	420
	418	+DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
	419	+
	420	+‘DF1(1.0.0)/POPULATION.CANADA’ :=
	421	+
	422	+DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
	423	+
	424	+… … …
	425	+
421	421	In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}}
422	422
423	423	In the direction from SDMX to VTL it is allowed to omit the value of one or more DimensionComponents on which the mapping is based, but maintaining all the separating dots (therefore it may happen to find two or more consecutive dots and dots in the beginning or in the end). The absence of value means that for the corresponding Dimension all the values are kept and the Dimension is not dropped.
...	...	@@ -426,9 +426,10 @@
426	426
427	427	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
428	428
429		-> ‘DF1(1.0.0)/POPULATION.’ :=
430		-> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
	434	+‘DF1(1.0.0)/POPULATION.’ :=
431	431
	436	+DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
	437	+
432	432	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
433	433
434	434	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
...	...	@@ -446,33 +446,41 @@
446	446
447	447	The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:{{footnote}}the symbol of the VTL persistent assignment is used (<-){{/footnote}}
448	448
449		-> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
	455	+‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
450	450
451	451	Some examples follow, for some specific values of INDICATOR and COUNTRY:
452	452
453		-> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
454		-> … … …
455		-> ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
456		-> ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
457		-> … … …
	459	+‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
	460	+… … …
458	458
	462	+‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
	463	+‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
	464	+… … …
	465	+
459	459	As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively:
460	460
461		-> VTL dataset INDICATOR value COUNTRY value
462		->
463		-> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
464		-> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
465		->
466		-> ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
467		-> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
468		-> … … …
	468	+VTL dataset   INDICATOR value COUNTRY value
469	469
	470	+‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
	471	+‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
	472	+‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
	473	+‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
	474	+
	475	+… … …
	476	+
470	470	It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be:
471	471
472		-> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”];… … … DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”];… … … DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’, DF2bis_GDPPERCAPITA_CANADA’,
473		-> … ,
474		-> DF2bis_POPGROWTH_USA’, DF2bis_POPGROWTH_CANADA’
475		-> …);
	479	+DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
	480	+DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
	481	+DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
	482	+[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
	483	+DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
	484	+DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
	485	+DF2bis_GDPPERCAPITA_CANADA’,
	486	+… ,
	487	+DF2bis_POPGROWTH_USA’,
	488	+DF2bis_POPGROWTH_CANADA’
	489	+…);
476	476
477	477	In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
478	478
...	...	@@ -484,26 +484,25 @@
484	484
485	485	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
486	486
487		-(% style="width:706.294px" %)
488		-|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX
489		-|(% style="width:257px" %)**Data Set Component**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
490		-|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation
491		-|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)(((
	501	+|VTL|SDMX
	502	+|**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^^
	503	+|**Represented Variable**|**Concept** with a definite Representation
	504	+|**Value Domain**|(((
492	492	**Representation** (see the Structure
493	493	Pattern in the Base Package)
494	494	)))
495		-|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
496		-|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
497		-|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
	508	+|**Enumerated Value Domain / Code List**|**Codelist**
	509	+|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
	510	+|**Described Value Domain**|(((
498	498	non-enumerated** Representation**
499	499	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
500	500	)))
501		-|(% style="width:257px" %)**Value**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
502		-|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)
503		-|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
504		-|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
505		-|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
506		-|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX
	514	+|**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
	515	+| |to a valid **value **(for non-enumerated** **Representations)
	516	+|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
	517	+|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
	518	+|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
	519	+|**Set list**|This abstraction does not exist in SDMX
507	507
508	508	The main difference between VTL and SDMX relies on the fact that the VTL artefacts for defining subsets of Value Domains do not exist in SDMX, therefore the VTL features for referring to predefined subsets are not available in SDMX. These artefacts are the Value Domain Subset (or Set), either enumerated or described, the Set List (list of values belonging to enumerated subsets) and the Data Set Component (aimed at defining the set of values that the Component of a Data Set can take, possibly a subset of the codes of Value Domain).
509	509
...	...	@@ -511,10 +511,8 @@
511	511
512	512	Therefore, it is important to be aware that some VTL operations (for example the binary operations at data set level) are consistent only if the components having the same names in the operated VTL Data Sets have also the same representation (i.e. the same Value Domain as for VTL). For example, it is possible to obtain correct results from the VTL expression
513	513
514		-> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
	527	+DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
515	515
516		-if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
517		-
518	518	As mentioned, the property above is not enforced by construction in SDMX, and different representations of the same Concept can be not compatible one another (for example, it may happen that geo_area is represented by ISO-alpha-3 codes in DS_a and by ISO alpha-2 codes in DS_b). Therefore, it will be up to the definer of VTL
519	519
520	520	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -529,9 +529,8 @@
529	529
530	530	The VTL data types are sub-divided in scalar types (like integers, strings, etc.), which are the types of the scalar values, and compound types (like Data Sets, Components, Rulesets, etc.), which are the types of the compound structures. See below the diagram of the VTL data types, taken from the VTL User Manual:
531	531
	543	+[[image:1750067055028-964.png]]
532	532
533		-[[image:1750070288958-132.png]]
534		-
535	535	**Figure 22 – VTL Data Types**
536	536
537	537	The VTL scalar types are in turn subdivided in basic scalar types, which are elementary (not defined in term of other data types) and Value Domain and Set scalar types, which are defined in terms of the basic scalar types.
...	...	@@ -538,8 +538,6 @@
538	538
539	539	The VTL basic scalar types are listed below and follow a hierarchical structure in terms of supersets/subsets (e.g. "scalar" is the superset of all the basic scalar types):
540	540
541		-[[image:1750070310572-584.png]]
542		-
543	543	**Figure 23 – VTL Basic Scalar Types**
544	544
545	545	=== 12.4.2 VTL basic scalar types and SDMX data types ===
...	...	@@ -564,157 +564,158 @@
564	564
565	565	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
566	566
567		-(% style="width:583.294px" %)
568		-|(% style="width:360px" %)SDMX data type (BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type
569		-|(% style="width:360px" %)(((
	575	+|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
	576	+|(((
570	570	String
571	571	(string allowing any character)
572		-)))|(% style="width:221px" %)string
573		-|(% style="width:360px" %)(((
574		-Alpha
	579	+)))|string
	580	+|(((
	581	+Alpha
	582	+
575	575	(string which only allows A-z)
576		-)))|(% style="width:221px" %)string
577		-|(% style="width:360px" %)(((
	584	+)))|string
	585	+|(((
578	578	AlphaNumeric
579	579	(string which only allows A-z and 0-9)
580		-)))|(% style="width:221px" %)string
581		-|(% style="width:360px" %)(((
	588	+)))|string
	589	+|(((
582	582	Numeric
	591	+
583	583	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
584		-)))|(% style="width:221px" %)string
585		-|(% style="width:360px" %)(((
	593	+)))|string
	594	+|(((
586	586	BigInteger
587	587	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
588		-)))|(% style="width:221px" %)integer
589		-|(% style="width:360px" %)(((
	597	+)))|integer
	598	+|(((
590	590	Integer
591	591	(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
592	592	(inclusive))
593		-)))|(% style="width:221px" %)integer
594		-|(% style="width:360px" %)(((
	602	+)))|integer
	603	+|(((
595	595	Long
596	596	(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
597	597	+9223372036854775807 (inclusive))
598		-)))|(% style="width:221px" %)integer
599		-|(% style="width:360px" %)(((
	607	+)))|integer
	608	+|(((
600	600	Short
601	601	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
602		-)))|(% style="width:221px" %)integer
603		-|(% style="width:360px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:221px" %)number
604		-|(% style="width:360px" %)(((
	611	+)))|integer
	612	+|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
	613	+|(((
605	605	Float
606	606	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
607		-)))|(% style="width:221px" %)number
608		-|(% style="width:360px" %)(((
	616	+)))|number
	617	+|(((
609	609	Double
610	610	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
611		-)))|(% style="width:221px" %)number
612		-|(% style="width:360px" %)(((
	620	+)))|number
	621	+|(((
613	613	Boolean
614	614	(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
615	615	binary-valued logic: {true, false})
616		-)))|(% style="width:221px" %)boolean
617		-|(% style="width:360px" %)(((
	625	+)))|boolean
	626	+|(((
618	618	URI
619	619	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
620		-)))|(% style="width:221px" %)string
621		-|(% style="width:360px" %)(((
	629	+)))|string
	630	+|(((
622	622	Count
623	623	(an integer following a sequential pattern, increasing by 1 for each occurrence)
624		-)))|(% style="width:221px" %)integer
625		-|(% style="width:360px" %)(((
	633	+)))|integer
	634	+|(((
626	626	InclusiveValueRange
627	627	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
628		-)))|(% style="width:221px" %)number
629		-|(% style="width:360px" %)(((
	637	+)))|number
	638	+|(((
630	630	ExclusiveValueRange
631	631	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
632		-)))|(% style="width:221px" %)number
633		-|(% style="width:360px" %)(((
	641	+)))|number
	642	+|(((
634	634	Incremental
635	635	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
636		-)))|(% style="width:221px" %)number
637		-|(% style="width:360px" %)(((
	645	+)))|number
	646	+|(((
638	638	ObservationalTimePeriod
639	639	(superset of StandardTimePeriod and TimeRange)
640		-)))|(% style="width:221px" %)time
641		-|(% style="width:360px" %)(((
	649	+)))|time
	650	+|(((
642	642	StandardTimePeriod
643	643	(superset of BasicTimePeriod and ReportingTimePeriod)
644		-)))|(% style="width:221px" %)time
645		-|(% style="width:360px" %)(((
	653	+)))|time
	654	+|(((
646	646	BasicTimePeriod
647	647	(superset of GregorianTimePeriod and DateTime)
648		-)))|(% style="width:221px" %)date
649		-|(% style="width:360px" %)(((
	657	+)))|date
	658	+|(((
650	650	GregorianTimePeriod
651	651	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
652		-)))|(% style="width:221px" %)date
653		-|(% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date
654		-|(% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date
655		-|(% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date
656		-|(% style="width:360px" %)(((
	661	+)))|date
	662	+|GregorianYear (YYYY)|date
	663	+|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
	664	+|GregorianDay (YYYY-MM-DD)|date
	665	+|(((
657	657	ReportingTimePeriod
658	658	(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
659		-)))|(% style="width:221px" %)time_period
660		-|(% style="width:360px" %)(((
	668	+)))|time_period
	669	+|(((
661	661	ReportingYear
662	662	(YYYY-A1 – 1 year period)
663		-)))|(% style="width:221px" %)time_period
664		-|(% style="width:360px" %)(((
	672	+)))|time_period
	673	+|(((
665	665	ReportingSemester
666	666	(YYYY-Ss – 6 month period)
667		-)))|(% style="width:221px" %)time_period
668		-|(% style="width:360px" %)(((
	676	+)))|time_period
	677	+|(((
669	669	ReportingTrimester
670	670	(YYYY-Tt – 4 month period)
671		-)))|(% style="width:221px" %)time_period
672		-|(% style="width:360px" %)(((
	680	+)))|time_period
	681	+|(((
673	673	ReportingQuarter
674	674	(YYYY-Qq – 3 month period)
675		-)))|(% style="width:221px" %)time_period
676		-|(% style="width:360px" %)(((
	684	+)))|time_period
	685	+|(((
677	677	ReportingMonth
678	678	(YYYY-Mmm – 1 month period)
679		-)))|(% style="width:221px" %)time_period
680		-|(% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period
681		-|(% style="width:360px" %) (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% style="width:221px" %)
682		-|(% style="width:360px" %)(((
	688	+)))|time_period
	689	+|ReportingWeek|time_period
	690	+| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
	691	+|(((
683	683	ReportingDay
684	684	(YYYY-Dddd – 1 day period)
685		-)))|(% style="width:221px" %)time_period
686		-|(% style="width:360px" %)(((
	694	+)))|time_period
	695	+|(((
687	687	DateTime
688	688	(YYYY-MM-DDThh:mm:ss)
689		-)))|(% style="width:221px" %)date
690		-|(% style="width:360px" %)(((
	698	+)))|date
	699	+|(((
691	691	TimeRange
692	692	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
693		-)))|(% style="width:221px" %)time
694		-|(% style="width:360px" %)(((
	702	+)))|time
	703	+|(((
695	695	Month
696	696	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
697		-)))|(% style="width:221px" %)string
698		-|(% style="width:360px" %)(((
	706	+)))|string
	707	+|(((
699	699	MonthDay
700	700	(~-~-MM-DD; specifies a day within a month independent of a year; e.g. Christmas is December 25^^th^^; used to specify reporting year start day)
701		-)))|(% style="width:221px" %)string
702		-|(% style="width:360px" %)(((
	710	+)))|string
	711	+|(((
703	703	Day
704	704	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
705		-)))|(% style="width:221px" %)string
706		-|(% style="width:360px" %)(((
	714	+)))|string
	715	+|(((
707	707	Time
708	708	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
709		-)))|(% style="width:221px" %)string
710		-|(% style="width:360px" %)(((
	718	+)))|string
	719	+|(((
711	711	Duration
712	712	(corresponds to XML Schema xs:duration datatype)
713		-)))|(% style="width:221px" %)duration
714		-|(% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable
715		-|(% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable
716		-|(% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable
717		-|(% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable
	722	+)))|duration
	723	+|XHTML|Metadata type – not applicable
	724	+|KeyValues|Metadata type – not applicable
	725	+|IdentifiableReference|Metadata type – not applicable
	726	+|DataSetReference|Metadata type – not applicable
718	718
719	719	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
720	720
...	...	@@ -724,82 +724,84 @@
724	724
725	725	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
726	726
727		-(% style="width:748.294px" %)
728		-|(% style="width:164px" %)(((
729		-VTL basic scalar type
730		-)))|(% style="width:304px" %)(((
	736	+|(((
	737	+VTL basic
	738	+scalar type
	739	+)))|(((
731	731	Default SDMX data type
732		-(BasicComponentDataType)
733		-)))|(% style="width:277px" %)Default output format
734		-|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string)
735		-|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float)
736		-|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int)
737		-|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z
738		-|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above)
739		-|(% style="width:164px" %)time_period|(% style="width:304px" %)(((
	741	+(BasicComponentDataType
	742	+)
	743	+)))|Default output format
	744	+|String|String|Like XML (xs:string)
	745	+|Number|Float|Like XML (xs:float)
	746	+|Integer|Integer|Like XML (xs:int)
	747	+|Date|DateTime|YYYY-MM-DDT00:00:00Z
	748	+|Time|StandardTimePeriod|<date>/<date> (as defined above)
	749	+|time_period|(((
740	740	ReportingTimePeriod
741	741	(StandardReportingPeriod)
742		-)))|(% style="width:277px" %)(((
	752	+)))|(((
743	743	YYYY-Pppp
744	744	(according to SDMX )
745	745	)))
746		-|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS
747		-|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"
	756	+|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
	757	+|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
748	748
749	749	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
750	750
751		-In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
	761	+In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
752	752
	763	+Transformations and Expressions of the SDMX information model).
	764	+
753	753	The custom output formats can be specified by means of the VTL formatting mask described in the section "Type Conversion and Formatting Mask" of the VTL Reference Manual. Such a section describes the masks for the VTL basic scalar types "number", "integer", "date", "time", "time_period" and "duration" and gives examples. As for the types "string" and "boolean" the VTL conventions are extended with some other special characters as described in the following table.
754	754
755		-(% style="width:717.294px" %)
756		-|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks
757		-|(% colspan="2" style="width:714px" %)
758		-|(% colspan="2" style="width:714px" %)Number
759		-|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
760		-|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation)
761		-|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
762		-|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
763		-|(% style="width:122px" %) |(% style="width:591px" %)
764		-|(% colspan="2" style="width:714px" %)Time and duration
765		-|(% style="width:122px" %)C|(% style="width:591px" %)century
766		-|(% style="width:122px" %)Y|(% style="width:591px" %)year
767		-|(% style="width:122px" %)S|(% style="width:591px" %)semester
768		-|(% style="width:122px" %)Q|(% style="width:591px" %)quarter
769		-|(% style="width:122px" %)M|(% style="width:591px" %)month
770		-|(% style="width:122px" %)W|(% style="width:591px" %)week
771		-|(% style="width:122px" %)D|(% style="width:591px" %)day
772		-|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours)
773		-|(% style="width:122px" %)M|(% style="width:591px" %)minute
774		-|(% style="width:122px" %)S|(% style="width:591px" %)second
775		-|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second
776		-|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration)
777		-|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator
778		-|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
779		-|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January)
780		-|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
781		-|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january)
782		-|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday)
783		-|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
784		-|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
785		-|(% style="width:122px" %) |(% style="width:591px" %)
786		-|(% colspan="2" style="width:714px" %)String
787		-|(% style="width:122px" %)X|(% style="width:591px" %)any string character
788		-|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z"
789		-|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9"
790		-|(% style="width:122px" %) |(% style="width:591px" %)
791		-|(% colspan="2" style="width:714px" %)Boolean
792		-|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False
793		-|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False
794		-|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False
795		-|(% style="width:122px" %) |(% style="width:591px" %)
796		-|(% colspan="2" style="width:714px" %)Other qualifiers
797		-|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type)
798		-|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type)
799		-|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets)
800		-|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask
801		-|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day
802		-|(% style="width:122px" %) |(% style="width:591px" %)
	767	+|(% colspan="2" %)VTL special characters for the formatting masks
	768	+|(% colspan="2" %)
	769	+|(% colspan="2" %)Number
	770	+|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
	771	+|E|one numeric digit (for the exponent of the scientific notation)
	772	+|. (dot)|possible separator between the integer and the decimal parts.
	773	+|, (comma)|possible separator between the integer and the decimal parts.
	774	+| |
	775	+|(% colspan="2" %)Time and duration
	776	+|C|century
	777	+|Y|year
	778	+|S|semester
	779	+|Q|quarter
	780	+|M|month
	781	+|W|week
	782	+|D|day
	783	+|h|hour digit (by default on 24 hours)
	784	+|M|minute
	785	+|S|second
	786	+|D|decimal of second
	787	+|P|period indicator (representation in one digit for the duration)
	788	+|P|number of the periods specified in the period indicator
	789	+|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
	790	+|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
	791	+|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
	792	+|Month|lowercase textual representation of the month (e.g., january)
	793	+|Day|lowercase textual representation of the month (e.g., monday)
	794	+|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
	795	+|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
	796	+| |
	797	+|(% colspan="2" %)String
	798	+|X|any string character
	799	+|Z|any string character from "A" to "z"
	800	+|9|any string character from "0" to "9"
	801	+| |
	802	+|(% colspan="2" %)Boolean
	803	+|B|Boolean using "true" for True and "false" for False
	804	+|1|Boolean using "1" for True and "0" for False
	805	+|0|Boolean using "0" for True and "1" for False
	806	+| |
	807	+|(% colspan="2" %)Other qualifiers
	808	+|*|an arbitrary number of digits (of the preceding type)
	809	+|+|at least one digit (of the preceding type)
	810	+|( )|optional digits (specified within the brackets)
	811	+|\|prefix for the special characters that must appear in the mask
	812	+|N|fixed number of digits used in the preceding textual representation of the month or the day
	813	+| |
803	803
804	804	The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion{{footnote}}The representation given in the DSD should obviously be compatible with the VTL data type.{{/footnote}}.
805	805

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