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
...	...	@@ -256,19 +256,14 @@
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)
260		-
261		-Identifiers, (time) Identifier and Attributes.
262		-
	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.
263	263	* 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
264	264	* 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
265	265
266	266	==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
267	267
268		-* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain
	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.
269	269
270		-Attributes.
271		-
272	272	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.
273	273
274	274	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.
...	...	@@ -285,11 +285,12 @@
285	285
286	286	Mapping table:
287	287
288		-|**VTL**|**SDMX**
289		-|(Simple) Identifier|Dimension
290		-|(Time) Identifier|TimeDimension
291		-|Measure|Measure
292		-|Attribute|DataAttribute
	283	+(% style="width:470.294px" %)
	284	+|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX**
	285	+|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension
	286	+|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension
	287	+|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure
	288	+|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute
293	293
294	294	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.
295	295
...	...	@@ -317,11 +317,12 @@
317	317
318	318	The summary mapping table of the **unpivot** mapping method is the following:
319	319
320		-|**VTL**|**SDMX**
321		-|(Simple) Identifier|Dimension
322		-|(Time) Identifier|TimeDimension
323		-|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
324		-|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
	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
325	325
326	326	At observation / data point level:
327	327
...	...	@@ -343,12 +343,13 @@
343	343
344	344	The mapping table is the following:
345	345
346		-|VTL|SDMX
347		-|(Simple) Identifier|Dimension
348		-|(Time) Identifier|TimeDimension
349		-|Some Measures|Measure
350		-|Other Measures|DataAttribute
351		-|Attribute|DataAttribute
	343	+(% style="width:467.294px" %)
	344	+|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
	345	+|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
	346	+|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
	347	+|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
	348	+|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
	349	+|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
352	352
353	353	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.
354	354
...	...	@@ -386,11 +386,11 @@
386	386
387	387	Therefore, the generic name of this kind of VTL datasets would be:
388	388
389		-'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
	387	+> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
390	390
391	391	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:
392	392
393		-‘DF(1.0.0)/POPULATION.USA’
	391	+> ‘DF(1.0.0)/POPULATION.USA’
394	394
395	395	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.
396	396
...	...	@@ -404,26 +404,22 @@
404	404
405	405	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.
406	406
407		-In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
	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 …).
408	408
409		-basic, pivot …).
410		-
411	411	In the example above, for all the datasets of the kind
412	412
413		-‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
	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.
414	414
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		-‘DF1(1.0.0)/POPULATION.USA’ :=
	413	+> ‘DF1(1.0.0)/POPULATION.USA’ :=
	414	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
	415	+>
	416	+> ‘DF1(1.0.0)/POPULATION.CANADA’ :=
	417	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
	418	+>
	419	+> … … …
418	418
419		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
420		-
421		-‘DF1(1.0.0)/POPULATION.CANADA’ :=
422		-
423		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
424		-
425		-… … …
426		-
427	427	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}}
428	428
429	429	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.
...	...	@@ -432,10 +432,9 @@
432	432
433	433	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
434	434
435		-‘DF1(1.0.0)/POPULATION.’ :=
	429	+> ‘DF1(1.0.0)/POPULATION.’ :=
	430	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
436	436
437		-DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
438		-
439	439	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
440	440
441	441	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
...	...	@@ -453,41 +453,33 @@
453	453
454	454	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}}
455	455
456		-‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
	449	+> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
457	457
458	458	Some examples follow, for some specific values of INDICATOR and COUNTRY:
459	459
460		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
461		-… … …
	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	+> … … …
462	462
463		-‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
464		-‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
465		-… … …
466		-
467	467	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:
468	468
469		-VTL dataset   INDICATOR value COUNTRY value
	461	+> VTL dataset INDICATOR value COUNTRY value
	462	+>
	463	+> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
	464	+> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
	465	+>
	466	+> ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
	467	+> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
	468	+> … … …
470	470
471		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
472		-‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
473		-‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
474		-‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
475		-
476		-… … …
477		-
478	478	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:
479	479
480		-DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
481		-DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
482		-DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
483		-[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
484		-DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
485		-DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
486		-DF2bis_GDPPERCAPITA_CANADA’,
487		-… ,
488		-DF2bis_POPGROWTH_USA’,
489		-DF2bis_POPGROWTH_CANADA’
490		-…);
	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	+> …);
491	491
492	492	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.
493	493
...	...	@@ -499,25 +499,26 @@
499	499
500	500	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
501	501
502		-|VTL|SDMX
503		-|**Data Set Component**|Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
504		-|**Represented Variable**|**Concept** with a definite Representation
505		-|**Value Domain**|(((
	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" %)(((
506	506	**Representation** (see the Structure
507	507	Pattern in the Base Package)
508	508	)))
509		-|**Enumerated Value Domain / Code List**|**Codelist**
510		-|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
511		-|**Described Value Domain**|(((
	495	+|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
	496	+|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
	497	+|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
512	512	non-enumerated** Representation**
513	513	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
514	514	)))
515		-|**Value**|Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
516		-| |to a valid **value **(for non-enumerated** **Representations)
517		-|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
518		-|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
519		-|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
520		-|**Set list**|This abstraction does not exist in SDMX
	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
521	521
522	522	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).
523	523
...	...	@@ -525,8 +525,10 @@
525	525
526	526	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
527	527
528		-DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
	514	+> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
529	529
	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	+
530	530	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
531	531
532	532	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -541,8 +541,9 @@
541	541
542	542	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:
543	543
544		-[[image:1750067055028-964.png]]
545	545
	533	+[[image:1750070288958-132.png]]
	534	+
546	546	**Figure 22 – VTL Data Types**
547	547
548	548	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.
...	...	@@ -549,6 +549,8 @@
549	549
550	550	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):
551	551
	541	+[[image:1750070310572-584.png]]
	542	+
552	552	**Figure 23 – VTL Basic Scalar Types**
553	553
554	554	=== 12.4.2 VTL basic scalar types and SDMX data types ===
...	...	@@ -573,158 +573,157 @@
573	573
574	574	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
575	575
576		-|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
577		-|(((
	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" %)(((
578	578	String
579	579	(string allowing any character)
580		-)))|string
581		-|(((
582		-Alpha
583		-
	572	+)))|(% style="width:221px" %)string
	573	+|(% style="width:360px" %)(((
	574	+Alpha
584	584	(string which only allows A-z)
585		-)))|string
586		-|(((
	576	+)))|(% style="width:221px" %)string
	577	+|(% style="width:360px" %)(((
587	587	AlphaNumeric
588	588	(string which only allows A-z and 0-9)
589		-)))|string
590		-|(((
	580	+)))|(% style="width:221px" %)string
	581	+|(% style="width:360px" %)(((
591	591	Numeric
592		-
593	593	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
594		-)))|string
595		-|(((
	584	+)))|(% style="width:221px" %)string
	585	+|(% style="width:360px" %)(((
596	596	BigInteger
597	597	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
598		-)))|integer
599		-|(((
	588	+)))|(% style="width:221px" %)integer
	589	+|(% style="width:360px" %)(((
600	600	Integer
601	601	(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
602	602	(inclusive))
603		-)))|integer
604		-|(((
	593	+)))|(% style="width:221px" %)integer
	594	+|(% style="width:360px" %)(((
605	605	Long
606	606	(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
607	607	+9223372036854775807 (inclusive))
608		-)))|integer
609		-|(((
	598	+)))|(% style="width:221px" %)integer
	599	+|(% style="width:360px" %)(((
610	610	Short
611	611	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
612		-)))|integer
613		-|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
614		-|(((
	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" %)(((
615	615	Float
616	616	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
617		-)))|number
618		-|(((
	607	+)))|(% style="width:221px" %)number
	608	+|(% style="width:360px" %)(((
619	619	Double
620	620	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
621		-)))|number
622		-|(((
	611	+)))|(% style="width:221px" %)number
	612	+|(% style="width:360px" %)(((
623	623	Boolean
624	624	(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
625	625	binary-valued logic: {true, false})
626		-)))|boolean
627		-|(((
	616	+)))|(% style="width:221px" %)boolean
	617	+|(% style="width:360px" %)(((
628	628	URI
629	629	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
630		-)))|string
631		-|(((
	620	+)))|(% style="width:221px" %)string
	621	+|(% style="width:360px" %)(((
632	632	Count
633	633	(an integer following a sequential pattern, increasing by 1 for each occurrence)
634		-)))|integer
635		-|(((
	624	+)))|(% style="width:221px" %)integer
	625	+|(% style="width:360px" %)(((
636	636	InclusiveValueRange
637	637	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
638		-)))|number
639		-|(((
	628	+)))|(% style="width:221px" %)number
	629	+|(% style="width:360px" %)(((
640	640	ExclusiveValueRange
641	641	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
642		-)))|number
643		-|(((
	632	+)))|(% style="width:221px" %)number
	633	+|(% style="width:360px" %)(((
644	644	Incremental
645	645	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
646		-)))|number
647		-|(((
	636	+)))|(% style="width:221px" %)number
	637	+|(% style="width:360px" %)(((
648	648	ObservationalTimePeriod
649	649	(superset of StandardTimePeriod and TimeRange)
650		-)))|time
651		-|(((
	640	+)))|(% style="width:221px" %)time
	641	+|(% style="width:360px" %)(((
652	652	StandardTimePeriod
653	653	(superset of BasicTimePeriod and ReportingTimePeriod)
654		-)))|time
655		-|(((
	644	+)))|(% style="width:221px" %)time
	645	+|(% style="width:360px" %)(((
656	656	BasicTimePeriod
657	657	(superset of GregorianTimePeriod and DateTime)
658		-)))|date
659		-|(((
	648	+)))|(% style="width:221px" %)date
	649	+|(% style="width:360px" %)(((
660	660	GregorianTimePeriod
661	661	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
662		-)))|date
663		-|GregorianYear (YYYY)|date
664		-|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
665		-|GregorianDay (YYYY-MM-DD)|date
666		-|(((
	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" %)(((
667	667	ReportingTimePeriod
668	668	(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
669		-)))|time_period
670		-|(((
	659	+)))|(% style="width:221px" %)time_period
	660	+|(% style="width:360px" %)(((
671	671	ReportingYear
672	672	(YYYY-A1 – 1 year period)
673		-)))|time_period
674		-|(((
	663	+)))|(% style="width:221px" %)time_period
	664	+|(% style="width:360px" %)(((
675	675	ReportingSemester
676	676	(YYYY-Ss – 6 month period)
677		-)))|time_period
678		-|(((
	667	+)))|(% style="width:221px" %)time_period
	668	+|(% style="width:360px" %)(((
679	679	ReportingTrimester
680	680	(YYYY-Tt – 4 month period)
681		-)))|time_period
682		-|(((
	671	+)))|(% style="width:221px" %)time_period
	672	+|(% style="width:360px" %)(((
683	683	ReportingQuarter
684	684	(YYYY-Qq – 3 month period)
685		-)))|time_period
686		-|(((
	675	+)))|(% style="width:221px" %)time_period
	676	+|(% style="width:360px" %)(((
687	687	ReportingMonth
688	688	(YYYY-Mmm – 1 month period)
689		-)))|time_period
690		-|ReportingWeek|time_period
691		-| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
692		-|(((
	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" %)(((
693	693	ReportingDay
694	694	(YYYY-Dddd – 1 day period)
695		-)))|time_period
696		-|(((
	685	+)))|(% style="width:221px" %)time_period
	686	+|(% style="width:360px" %)(((
697	697	DateTime
698	698	(YYYY-MM-DDThh:mm:ss)
699		-)))|date
700		-|(((
	689	+)))|(% style="width:221px" %)date
	690	+|(% style="width:360px" %)(((
701	701	TimeRange
702	702	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
703		-)))|time
704		-|(((
	693	+)))|(% style="width:221px" %)time
	694	+|(% style="width:360px" %)(((
705	705	Month
706	706	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
707		-)))|string
708		-|(((
	697	+)))|(% style="width:221px" %)string
	698	+|(% style="width:360px" %)(((
709	709	MonthDay
710	710	(~-~-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)
711		-)))|string
712		-|(((
	701	+)))|(% style="width:221px" %)string
	702	+|(% style="width:360px" %)(((
713	713	Day
714	714	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
715		-)))|string
716		-|(((
	705	+)))|(% style="width:221px" %)string
	706	+|(% style="width:360px" %)(((
717	717	Time
718	718	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
719		-)))|string
720		-|(((
	709	+)))|(% style="width:221px" %)string
	710	+|(% style="width:360px" %)(((
721	721	Duration
722	722	(corresponds to XML Schema xs:duration datatype)
723		-)))|duration
724		-|XHTML|Metadata type – not applicable
725		-|KeyValues|Metadata type – not applicable
726		-|IdentifiableReference|Metadata type – not applicable
727		-|DataSetReference|Metadata type – not applicable
	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
728	728
729	729	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
730	730
...	...	@@ -734,84 +734,82 @@
734	734
735	735	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
736	736
737		-|(((
738		-VTL basic
739		-scalar type
740		-)))|(((
	727	+(% style="width:748.294px" %)
	728	+|(% style="width:164px" %)(((
	729	+VTL basic scalar type
	730	+)))|(% style="width:304px" %)(((
741	741	Default SDMX data type
742		-(BasicComponentDataType
743		-)
744		-)))|Default output format
745		-|String|String|Like XML (xs:string)
746		-|Number|Float|Like XML (xs:float)
747		-|Integer|Integer|Like XML (xs:int)
748		-|Date|DateTime|YYYY-MM-DDT00:00:00Z
749		-|Time|StandardTimePeriod|<date>/<date> (as defined above)
750		-|time_period|(((
	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" %)(((
751	751	ReportingTimePeriod
752	752	(StandardReportingPeriod)
753		-)))|(((
	742	+)))|(% style="width:277px" %)(((
754	754	YYYY-Pppp
755	755	(according to SDMX )
756	756	)))
757		-|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
758		-|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
	746	+|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS
	747	+|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"
759	759
760	760	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
761	761
762		-In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
	751	+In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
763	763
764		-Transformations and Expressions of the SDMX information model).
765		-
766	766	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.
767	767
768		-|(% colspan="2" %)VTL special characters for the formatting masks
769		-|(% colspan="2" %)
770		-|(% colspan="2" %)Number
771		-|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
772		-|E|one numeric digit (for the exponent of the scientific notation)
773		-|. (dot)|possible separator between the integer and the decimal parts.
774		-|, (comma)|possible separator between the integer and the decimal parts.
775		-| |
776		-|(% colspan="2" %)Time and duration
777		-|C|century
778		-|Y|year
779		-|S|semester
780		-|Q|quarter
781		-|M|month
782		-|W|week
783		-|D|day
784		-|h|hour digit (by default on 24 hours)
785		-|M|minute
786		-|S|second
787		-|D|decimal of second
788		-|P|period indicator (representation in one digit for the duration)
789		-|P|number of the periods specified in the period indicator
790		-|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
791		-|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
792		-|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
793		-|Month|lowercase textual representation of the month (e.g., january)
794		-|Day|lowercase textual representation of the month (e.g., monday)
795		-|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
796		-|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
797		-| |
798		-|(% colspan="2" %)String
799		-|X|any string character
800		-|Z|any string character from "A" to "z"
801		-|9|any string character from "0" to "9"
802		-| |
803		-|(% colspan="2" %)Boolean
804		-|B|Boolean using "true" for True and "false" for False
805		-|1|Boolean using "1" for True and "0" for False
806		-|0|Boolean using "0" for True and "1" for False
807		-| |
808		-|(% colspan="2" %)Other qualifiers
809		-|*|an arbitrary number of digits (of the preceding type)
810		-|+|at least one digit (of the preceding type)
811		-|( )|optional digits (specified within the brackets)
812		-|\|prefix for the special characters that must appear in the mask
813		-|N|fixed number of digits used in the preceding textual representation of the month or the day
814		-| |
	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" %)
815	815
816	816	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}}.
817	817

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