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
...	...	@@ -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
	283	+|**VTL**|**SDMX**
	284	+|(Simple) Identifier|Dimension
	285	+|(Time) Identifier|TimeDimension
	286	+|Measure|Measure
	287	+|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
	315	+|**VTL**|**SDMX**
	316	+|(Simple) Identifier|Dimension
	317	+|(Time) Identifier|TimeDimension
	318	+|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
	319	+|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
	341	+|VTL|SDMX
	342	+|(Simple) Identifier|Dimension
	343	+|(Time) Identifier|TimeDimension
	344	+|Some Measures|Measure
	345	+|Other Measures|DataAttribute
	346	+|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'
	384	+'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’
	388	+‘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 …).
	402	+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
	404	+basic, pivot …).
	405	+
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.
	408	+‘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		-> … … …
	412	+‘DF1(1.0.0)/POPULATION.USA’ :=
420	420
	414	+DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
	415	+
	416	+‘DF1(1.0.0)/POPULATION.CANADA’ :=
	417	+
	418	+DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
	419	+
	420	+… … …
	421	+
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” ];
	430	+‘DF1(1.0.0)/POPULATION.’ :=
431	431
	432	+DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
	433	+
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.
...	...	@@ -446,38 +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
	451	+‘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		-> … … …
	455	+‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
	456	+… … …
458	458
	458	+‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
	459	+‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
	460	+… … …
	461	+
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	461	VTL dataset   INDICATOR value COUNTRY value
462	462
463		-> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
464		-> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
465		-> ‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
466		-> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
467		-> … … …
	466	+‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
	467	+‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
	468	+‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
	469	+‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
468	468
	471	+… … …
	472	+
469	469	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:
470	470
471		-> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
472		-> DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
473		-> DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’  [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
474		-> DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
475		-> DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
476		-> DF2bis_GDPPERCAPITA_CANADA’,
477		-> … ,
478		-> DF2bis_POPGROWTH_USA’,
479		-> DF2bis_POPGROWTH_CANADA’
480		-> …);
	475	+DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
	476	+DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
	477	+DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
	478	+[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
	479	+DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
	480	+DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
	481	+DF2bis_GDPPERCAPITA_CANADA’,
	482	+… ,
	483	+DF2bis_POPGROWTH_USA’,
	484	+DF2bis_POPGROWTH_CANADA’
	485	+…);
481	481
482	482	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.
483	483
...	...	@@ -489,26 +489,25 @@
489	489
490	490	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
491	491
492		-(% style="width:706.294px" %)
493		-|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX
494		-|(% 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^^
495		-|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation
496		-|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)(((
	497	+|VTL|SDMX
	498	+|**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^^
	499	+|**Represented Variable**|**Concept** with a definite Representation
	500	+|**Value Domain**|(((
497	497	**Representation** (see the Structure
498	498	Pattern in the Base Package)
499	499	)))
500		-|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
501		-|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
502		-|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
	504	+|**Enumerated Value Domain / Code List**|**Codelist**
	505	+|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
	506	+|**Described Value Domain**|(((
503	503	non-enumerated** Representation**
504	504	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
505	505	)))
506		-|(% 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
507		-|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)
508		-|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
509		-|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
510		-|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
511		-|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX
	510	+|**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
	511	+| |to a valid **value **(for non-enumerated** **Representations)
	512	+|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
	513	+|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
	514	+|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
	515	+|**Set list**|This abstraction does not exist in SDMX
512	512
513	513	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).
514	514
...	...	@@ -516,10 +516,8 @@
516	516
517	517	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
518	518
519		-> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
	523	+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.
520	520
521		-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.
522		-
523	523	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
524	524
525	525	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -534,9 +534,8 @@
534	534
535	535	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:
536	536
	539	+[[image:1750067055028-964.png]]
537	537
538		-[[image:1750070288958-132.png]]
539		-
540	540	**Figure 22 – VTL Data Types**
541	541
542	542	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.
...	...	@@ -543,8 +543,6 @@
543	543
544	544	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):
545	545
546		-[[image:1750070310572-584.png]]
547		-
548	548	**Figure 23 – VTL Basic Scalar Types**
549	549
550	550	=== 12.4.2 VTL basic scalar types and SDMX data types ===
...	...	@@ -569,157 +569,158 @@
569	569
570	570	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
571	571
572		-(% style="width:583.294px" %)
573		-|(% style="width:360px" %)SDMX data type (BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type
574		-|(% style="width:360px" %)(((
	571	+|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
	572	+|(((
575	575	String
576	576	(string allowing any character)
577		-)))|(% style="width:221px" %)string
578		-|(% style="width:360px" %)(((
579		-Alpha
	575	+)))|string
	576	+|(((
	577	+Alpha
	578	+
580	580	(string which only allows A-z)
581		-)))|(% style="width:221px" %)string
582		-|(% style="width:360px" %)(((
	580	+)))|string
	581	+|(((
583	583	AlphaNumeric
584	584	(string which only allows A-z and 0-9)
585		-)))|(% style="width:221px" %)string
586		-|(% style="width:360px" %)(((
	584	+)))|string
	585	+|(((
587	587	Numeric
	587	+
588	588	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
589		-)))|(% style="width:221px" %)string
590		-|(% style="width:360px" %)(((
	589	+)))|string
	590	+|(((
591	591	BigInteger
592	592	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
593		-)))|(% style="width:221px" %)integer
594		-|(% style="width:360px" %)(((
	593	+)))|integer
	594	+|(((
595	595	Integer
596	596	(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
597	597	(inclusive))
598		-)))|(% style="width:221px" %)integer
599		-|(% style="width:360px" %)(((
	598	+)))|integer
	599	+|(((
600	600	Long
601	601	(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
602	602	+9223372036854775807 (inclusive))
603		-)))|(% style="width:221px" %)integer
604		-|(% style="width:360px" %)(((
	603	+)))|integer
	604	+|(((
605	605	Short
606	606	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
607		-)))|(% style="width:221px" %)integer
608		-|(% 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
609		-|(% style="width:360px" %)(((
	607	+)))|integer
	608	+|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
	609	+|(((
610	610	Float
611	611	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
612		-)))|(% style="width:221px" %)number
613		-|(% style="width:360px" %)(((
	612	+)))|number
	613	+|(((
614	614	Double
615	615	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
616		-)))|(% style="width:221px" %)number
617		-|(% style="width:360px" %)(((
	616	+)))|number
	617	+|(((
618	618	Boolean
619	619	(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
620	620	binary-valued logic: {true, false})
621		-)))|(% style="width:221px" %)boolean
622		-|(% style="width:360px" %)(((
	621	+)))|boolean
	622	+|(((
623	623	URI
624	624	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
625		-)))|(% style="width:221px" %)string
626		-|(% style="width:360px" %)(((
	625	+)))|string
	626	+|(((
627	627	Count
628	628	(an integer following a sequential pattern, increasing by 1 for each occurrence)
629		-)))|(% style="width:221px" %)integer
630		-|(% style="width:360px" %)(((
	629	+)))|integer
	630	+|(((
631	631	InclusiveValueRange
632	632	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
633		-)))|(% style="width:221px" %)number
634		-|(% style="width:360px" %)(((
	633	+)))|number
	634	+|(((
635	635	ExclusiveValueRange
636	636	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
637		-)))|(% style="width:221px" %)number
638		-|(% style="width:360px" %)(((
	637	+)))|number
	638	+|(((
639	639	Incremental
640	640	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
641		-)))|(% style="width:221px" %)number
642		-|(% style="width:360px" %)(((
	641	+)))|number
	642	+|(((
643	643	ObservationalTimePeriod
644	644	(superset of StandardTimePeriod and TimeRange)
645		-)))|(% style="width:221px" %)time
646		-|(% style="width:360px" %)(((
	645	+)))|time
	646	+|(((
647	647	StandardTimePeriod
648	648	(superset of BasicTimePeriod and ReportingTimePeriod)
649		-)))|(% style="width:221px" %)time
650		-|(% style="width:360px" %)(((
	649	+)))|time
	650	+|(((
651	651	BasicTimePeriod
652	652	(superset of GregorianTimePeriod and DateTime)
653		-)))|(% style="width:221px" %)date
654		-|(% style="width:360px" %)(((
	653	+)))|date
	654	+|(((
655	655	GregorianTimePeriod
656	656	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
657		-)))|(% style="width:221px" %)date
658		-|(% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date
659		-|(% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date
660		-|(% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date
661		-|(% style="width:360px" %)(((
	657	+)))|date
	658	+|GregorianYear (YYYY)|date
	659	+|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
	660	+|GregorianDay (YYYY-MM-DD)|date
	661	+|(((
662	662	ReportingTimePeriod
663	663	(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
664		-)))|(% style="width:221px" %)time_period
665		-|(% style="width:360px" %)(((
	664	+)))|time_period
	665	+|(((
666	666	ReportingYear
667	667	(YYYY-A1 – 1 year period)
668		-)))|(% style="width:221px" %)time_period
669		-|(% style="width:360px" %)(((
	668	+)))|time_period
	669	+|(((
670	670	ReportingSemester
671	671	(YYYY-Ss – 6 month period)
672		-)))|(% style="width:221px" %)time_period
673		-|(% style="width:360px" %)(((
	672	+)))|time_period
	673	+|(((
674	674	ReportingTrimester
675	675	(YYYY-Tt – 4 month period)
676		-)))|(% style="width:221px" %)time_period
677		-|(% style="width:360px" %)(((
	676	+)))|time_period
	677	+|(((
678	678	ReportingQuarter
679	679	(YYYY-Qq – 3 month period)
680		-)))|(% style="width:221px" %)time_period
681		-|(% style="width:360px" %)(((
	680	+)))|time_period
	681	+|(((
682	682	ReportingMonth
683	683	(YYYY-Mmm – 1 month period)
684		-)))|(% style="width:221px" %)time_period
685		-|(% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period
686		-|(% style="width:360px" %) (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% style="width:221px" %)
687		-|(% style="width:360px" %)(((
	684	+)))|time_period
	685	+|ReportingWeek|time_period
	686	+| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
	687	+|(((
688	688	ReportingDay
689	689	(YYYY-Dddd – 1 day period)
690		-)))|(% style="width:221px" %)time_period
691		-|(% style="width:360px" %)(((
	690	+)))|time_period
	691	+|(((
692	692	DateTime
693	693	(YYYY-MM-DDThh:mm:ss)
694		-)))|(% style="width:221px" %)date
695		-|(% style="width:360px" %)(((
	694	+)))|date
	695	+|(((
696	696	TimeRange
697	697	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
698		-)))|(% style="width:221px" %)time
699		-|(% style="width:360px" %)(((
	698	+)))|time
	699	+|(((
700	700	Month
701	701	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
702		-)))|(% style="width:221px" %)string
703		-|(% style="width:360px" %)(((
	702	+)))|string
	703	+|(((
704	704	MonthDay
705	705	(~-~-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)
706		-)))|(% style="width:221px" %)string
707		-|(% style="width:360px" %)(((
	706	+)))|string
	707	+|(((
708	708	Day
709	709	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
710		-)))|(% style="width:221px" %)string
711		-|(% style="width:360px" %)(((
	710	+)))|string
	711	+|(((
712	712	Time
713	713	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
714		-)))|(% style="width:221px" %)string
715		-|(% style="width:360px" %)(((
	714	+)))|string
	715	+|(((
716	716	Duration
717	717	(corresponds to XML Schema xs:duration datatype)
718		-)))|(% style="width:221px" %)duration
719		-|(% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable
720		-|(% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable
721		-|(% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable
722		-|(% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable
	718	+)))|duration
	719	+|XHTML|Metadata type – not applicable
	720	+|KeyValues|Metadata type – not applicable
	721	+|IdentifiableReference|Metadata type – not applicable
	722	+|DataSetReference|Metadata type – not applicable
723	723
724	724	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
725	725
...	...	@@ -729,82 +729,84 @@
729	729
730	730	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
731	731
732		-(% style="width:748.294px" %)
733		-|(% style="width:164px" %)(((
734		-VTL basic scalar type
735		-)))|(% style="width:304px" %)(((
	732	+|(((
	733	+VTL basic
	734	+scalar type
	735	+)))|(((
736	736	Default SDMX data type
737		-(BasicComponentDataType)
738		-)))|(% style="width:277px" %)Default output format
739		-|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string)
740		-|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float)
741		-|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int)
742		-|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z
743		-|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above)
744		-|(% style="width:164px" %)time_period|(% style="width:304px" %)(((
	737	+(BasicComponentDataType
	738	+)
	739	+)))|Default output format
	740	+|String|String|Like XML (xs:string)
	741	+|Number|Float|Like XML (xs:float)
	742	+|Integer|Integer|Like XML (xs:int)
	743	+|Date|DateTime|YYYY-MM-DDT00:00:00Z
	744	+|Time|StandardTimePeriod|<date>/<date> (as defined above)
	745	+|time_period|(((
745	745	ReportingTimePeriod
746	746	(StandardReportingPeriod)
747		-)))|(% style="width:277px" %)(((
	748	+)))|(((
748	748	YYYY-Pppp
749	749	(according to SDMX )
750	750	)))
751		-|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS
752		-|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"
	752	+|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
	753	+|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
753	753
754	754	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
755	755
756		-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).
	757	+In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
757	757
	759	+Transformations and Expressions of the SDMX information model).
	760	+
758	758	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.
759	759
760		-(% style="width:717.294px" %)
761		-|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks
762		-|(% colspan="2" style="width:714px" %)
763		-|(% colspan="2" style="width:714px" %)Number
764		-|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
765		-|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation)
766		-|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
767		-|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
768		-|(% style="width:122px" %) |(% style="width:591px" %)
769		-|(% colspan="2" style="width:714px" %)Time and duration
770		-|(% style="width:122px" %)C|(% style="width:591px" %)century
771		-|(% style="width:122px" %)Y|(% style="width:591px" %)year
772		-|(% style="width:122px" %)S|(% style="width:591px" %)semester
773		-|(% style="width:122px" %)Q|(% style="width:591px" %)quarter
774		-|(% style="width:122px" %)M|(% style="width:591px" %)month
775		-|(% style="width:122px" %)W|(% style="width:591px" %)week
776		-|(% style="width:122px" %)D|(% style="width:591px" %)day
777		-|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours)
778		-|(% style="width:122px" %)M|(% style="width:591px" %)minute
779		-|(% style="width:122px" %)S|(% style="width:591px" %)second
780		-|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second
781		-|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration)
782		-|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator
783		-|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
784		-|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January)
785		-|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
786		-|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january)
787		-|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday)
788		-|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
789		-|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
790		-|(% style="width:122px" %) |(% style="width:591px" %)
791		-|(% colspan="2" style="width:714px" %)String
792		-|(% style="width:122px" %)X|(% style="width:591px" %)any string character
793		-|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z"
794		-|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9"
795		-|(% style="width:122px" %) |(% style="width:591px" %)
796		-|(% colspan="2" style="width:714px" %)Boolean
797		-|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False
798		-|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False
799		-|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False
800		-|(% style="width:122px" %) |(% style="width:591px" %)
801		-|(% colspan="2" style="width:714px" %)Other qualifiers
802		-|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type)
803		-|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type)
804		-|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets)
805		-|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask
806		-|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day
807		-|(% style="width:122px" %) |(% style="width:591px" %)
	763	+|(% colspan="2" %)VTL special characters for the formatting masks
	764	+|(% colspan="2" %)
	765	+|(% colspan="2" %)Number
	766	+|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
	767	+|E|one numeric digit (for the exponent of the scientific notation)
	768	+|. (dot)|possible separator between the integer and the decimal parts.
	769	+|, (comma)|possible separator between the integer and the decimal parts.
	770	+| |
	771	+|(% colspan="2" %)Time and duration
	772	+|C|century
	773	+|Y|year
	774	+|S|semester
	775	+|Q|quarter
	776	+|M|month
	777	+|W|week
	778	+|D|day
	779	+|h|hour digit (by default on 24 hours)
	780	+|M|minute
	781	+|S|second
	782	+|D|decimal of second
	783	+|P|period indicator (representation in one digit for the duration)
	784	+|P|number of the periods specified in the period indicator
	785	+|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
	786	+|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
	787	+|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
	788	+|Month|lowercase textual representation of the month (e.g., january)
	789	+|Day|lowercase textual representation of the month (e.g., monday)
	790	+|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
	791	+|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
	792	+| |
	793	+|(% colspan="2" %)String
	794	+|X|any string character
	795	+|Z|any string character from "A" to "z"
	796	+|9|any string character from "0" to "9"
	797	+| |
	798	+|(% colspan="2" %)Boolean
	799	+|B|Boolean using "true" for True and "false" for False
	800	+|1|Boolean using "1" for True and "0" for False
	801	+|0|Boolean using "0" for True and "1" for False
	802	+| |
	803	+|(% colspan="2" %)Other qualifiers
	804	+|*|an arbitrary number of digits (of the preceding type)
	805	+|+|at least one digit (of the preceding type)
	806	+|( )|optional digits (specified within the brackets)
	807	+|\|prefix for the special characters that must appear in the mask
	808	+|N|fixed number of digits used in the preceding textual representation of the month or the day
	809	+| |
808	808
809	809	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}}.
810	810

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