Changes for page 12 Validation and Transformation Language (VTL)

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...	...	@@ -14,8 +14,10 @@
14	14
15	15	The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate{{footnote}}In this chapter, in order to distinguish VTL and SDMX model artefacts, the VTL ones are written in the Arial font while the SDMX ones in Courier New{{/footnote}}. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of Transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL "Data Set", which do not correspond one another: as a matter of fact, the VTL "Data Set" maps to the SDMX "Dataflow", while the SDMX "Dataset" has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL Transformations). A SDMX "Dataset", however, is an instance of a SDMX "Dataflow" and can be the artefact on which the VTL transformations are executed (i.e., the Transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
16	16
17		-The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
	17	+The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of
18	18
	19	+Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
	20	+
19	19	This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts.
20	20
21	21	== 12.2 References to SDMX artefacts from VTL statements ==
...	...	@@ -26,8 +26,10 @@
26	26
27	27	The alias of an SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name.
28	28
29		-In any case, the aliases used in the VTL Transformations have to be mapped to the SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
	31	+In any case, the aliases used in the VTL Transformations have to be mapped to the
30	30
	33	+SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
	34	+
31	31	The correspondence between an alias and a SDMX artefact must be one-to-one, meaning that a generic alias identifies one and just one SDMX artefact while a SDMX artefact is identified by one and just one alias. In other words, within a VtlMappingScheme an artefact can have just one alias and different artefacts cannot have the same alias.
32	32
33	33	The references through the URN and the abbreviated URN are described in the following paragraphs.
...	...	@@ -198,7 +198,7 @@
198	198
199	199	=== 12.3.3 Mapping from SDMX to VTL data structures ===
200	200
201		-==== 12.3.3.1 Basic Mapping ====
	205	+**12.3.3.1 Basic Mapping**
202	202
203	203	The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes. When transforming **from SDMX to VTL**, this method consists in leaving the components unchanged and maintaining their names and roles, according to the following table:
204	204
...	...	@@ -228,11 +228,18 @@
228	228	The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation):
229	229
230	230	* A SDMX simple dimension becomes a VTL (simple) identifier and a SDMX TimeDimension becomes a VTL (time) identifier;
231		-* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a Component;
	235	+* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a
	236	+
	237	+Component;
	238	+
232	232	* The SDMX MeasureDimension is not mapped to VTL (it disappears in the VTL Data Structure);
233	233	* The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
234	234	* An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
235		-** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension;
	242	+** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the
	243	+
	244	+AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension;
	245	+
	246	+*
236	236	** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators).
237	237	** Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship.
238	238
...	...	@@ -255,7 +255,10 @@
255	255	At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
256	256
257	257	* The set of SDMX observations having the same values for all the Dimensions except than the MeasureDimension become one multi-measure VTL Data Point, having one Measure for each Code Cj of the SDMX MeasureDimension;
258		-* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
	269	+* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple)
	270	+
	271	+Identifiers, (time) Identifier and Attributes.
	272	+
259	259	* The value of the Measure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj
260	260	* For the SDMX DataAttributes depending on the MeasureDimension, the value of the DataAttribute DA of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Attribute DA_Cj
261	261
...	...	@@ -348,7 +348,7 @@
348	348	The mapping table is the following:
349	349
350	350	(% style="width:689.294px" %)
351		-|(% style="width:344px" %)**VTL**|(% style="width:341px" %)**SDMX**
	365	+|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX
352	352	|(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension
353	353	|(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension
354	354	|(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure
...	...	@@ -408,16 +408,22 @@
408	408
409	409	SDMX Dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=// COUNTRYvalue//. For example, the VTL dataset ‘DF1(1.0.0)/POPULATION.USA’ would contain all the observations of DF1(1.0.0) having INDICATOR = POPULATION and COUNTRY = USA.
410	410
411		-In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
	425	+In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
412	412
413		-In the example above, for all the datasets of the kind ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
	427	+basic, pivot …).
414	414
	429	+In the example above, for all the datasets of the kind
	430	+
	431	+‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
	432	+
415	415	It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression:
416	416
417	417	‘DF1(1.0.0)/POPULATION.USA’ :=
	436	+
418	418	DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
419	419
420	420	‘DF1(1.0.0)/POPULATION.CANADA’ :=
	440	+
421	421	DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
422	422
423	423	… … …
...	...	@@ -433,6 +433,7 @@
433	433	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
434	434
435	435	‘DF1(1.0.0)/POPULATION.’ :=
	456	+
436	436	DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
437	437
438	438	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
...	...	@@ -463,8 +463,11 @@
463	463	‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
464	464
465	465	… … …
	487	+
466	466	‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
	489	+
467	467	‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
	491	+
468	468	… … …
469	469
470	470	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:
...	...	@@ -612,159 +612,204 @@
612	612
613	613	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
614	614
615		-(% style="width:823.294px" %)
616		-|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type**
617		-|(% style="width:509px" %)(((
	639	+|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
	640	+|(((
618	618	String
	642	+
619	619	(string allowing any character)
620		-)))|(% style="width:312px" %)string
621		-|(% style="width:509px" %)(((
	644	+)))|string
	645	+|(((
622	622	Alpha
	647	+
623	623	(string which only allows A-z)
624		-)))|(% style="width:312px" %)string
625		-|(% style="width:509px" %)(((
	649	+)))|string
	650	+|(((
626	626	AlphaNumeric
	652	+
627	627	(string which only allows A-z and 0-9)
628		-)))|(% style="width:312px" %)string
629		-|(% style="width:509px" %)(((
	654	+)))|string
	655	+|(((
630	630	Numeric
	657	+
631	631	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
632		-)))|(% style="width:312px" %)string
633		-|(% style="width:509px" %)(((
	659	+)))|string
	660	+|(((
634	634	BigInteger
	662	+
635	635	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
636		-)))|(% style="width:312px" %)integer
637		-|(% style="width:509px" %)(((
	664	+)))|integer
	665	+|(((
638	638	Integer
639		-(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
640		-)))|(% style="width:312px" %)integer
641		-|(% style="width:509px" %)(((
	667	+
	668	+(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
	669	+
	670	+(inclusive))
	671	+)))|integer
	672	+|(((
642	642	Long
643		-(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
644		-)))|(% style="width:312px" %)integer
645		-|(% style="width:509px" %)(((
	674	+
	675	+(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
	676	+
	677	++9223372036854775807 (inclusive))
	678	+)))|integer
	679	+|(((
646	646	Short
	681	+
647	647	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
648		-)))|(% style="width:312px" %)integer
649		-|(% style="width:509px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:312px" %)number
650		-|(% style="width:509px" %)(((
	683	+)))|integer
	684	+|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
	685	+|(((
651	651	Float
	687	+
652	652	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
653		-)))|(% style="width:312px" %)number
654		-|(% style="width:509px" %)(((
	689	+)))|number
	690	+|(((
655	655	Double
	692	+
656	656	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
657		-)))|(% style="width:312px" %)number
658		-|(% style="width:509px" %)(((
	694	+)))|number
	695	+|(((
659	659	Boolean
660		-(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
661		-)))|(% style="width:312px" %)boolean
662	662
663		-(% style="width:822.294px" %)
664		-|(% colspan="2" style="width:507px" %)(((
	698	+(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
	699	+
	700	+binary-valued logic: {true, false})
	701	+)))|boolean
	702	+
	703	+| |(% colspan="2" %)(((
665	665	URI
	705	+
666	666	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
667		-)))|(% colspan="1" style="width:311px" %)string
668		-|(% colspan="2" style="width:507px" %)(((
	707	+)))|(% colspan="2" %)string
	708	+| |(% colspan="2" %)(((
669	669	Count
	710	+
670	670	(an integer following a sequential pattern, increasing by 1 for each occurrence)
671		-)))|(% colspan="1" style="width:311px" %)integer
672		-|(% colspan="2" style="width:507px" %)(((
	712	+)))|(% colspan="2" %)integer
	713	+| |(% colspan="2" %)(((
673	673	InclusiveValueRange
	715	+
674	674	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
675		-)))|(% colspan="1" style="width:311px" %)number
676		-|(% colspan="2" style="width:507px" %)(((
	717	+)))|(% colspan="2" %)number
	718	+| |(% colspan="2" %)(((
677	677	ExclusiveValueRange
	720	+
678	678	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
679		-)))|(% colspan="1" style="width:311px" %)number
680		-|(% colspan="2" style="width:507px" %)(((
	722	+)))|(% colspan="2" %)number
	723	+| |(% colspan="2" %)(((
681	681	Incremental
	725	+
682	682	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
683		-)))|(% colspan="1" style="width:311px" %)number
684		-|(% colspan="2" style="width:507px" %)(((
	727	+)))|(% colspan="2" %)number
	728	+| |(% colspan="2" %)(((
685	685	ObservationalTimePeriod
	730	+
686	686	(superset of StandardTimePeriod and TimeRange)
687		-)))|(% colspan="1" style="width:311px" %)time
688		-|(% colspan="2" style="width:507px" %)(((
	732	+)))|(% colspan="2" %)time
	733	+| |(% colspan="2" %)(((
689	689	StandardTimePeriod
690		-(superset of BasicTimePeriod and ReportingTimePeriod)
691		-)))|(% colspan="1" style="width:311px" %)time
692		-|(% colspan="2" style="width:507px" %)(((
	735	+
	736	+(superset of BasicTimePeriod and
	737	+
	738	+ReportingTimePeriod)
	739	+)))|(% colspan="2" %)time
	740	+| |(% colspan="2" %)(((
693	693	BasicTimePeriod
	742	+
694	694	(superset of GregorianTimePeriod and DateTime)
695		-)))|(% colspan="1" style="width:311px" %)date
696		-|(% colspan="2" style="width:507px" %)(((
	744	+)))|(% colspan="2" %)date
	745	+| |(% colspan="2" %)(((
697	697	GregorianTimePeriod
	747	+
698	698	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
699		-)))|(% colspan="1" style="width:311px" %)date
700		-|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date
701		-|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date
702		-|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date
703		-|(% colspan="2" style="width:507px" %)(((
	749	+)))|(% colspan="2" %)date
	750	+| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
	751	+| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
	752	+| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
	753	+| |(% colspan="2" %)(((
704	704	ReportingTimePeriod
705		-(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
706		-)))|(% colspan="1" style="width:311px" %)time_period
707		-|(% colspan="2" style="width:507px" %)(((
	755	+
	756	+(superset of RepostingYear, ReportingSemester,
	757	+
	758	+ReportingTrimester, ReportingQuarter,
	759	+
	760	+ReportingMonth, ReportingWeek, ReportingDay)
	761	+)))|(% colspan="2" %)time_period
	762	+| |(% colspan="2" %)(((
708	708	ReportingYear
	764	+
709	709	(YYYY-A1 – 1 year period)
710		-)))|(% colspan="1" style="width:311px" %)time_period
711		-|(% colspan="2" style="width:507px" %)(((
	766	+)))|(% colspan="2" %)time_period
	767	+| |(% colspan="2" %)(((
712	712	ReportingSemester
	769	+
713	713	(YYYY-Ss – 6 month period)
714		-)))|(% colspan="1" style="width:311px" %)time_period
715		-|(% colspan="2" style="width:507px" %)(((
	771	+)))|(% colspan="2" %)time_period
	772	+| |(% colspan="2" %)(((
716	716	ReportingTrimester
	774	+
717	717	(YYYY-Tt – 4 month period)
718		-)))|(% colspan="1" style="width:311px" %)time_period
719		-|(% colspan="2" style="width:507px" %)(((
	776	+)))|(% colspan="2" %)time_period
	777	+| |(% colspan="2" %)(((
720	720	ReportingQuarter
	779	+
721	721	(YYYY-Qq – 3 month period)
722		-)))|(% colspan="1" style="width:311px" %)time_period
723		-|(% colspan="2" style="width:507px" %)(((
	781	+)))|(% colspan="2" %)time_period
	782	+| |(% colspan="2" %)(((
724	724	ReportingMonth
	784	+
725	725	(YYYY-Mmm – 1 month period)
726		-)))|(% colspan="1" style="width:311px" %)time_period
727		-|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period
728		-|(% colspan="1" style="width:507px" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" style="width:312px" %)
729		-|(% colspan="1" style="width:507px" %)(((
	786	+)))|(% colspan="2" %)time_period
	787	+| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
	788	+| |(% colspan="2" %) |(% colspan="2" %)
	789	+| |(% colspan="2" %) |(% colspan="2" %)
	790	+|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) |
	791	+|(% colspan="2" %)(((
730	730	ReportingDay
	793	+
731	731	(YYYY-Dddd – 1 day period)
732		-)))|(% colspan="2" style="width:312px" %)time_period
733		-|(% colspan="1" style="width:507px" %)(((
	795	+)))|(% colspan="2" %)time_period|
	796	+|(% colspan="2" %)(((
734	734	DateTime
	798	+
735	735	(YYYY-MM-DDThh:mm:ss)
736		-)))|(% colspan="2" style="width:312px" %)date
737		-|(% colspan="1" style="width:507px" %)(((
	800	+)))|(% colspan="2" %)date|
	801	+|(% colspan="2" %)(((
738	738	TimeRange
	803	+
739	739	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
740		-)))|(% colspan="2" style="width:312px" %)time
741		-|(% colspan="1" style="width:507px" %)(((
	805	+)))|(% colspan="2" %)time|
	806	+|(% colspan="2" %)(((
742	742	Month
	808	+
743	743	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
744		-)))|(% colspan="2" style="width:312px" %)string
745		-|(% colspan="1" style="width:507px" %)(((
	810	+)))|(% colspan="2" %)string|
	811	+|(% colspan="2" %)(((
746	746	MonthDay
	813	+
747	747	(~-~-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)
748		-)))|(% colspan="2" style="width:312px" %)string
749		-|(% colspan="1" style="width:507px" %)(((
	815	+)))|(% colspan="2" %)string|
	816	+|(% colspan="2" %)(((
750	750	Day
	818	+
751	751	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
752		-)))|(% colspan="2" style="width:312px" %)string
753		-|(% colspan="1" style="width:507px" %)(((
	820	+)))|(% colspan="2" %)string|
	821	+|(% colspan="2" %)(((
754	754	Time
	823	+
755	755	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
756		-)))|(% colspan="2" style="width:312px" %)string
757		-|(% colspan="1" style="width:507px" %)(((
	825	+)))|(% colspan="2" %)string|
	826	+|(% colspan="2" %)(((
758	758	Duration
	828	+
759	759	(corresponds to XML Schema xs:duration datatype)
760		-)))|(% colspan="2" style="width:312px" %)duration
761		-|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable
762		-|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable
763		-|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
764		-|(% colspan="1" style="width:507px" %)DataSetReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
	830	+)))|(% colspan="2" %)duration|
	831	+|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
	832	+|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
	833	+|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
	834	+|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
765	765
766		-(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %)
767		-**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
	836	+==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
768	768
769	769	When VTL takes in input SDMX artefacts, it is assumed that a type conversion according to the table above always happens. In case a different VTL basic scalar type is desired, it can be achieved in the VTL program taking in input the default VTL basic scalar type above and applying to it the VTL type conversion features (see the implicit and explicit type conversion and the "cast" operator in the VTL Reference Manual).
770	770
...	...	@@ -772,32 +772,39 @@
772	772
773	773	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
774	774
775		-(% style="width:1073.29px" %)
776		-|(% style="width:207px" %)(((
777		-**VTL basic scalar type**
778		-)))|(% style="width:462px" %)(((
779		-**Default SDMX data type (BasicComponentDataType)**
780		-)))|(% style="width:402px" %)**Default output format**
781		-|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string)
782		-|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float)
783		-|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int)
784		-|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z
785		-|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above)
786		-|(% style="width:207px" %)time_period|(% style="width:462px" %)(((
	844	+|(((
	845	+VTL basic
	846	+
	847	+scalar type
	848	+)))|(((
	849	+Default SDMX data type
	850	+
	851	+(BasicComponentDataType
	852	+
	853	+)
	854	+)))|Default output format
	855	+|String|String|Like XML (xs:string)
	856	+|Number|Float|Like XML (xs:float)
	857	+|Integer|Integer|Like XML (xs:int)
	858	+|Date|DateTime|YYYY-MM-DDT00:00:00Z
	859	+|Time|StandardTimePeriod|<date>/<date> (as defined above)
	860	+|time_period|(((
787	787	ReportingTimePeriod
	862	+
788	788	(StandardReportingPeriod)
789		-)))|(% style="width:402px" %)(((
	864	+)))|(((
790	790	YYYY-Pppp
	866	+
791	791	(according to SDMX )
792	792	)))
793		-|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)(((
	869	+|Duration|Duration|(((
794	794	Like XML (xs:duration)
	871	+
795	795	PnYnMnDTnHnMnS
796	796	)))
797		-|(% style="width:207px" %)Boolean|(% style="width:462px" %)Boolean|(% style="width:402px" %)Like XML (xs:boolean) with the values "true" or "false"
	874	+|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
798	798
799		-(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes-1" %)
800		-**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
	876	+==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
801	801
802	802	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).
803	803
...	...	@@ -851,7 +851,7 @@
851	851	|N|fixed number of digits used in the preceding textual representation of the month or the day
852	852	| |
853	853
854		-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}}.
	930	+The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
855	855
856	856	=== 12.4.5 Null Values ===
857	857
...	...	@@ -869,8 +869,10 @@
869	869
870	870	A different format can be specified in the attribute "vtlLiteralFormat" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model).
871	871
872		-Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL TransformationScheme.
	948	+Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL
873	873
	950	+TransformationScheme.
	951	+
874	874	In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
875	875
876	876	{{putFootnotes/}}