Changes for page 12 Validation and Transformation Language (VTL)

Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -14,8 +14,10 @@
14	14
15	15	The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate{{footnote}}In this chapter, in order to distinguish VTL and SDMX model artefacts, the VTL ones are written in the Arial font while the SDMX ones in Courier New{{/footnote}}. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of Transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL "Data Set", which do not correspond one another: as a matter of fact, the VTL "Data Set" maps to the SDMX "Dataflow", while the SDMX "Dataset" has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL Transformations). A SDMX "Dataset", however, is an instance of a SDMX "Dataflow" and can be the artefact on which the VTL transformations are executed (i.e., the Transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
16	16
17		-The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
	17	+The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of
18	18
	19	+Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
	20	+
19	19	This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts.
20	20
21	21	== 12.2 References to SDMX artefacts from VTL statements ==
...	...	@@ -241,7 +241,7 @@
241	241
242	242	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;
243	243
244		-*
	246	+*
245	245	** 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).
246	246	** 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.
247	247
...	...	@@ -529,9 +529,9 @@
529	529
530	530	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
531	531
532		-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.
	534	+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)^^[[(% 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" %)^^37^^>>path:#sdfootnote37sym||name="sdfootnote37anc"]](%%)^^, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
533	533
534		-Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets.{{footnote}}In case the ordered concatenation notation from VTL to SDMX is used, the set of Transformations described above is implicitly performed; therefore, in order to test the overall compliance of the VTL program to the VTL consistency rules, these implicit Transformations have to be considered as part of the VTL program even if they are not explicitly coded.{{/footnote}}
	536	+Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. ^^[[(% 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" %)^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]](%%)[[(% 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" %)^^39^^>>path:#sdfootnote39sym||name="sdfootnote39anc"]](%%)^^
535	535
536	536	It is worth noting that in the direction from VTL to SDMX it is mandatory to specify the value for every Dimension on which the mapping is based (in other word, in the name of the calculated VTL dataset is __not__ possible to omit the value of some of the Dimensions).
537	537
...	...	@@ -539,51 +539,52 @@
539	539
540	540	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
541	541
542		-(% style="width:1170.29px" %)
543		-|**VTL**|(% style="width:754px" %)**SDMX**
544		-|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
545		-|**Represented Variable**|(% style="width:754px" %)(((
	544	+|VTL|SDMX
	545	+|**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^^
	546	+|**Represented Variable**|(((
546	546	**Concept** with a definite
547	547
548	548	Representation
549	549	)))
550		-|**Value Domain**|(% style="width:754px" %)(((
	551	+|**Value Domain**|(((
551	551	**Representation** (see the Structure
552	552
553	553	Pattern in the Base Package)
554	554	)))
555		-|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
556		-|**Code**|(% style="width:754px" %)(((
	556	+|**Enumerated Value Domain / Code List**|**Codelist**
	557	+|**Code**|(((
557	557	**Code** (for enumerated
558	558
559	559	DimensionComponent, Measure, DataAttribute)
560	560	)))
561		-|**Described Value Domain**|(% style="width:754px" %)(((
562		-non-enumerated** Representation**
	562	+|**Described Value Domain**|(((
	563	+non-enumerated**    Representation**
563	563
564	564	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
565	565	)))
566		-|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
567		-| |(% style="width:754px" %)(((
568		-to a valid **value **(for non-enumerated** **Representations)
	567	+|**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
	568	+| |(((
	569	+to a valid **value    **(for non-enumerated**    **
	570	+
	571	+Representations)
569	569	)))
570		-|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
571		-|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
572		-|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
573		-|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
	573	+|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
	574	+|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
	575	+|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
	576	+|**Set list**|This abstraction does not exist in SDMX
574	574
575	575	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).
576	576
577		-Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear{{footnote}}By using represented variables, VTL can assume that data structures having the same variables as identifiers can be composed one another because the correspondent values can match.{{/footnote}}, while the SDMX Concepts can have different Representations in different DataStructures.{{footnote}}A Concept becomes a Component in a DataStructureDefinition, and Components can have different LocalRepresentations in different DataStructureDefinitions, also overriding the (possible) base representation of the Concept.{{/footnote}} This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
	580	+Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^40^^>>path:#sdfootnote40sym||name="sdfootnote40anc"]](%%)^^, while the SDMX Concepts can have different Representations in different DataStructures.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
578	578
579	579	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
580	580
581		-DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
	584	+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.
582	582
583		-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.
584		-
585	585	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
586	586
	588	+[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape5" height="1" width="192"]]
	589	+
587	587	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
588	588
589	589	It remains up to the SDMX-VTL definer also the assurance of the consistency between a VTL Ruleset defined on Variables and the SDMX Components on which the Ruleset is applied. In fact, a VTL Ruleset is expressed by means of the values of the Variables (i.e. SDMX Concepts), i.e. assuming definite representations for them (e.g. ISOalpha-3 for country). If the Ruleset is applied to SDMX Components that have the same name of the Concept they refer to but different representations (e.g. ISO-alpha-2 for country), the Ruleset cannot work properly.
...	...	@@ -598,8 +598,7 @@
598	598
599	599	[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
600	600
601		-(% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
602		-**Figure 22 – VTL Data Types**
	604	+==== Figure 22 – VTL Data Types ====
603	603
604	604	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.
605	605
...	...	@@ -606,12 +606,131 @@
606	606	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):
607	607
608	608
609		-**Figure 23 – VTL Basic Scalar Types**
610	610
611	611	(((
612		-
	613	+//n//
	614	+
	615	+//a//
	616	+
	617	+//e//
	618	+
	619	+//l//
	620	+
	621	+//o//
	622	+
	623	+//o//
	624	+
	625	+//B//
	626	+
	627	+//n//
	628	+
	629	+//o//
	630	+
	631	+//i//
	632	+
	633	+//t//
	634	+
	635	+//a//
	636	+
	637	+//r//
	638	+
	639	+//u//
	640	+
	641	+//D//
	642	+
	643	+//d//
	644	+
	645	+//o//
	646	+
	647	+//i//
	648	+
	649	+//r//
	650	+
	651	+//e//
	652	+
	653	+//p//
	654	+
	655	+//_//
	656	+
	657	+//e//
	658	+
	659	+//m//
	660	+
	661	+//i//
	662	+
	663	+//T//
	664	+
	665	+//e//
	666	+
	667	+//t//
	668	+
	669	+//a//
	670	+
	671	+//D//
	672	+
	673	+//e//
	674	+
	675	+//m//
	676	+
	677	+//i//
	678	+
	679	+//T//
	680	+
	681	+//r//
	682	+
	683	+//e//
	684	+
	685	+//g//
	686	+
	687	+//e//
	688	+
	689	+//t//
	690	+
	691	+//n//
	692	+
	693	+//I//
	694	+
	695	+//r//
	696	+
	697	+//e//
	698	+
	699	+//b//
	700	+
	701	+//m//
	702	+
	703	+//u//
	704	+
	705	+//N//
	706	+
	707	+//g//
	708	+
	709	+//n//
	710	+
	711	+//i//
	712	+
	713	+//r//
	714	+
	715	+//t//
	716	+
	717	+//S//
	718	+
	719	+//r//
	720	+
	721	+//a//
	722	+
	723	+//l//
	724	+
	725	+//a//
	726	+
	727	+//c//
	728	+
	729	+//S//
	730	+
	731	+[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_82d45833.gif||alt="Shape6" height="231" width="184"]]
613	613	)))
614	614
	734	+==== Figure 23 – VTL Basic Scalar Types ====
	735	+
615	615	=== 12.4.2 VTL basic scalar types and SDMX data types ===
616	616
617	617	The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
...	...	@@ -634,159 +634,204 @@
634	634
635	635	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
636	636
637		-(% style="width:823.294px" %)
638		-|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type**
639		-|(% style="width:509px" %)(((
	758	+|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
	759	+|(((
640	640	String
	761	+
641	641	(string allowing any character)
642		-)))|(% style="width:312px" %)string
643		-|(% style="width:509px" %)(((
	763	+)))|string
	764	+|(((
644	644	Alpha
	766	+
645	645	(string which only allows A-z)
646		-)))|(% style="width:312px" %)string
647		-|(% style="width:509px" %)(((
	768	+)))|string
	769	+|(((
648	648	AlphaNumeric
	771	+
649	649	(string which only allows A-z and 0-9)
650		-)))|(% style="width:312px" %)string
651		-|(% style="width:509px" %)(((
	773	+)))|string
	774	+|(((
652	652	Numeric
	776	+
653	653	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
654		-)))|(% style="width:312px" %)string
655		-|(% style="width:509px" %)(((
	778	+)))|string
	779	+|(((
656	656	BigInteger
	781	+
657	657	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
658		-)))|(% style="width:312px" %)integer
659		-|(% style="width:509px" %)(((
	783	+)))|integer
	784	+|(((
660	660	Integer
661		-(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
662		-)))|(% style="width:312px" %)integer
663		-|(% style="width:509px" %)(((
	786	+
	787	+(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
	788	+
	789	+(inclusive))
	790	+)))|integer
	791	+|(((
664	664	Long
665		-(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
666		-)))|(% style="width:312px" %)integer
667		-|(% style="width:509px" %)(((
	793	+
	794	+(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
	795	+
	796	++9223372036854775807 (inclusive))
	797	+)))|integer
	798	+|(((
668	668	Short
	800	+
669	669	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
670		-)))|(% style="width:312px" %)integer
671		-|(% 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
672		-|(% style="width:509px" %)(((
	802	+)))|integer
	803	+|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
	804	+|(((
673	673	Float
	806	+
674	674	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
675		-)))|(% style="width:312px" %)number
676		-|(% style="width:509px" %)(((
	808	+)))|number
	809	+|(((
677	677	Double
	811	+
678	678	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
679		-)))|(% style="width:312px" %)number
680		-|(% style="width:509px" %)(((
	813	+)))|number
	814	+|(((
681	681	Boolean
682		-(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
683		-)))|(% style="width:312px" %)boolean
684	684
685		-(% style="width:822.294px" %)
686		-|(% colspan="2" style="width:507px" %)(((
	817	+(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
	818	+
	819	+binary-valued logic: {true, false})
	820	+)))|boolean
	821	+
	822	+| |(% colspan="2" %)(((
687	687	URI
	824	+
688	688	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
689		-)))|(% colspan="1" style="width:311px" %)string
690		-|(% colspan="2" style="width:507px" %)(((
	826	+)))|(% colspan="2" %)string
	827	+| |(% colspan="2" %)(((
691	691	Count
	829	+
692	692	(an integer following a sequential pattern, increasing by 1 for each occurrence)
693		-)))|(% colspan="1" style="width:311px" %)integer
694		-|(% colspan="2" style="width:507px" %)(((
	831	+)))|(% colspan="2" %)integer
	832	+| |(% colspan="2" %)(((
695	695	InclusiveValueRange
	834	+
696	696	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
697		-)))|(% colspan="1" style="width:311px" %)number
698		-|(% colspan="2" style="width:507px" %)(((
	836	+)))|(% colspan="2" %)number
	837	+| |(% colspan="2" %)(((
699	699	ExclusiveValueRange
	839	+
700	700	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
701		-)))|(% colspan="1" style="width:311px" %)number
702		-|(% colspan="2" style="width:507px" %)(((
	841	+)))|(% colspan="2" %)number
	842	+| |(% colspan="2" %)(((
703	703	Incremental
	844	+
704	704	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
705		-)))|(% colspan="1" style="width:311px" %)number
706		-|(% colspan="2" style="width:507px" %)(((
	846	+)))|(% colspan="2" %)number
	847	+| |(% colspan="2" %)(((
707	707	ObservationalTimePeriod
	849	+
708	708	(superset of StandardTimePeriod and TimeRange)
709		-)))|(% colspan="1" style="width:311px" %)time
710		-|(% colspan="2" style="width:507px" %)(((
	851	+)))|(% colspan="2" %)time
	852	+| |(% colspan="2" %)(((
711	711	StandardTimePeriod
712		-(superset of BasicTimePeriod and ReportingTimePeriod)
713		-)))|(% colspan="1" style="width:311px" %)time
714		-|(% colspan="2" style="width:507px" %)(((
	854	+
	855	+(superset of BasicTimePeriod and
	856	+
	857	+ReportingTimePeriod)
	858	+)))|(% colspan="2" %)time
	859	+| |(% colspan="2" %)(((
715	715	BasicTimePeriod
	861	+
716	716	(superset of GregorianTimePeriod and DateTime)
717		-)))|(% colspan="1" style="width:311px" %)date
718		-|(% colspan="2" style="width:507px" %)(((
	863	+)))|(% colspan="2" %)date
	864	+| |(% colspan="2" %)(((
719	719	GregorianTimePeriod
	866	+
720	720	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
721		-)))|(% colspan="1" style="width:311px" %)date
722		-|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date
723		-|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date
724		-|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date
725		-|(% colspan="2" style="width:507px" %)(((
	868	+)))|(% colspan="2" %)date
	869	+| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
	870	+| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
	871	+| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
	872	+| |(% colspan="2" %)(((
726	726	ReportingTimePeriod
727		-(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
728		-)))|(% colspan="1" style="width:311px" %)time_period
729		-|(% colspan="2" style="width:507px" %)(((
	874	+
	875	+(superset of RepostingYear, ReportingSemester,
	876	+
	877	+ReportingTrimester, ReportingQuarter,
	878	+
	879	+ReportingMonth, ReportingWeek, ReportingDay)
	880	+)))|(% colspan="2" %)time_period
	881	+| |(% colspan="2" %)(((
730	730	ReportingYear
	883	+
731	731	(YYYY-A1 – 1 year period)
732		-)))|(% colspan="1" style="width:311px" %)time_period
733		-|(% colspan="2" style="width:507px" %)(((
	885	+)))|(% colspan="2" %)time_period
	886	+| |(% colspan="2" %)(((
734	734	ReportingSemester
	888	+
735	735	(YYYY-Ss – 6 month period)
736		-)))|(% colspan="1" style="width:311px" %)time_period
737		-|(% colspan="2" style="width:507px" %)(((
	890	+)))|(% colspan="2" %)time_period
	891	+| |(% colspan="2" %)(((
738	738	ReportingTrimester
	893	+
739	739	(YYYY-Tt – 4 month period)
740		-)))|(% colspan="1" style="width:311px" %)time_period
741		-|(% colspan="2" style="width:507px" %)(((
	895	+)))|(% colspan="2" %)time_period
	896	+| |(% colspan="2" %)(((
742	742	ReportingQuarter
	898	+
743	743	(YYYY-Qq – 3 month period)
744		-)))|(% colspan="1" style="width:311px" %)time_period
745		-|(% colspan="2" style="width:507px" %)(((
	900	+)))|(% colspan="2" %)time_period
	901	+| |(% colspan="2" %)(((
746	746	ReportingMonth
	903	+
747	747	(YYYY-Mmm – 1 month period)
748		-)))|(% colspan="1" style="width:311px" %)time_period
749		-|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period
750		-|(% 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" %)
751		-|(% colspan="1" style="width:507px" %)(((
	905	+)))|(% colspan="2" %)time_period
	906	+| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
	907	+| |(% colspan="2" %) |(% colspan="2" %)
	908	+| |(% colspan="2" %) |(% colspan="2" %)
	909	+|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) |
	910	+|(% colspan="2" %)(((
752	752	ReportingDay
	912	+
753	753	(YYYY-Dddd – 1 day period)
754		-)))|(% colspan="2" style="width:312px" %)time_period
755		-|(% colspan="1" style="width:507px" %)(((
	914	+)))|(% colspan="2" %)time_period|
	915	+|(% colspan="2" %)(((
756	756	DateTime
	917	+
757	757	(YYYY-MM-DDThh:mm:ss)
758		-)))|(% colspan="2" style="width:312px" %)date
759		-|(% colspan="1" style="width:507px" %)(((
	919	+)))|(% colspan="2" %)date|
	920	+|(% colspan="2" %)(((
760	760	TimeRange
	922	+
761	761	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
762		-)))|(% colspan="2" style="width:312px" %)time
763		-|(% colspan="1" style="width:507px" %)(((
	924	+)))|(% colspan="2" %)time|
	925	+|(% colspan="2" %)(((
764	764	Month
	927	+
765	765	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
766		-)))|(% colspan="2" style="width:312px" %)string
767		-|(% colspan="1" style="width:507px" %)(((
	929	+)))|(% colspan="2" %)string|
	930	+|(% colspan="2" %)(((
768	768	MonthDay
	932	+
769	769	(~-~-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)
770		-)))|(% colspan="2" style="width:312px" %)string
771		-|(% colspan="1" style="width:507px" %)(((
	934	+)))|(% colspan="2" %)string|
	935	+|(% colspan="2" %)(((
772	772	Day
	937	+
773	773	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
774		-)))|(% colspan="2" style="width:312px" %)string
775		-|(% colspan="1" style="width:507px" %)(((
	939	+)))|(% colspan="2" %)string|
	940	+|(% colspan="2" %)(((
776	776	Time
	942	+
777	777	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
778		-)))|(% colspan="2" style="width:312px" %)string
779		-|(% colspan="1" style="width:507px" %)(((
	944	+)))|(% colspan="2" %)string|
	945	+|(% colspan="2" %)(((
780	780	Duration
	947	+
781	781	(corresponds to XML Schema xs:duration datatype)
782		-)))|(% colspan="2" style="width:312px" %)duration
783		-|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable
784		-|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable
785		-|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
786		-|(% colspan="1" style="width:507px" %)DataSetReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
	949	+)))|(% colspan="2" %)duration|
	950	+|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
	951	+|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
	952	+|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
	953	+|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
787	787
788		-(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %)
789		-**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
	955	+==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
790	790
791	791	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).
792	792
...	...	@@ -794,32 +794,39 @@
794	794
795	795	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
796	796
797		-(% style="width:1073.29px" %)
798		-|(% style="width:207px" %)(((
799		-**VTL basic scalar type**
800		-)))|(% style="width:462px" %)(((
801		-**Default SDMX data type (BasicComponentDataType)**
802		-)))|(% style="width:402px" %)**Default output format**
803		-|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string)
804		-|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float)
805		-|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int)
806		-|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z
807		-|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above)
808		-|(% style="width:207px" %)time_period|(% style="width:462px" %)(((
	963	+|(((
	964	+VTL basic
	965	+
	966	+scalar type
	967	+)))|(((
	968	+Default SDMX data type
	969	+
	970	+(BasicComponentDataType
	971	+
	972	+)
	973	+)))|Default output format
	974	+|String|String|Like XML (xs:string)
	975	+|Number|Float|Like XML (xs:float)
	976	+|Integer|Integer|Like XML (xs:int)
	977	+|Date|DateTime|YYYY-MM-DDT00:00:00Z
	978	+|Time|StandardTimePeriod|<date>/<date> (as defined above)
	979	+|time_period|(((
809	809	ReportingTimePeriod
	981	+
810	810	(StandardReportingPeriod)
811		-)))|(% style="width:402px" %)(((
	983	+)))|(((
812	812	YYYY-Pppp
	985	+
813	813	(according to SDMX )
814	814	)))
815		-|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)(((
	988	+|Duration|Duration|(((
816	816	Like XML (xs:duration)
	990	+
817	817	PnYnMnDTnHnMnS
818	818	)))
819		-|(% style="width:207px" %)Boolean|(% style="width:462px" %)Boolean|(% style="width:402px" %)Like XML (xs:boolean) with the values "true" or "false"
	993	+|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
820	820
821		-(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes-1" %)
822		-**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
	995	+==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
823	823
824	824	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).
825	825
...	...	@@ -873,7 +873,7 @@
873	873	|N|fixed number of digits used in the preceding textual representation of the month or the day
874	874	| |
875	875
876		-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}}.
	1049	+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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
877	877
878	878	=== 12.4.5 Null Values ===
879	879
...	...	@@ -891,8 +891,10 @@
891	891
892	892	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).
893	893
894		-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.
	1067	+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
895	895
	1069	+TransformationScheme.
	1070	+
896	896	In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
897	897
898	898	{{putFootnotes/}}