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 ==
...	...	@@ -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
...	...	@@ -517,9 +517,9 @@
517	517
518	518	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
519	519
520		-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.
521	521
522		-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"]](%%)^^
523	523
524	524	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).
525	525
...	...	@@ -527,51 +527,52 @@
527	527
528	528	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
529	529
530		-(% style="width:1170.29px" %)
531		-|**VTL**|(% style="width:754px" %)**SDMX**
532		-|**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}}
533		-|**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**|(((
534	534	**Concept** with a definite
535	535
536	536	Representation
537	537	)))
538		-|**Value Domain**|(% style="width:754px" %)(((
	551	+|**Value Domain**|(((
539	539	**Representation** (see the Structure
540	540
541	541	Pattern in the Base Package)
542	542	)))
543		-|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
544		-|**Code**|(% style="width:754px" %)(((
	556	+|**Enumerated Value Domain / Code List**|**Codelist**
	557	+|**Code**|(((
545	545	**Code** (for enumerated
546	546
547	547	DimensionComponent, Measure, DataAttribute)
548	548	)))
549		-|**Described Value Domain**|(% style="width:754px" %)(((
550		-non-enumerated** Representation**
	562	+|**Described Value Domain**|(((
	563	+non-enumerated**    Representation**
551	551
552	552	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
553	553	)))
554		-|**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
555		-| |(% style="width:754px" %)(((
556		-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)
557	557	)))
558		-|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
559		-|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
560		-|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
561		-|**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
562	562
563	563	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).
564	564
565		-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.
566	566
567	567	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
568	568
569		-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.
570	570
571		-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.
572		-
573	573	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
574	574
	588	+[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape5" height="1" width="192"]]
	589	+
575	575	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
576	576
577	577	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.
...	...	@@ -586,8 +586,7 @@
586	586
587	587	[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
588	588
589		-(% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
590		-**Figure 22 – VTL Data Types**
	604	+==== Figure 22 – VTL Data Types ====
591	591
592	592	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.
593	593
...	...	@@ -594,12 +594,131 @@
594	594	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):
595	595
596	596
597		-**Figure 23 – VTL Basic Scalar Types**
598	598
599	599	(((
600		-
	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"]]
601	601	)))
602	602
	734	+==== Figure 23 – VTL Basic Scalar Types ====
	735	+
603	603	=== 12.4.2 VTL basic scalar types and SDMX data types ===
604	604
605	605	The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
...	...	@@ -622,159 +622,204 @@
622	622
623	623	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
624	624
625		-(% style="width:823.294px" %)
626		-|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type**
627		-|(% style="width:509px" %)(((
	758	+|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
	759	+|(((
628	628	String
	761	+
629	629	(string allowing any character)
630		-)))|(% style="width:312px" %)string
631		-|(% style="width:509px" %)(((
	763	+)))|string
	764	+|(((
632	632	Alpha
	766	+
633	633	(string which only allows A-z)
634		-)))|(% style="width:312px" %)string
635		-|(% style="width:509px" %)(((
	768	+)))|string
	769	+|(((
636	636	AlphaNumeric
	771	+
637	637	(string which only allows A-z and 0-9)
638		-)))|(% style="width:312px" %)string
639		-|(% style="width:509px" %)(((
	773	+)))|string
	774	+|(((
640	640	Numeric
	776	+
641	641	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
642		-)))|(% style="width:312px" %)string
643		-|(% style="width:509px" %)(((
	778	+)))|string
	779	+|(((
644	644	BigInteger
	781	+
645	645	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
646		-)))|(% style="width:312px" %)integer
647		-|(% style="width:509px" %)(((
	783	+)))|integer
	784	+|(((
648	648	Integer
649		-(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
650		-)))|(% style="width:312px" %)integer
651		-|(% style="width:509px" %)(((
	786	+
	787	+(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
	788	+
	789	+(inclusive))
	790	+)))|integer
	791	+|(((
652	652	Long
653		-(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
654		-)))|(% style="width:312px" %)integer
655		-|(% style="width:509px" %)(((
	793	+
	794	+(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
	795	+
	796	++9223372036854775807 (inclusive))
	797	+)))|integer
	798	+|(((
656	656	Short
	800	+
657	657	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
658		-)))|(% style="width:312px" %)integer
659		-|(% 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
660		-|(% 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	+|(((
661	661	Float
	806	+
662	662	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
663		-)))|(% style="width:312px" %)number
664		-|(% style="width:509px" %)(((
	808	+)))|number
	809	+|(((
665	665	Double
	811	+
666	666	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
667		-)))|(% style="width:312px" %)number
668		-|(% style="width:509px" %)(((
	813	+)))|number
	814	+|(((
669	669	Boolean
670		-(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
671		-)))|(% style="width:312px" %)boolean
672	672
673		-(% style="width:822.294px" %)
674		-|(% 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" %)(((
675	675	URI
	824	+
676	676	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
677		-)))|(% colspan="1" style="width:311px" %)string
678		-|(% colspan="2" style="width:507px" %)(((
	826	+)))|(% colspan="2" %)string
	827	+| |(% colspan="2" %)(((
679	679	Count
	829	+
680	680	(an integer following a sequential pattern, increasing by 1 for each occurrence)
681		-)))|(% colspan="1" style="width:311px" %)integer
682		-|(% colspan="2" style="width:507px" %)(((
	831	+)))|(% colspan="2" %)integer
	832	+| |(% colspan="2" %)(((
683	683	InclusiveValueRange
	834	+
684	684	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
685		-)))|(% colspan="1" style="width:311px" %)number
686		-|(% colspan="2" style="width:507px" %)(((
	836	+)))|(% colspan="2" %)number
	837	+| |(% colspan="2" %)(((
687	687	ExclusiveValueRange
	839	+
688	688	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
689		-)))|(% colspan="1" style="width:311px" %)number
690		-|(% colspan="2" style="width:507px" %)(((
	841	+)))|(% colspan="2" %)number
	842	+| |(% colspan="2" %)(((
691	691	Incremental
	844	+
692	692	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
693		-)))|(% colspan="1" style="width:311px" %)number
694		-|(% colspan="2" style="width:507px" %)(((
	846	+)))|(% colspan="2" %)number
	847	+| |(% colspan="2" %)(((
695	695	ObservationalTimePeriod
	849	+
696	696	(superset of StandardTimePeriod and TimeRange)
697		-)))|(% colspan="1" style="width:311px" %)time
698		-|(% colspan="2" style="width:507px" %)(((
	851	+)))|(% colspan="2" %)time
	852	+| |(% colspan="2" %)(((
699	699	StandardTimePeriod
700		-(superset of BasicTimePeriod and ReportingTimePeriod)
701		-)))|(% colspan="1" style="width:311px" %)time
702		-|(% colspan="2" style="width:507px" %)(((
	854	+
	855	+(superset of BasicTimePeriod and
	856	+
	857	+ReportingTimePeriod)
	858	+)))|(% colspan="2" %)time
	859	+| |(% colspan="2" %)(((
703	703	BasicTimePeriod
	861	+
704	704	(superset of GregorianTimePeriod and DateTime)
705		-)))|(% colspan="1" style="width:311px" %)date
706		-|(% colspan="2" style="width:507px" %)(((
	863	+)))|(% colspan="2" %)date
	864	+| |(% colspan="2" %)(((
707	707	GregorianTimePeriod
	866	+
708	708	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
709		-)))|(% colspan="1" style="width:311px" %)date
710		-|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date
711		-|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date
712		-|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date
713		-|(% 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" %)(((
714	714	ReportingTimePeriod
715		-(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
716		-)))|(% colspan="1" style="width:311px" %)time_period
717		-|(% 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" %)(((
718	718	ReportingYear
	883	+
719	719	(YYYY-A1 – 1 year period)
720		-)))|(% colspan="1" style="width:311px" %)time_period
721		-|(% colspan="2" style="width:507px" %)(((
	885	+)))|(% colspan="2" %)time_period
	886	+| |(% colspan="2" %)(((
722	722	ReportingSemester
	888	+
723	723	(YYYY-Ss – 6 month period)
724		-)))|(% colspan="1" style="width:311px" %)time_period
725		-|(% colspan="2" style="width:507px" %)(((
	890	+)))|(% colspan="2" %)time_period
	891	+| |(% colspan="2" %)(((
726	726	ReportingTrimester
	893	+
727	727	(YYYY-Tt – 4 month period)
728		-)))|(% colspan="1" style="width:311px" %)time_period
729		-|(% colspan="2" style="width:507px" %)(((
	895	+)))|(% colspan="2" %)time_period
	896	+| |(% colspan="2" %)(((
730	730	ReportingQuarter
	898	+
731	731	(YYYY-Qq – 3 month period)
732		-)))|(% colspan="1" style="width:311px" %)time_period
733		-|(% colspan="2" style="width:507px" %)(((
	900	+)))|(% colspan="2" %)time_period
	901	+| |(% colspan="2" %)(((
734	734	ReportingMonth
	903	+
735	735	(YYYY-Mmm – 1 month period)
736		-)))|(% colspan="1" style="width:311px" %)time_period
737		-|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period
738		-|(% 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" %)
739		-|(% 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" %)(((
740	740	ReportingDay
	912	+
741	741	(YYYY-Dddd – 1 day period)
742		-)))|(% colspan="2" style="width:312px" %)time_period
743		-|(% colspan="1" style="width:507px" %)(((
	914	+)))|(% colspan="2" %)time_period|
	915	+|(% colspan="2" %)(((
744	744	DateTime
	917	+
745	745	(YYYY-MM-DDThh:mm:ss)
746		-)))|(% colspan="2" style="width:312px" %)date
747		-|(% colspan="1" style="width:507px" %)(((
	919	+)))|(% colspan="2" %)date|
	920	+|(% colspan="2" %)(((
748	748	TimeRange
	922	+
749	749	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
750		-)))|(% colspan="2" style="width:312px" %)time
751		-|(% colspan="1" style="width:507px" %)(((
	924	+)))|(% colspan="2" %)time|
	925	+|(% colspan="2" %)(((
752	752	Month
	927	+
753	753	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
754		-)))|(% colspan="2" style="width:312px" %)string
755		-|(% colspan="1" style="width:507px" %)(((
	929	+)))|(% colspan="2" %)string|
	930	+|(% colspan="2" %)(((
756	756	MonthDay
	932	+
757	757	(~-~-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)
758		-)))|(% colspan="2" style="width:312px" %)string
759		-|(% colspan="1" style="width:507px" %)(((
	934	+)))|(% colspan="2" %)string|
	935	+|(% colspan="2" %)(((
760	760	Day
	937	+
761	761	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
762		-)))|(% colspan="2" style="width:312px" %)string
763		-|(% colspan="1" style="width:507px" %)(((
	939	+)))|(% colspan="2" %)string|
	940	+|(% colspan="2" %)(((
764	764	Time
	942	+
765	765	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
766		-)))|(% colspan="2" style="width:312px" %)string
767		-|(% colspan="1" style="width:507px" %)(((
	944	+)))|(% colspan="2" %)string|
	945	+|(% colspan="2" %)(((
768	768	Duration
	947	+
769	769	(corresponds to XML Schema xs:duration datatype)
770		-)))|(% colspan="2" style="width:312px" %)duration
771		-|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable
772		-|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable
773		-|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
774		-|(% 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|
775	775
776		-(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %)
777		-**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 ====
778	778
779	779	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).
780	780
...	...	@@ -782,32 +782,39 @@
782	782
783	783	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
784	784
785		-(% style="width:1073.29px" %)
786		-|(% style="width:207px" %)(((
787		-**VTL basic scalar type**
788		-)))|(% style="width:462px" %)(((
789		-**Default SDMX data type (BasicComponentDataType)**
790		-)))|(% style="width:402px" %)**Default output format**
791		-|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string)
792		-|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float)
793		-|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int)
794		-|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z
795		-|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above)
796		-|(% 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|(((
797	797	ReportingTimePeriod
	981	+
798	798	(StandardReportingPeriod)
799		-)))|(% style="width:402px" %)(((
	983	+)))|(((
800	800	YYYY-Pppp
	985	+
801	801	(according to SDMX )
802	802	)))
803		-|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)(((
	988	+|Duration|Duration|(((
804	804	Like XML (xs:duration)
	990	+
805	805	PnYnMnDTnHnMnS
806	806	)))
807		-|(% 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"
808	808
809		-(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes-1" %)
810		-**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 ====
811	811
812	812	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).
813	813
...	...	@@ -861,7 +861,7 @@
861	861	|N|fixed number of digits used in the preceding textual representation of the month or the day
862	862	| |
863	863
864		-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"]](%%)^^.
865	865
866	866	=== 12.4.5 Null Values ===
867	867
...	...	@@ -879,8 +879,10 @@
879	879
880	880	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).
881	881
882		-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
883	883
	1069	+TransformationScheme.
	1070	+
884	884	In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
885	885
886	886	{{putFootnotes/}}