Changes for page 12 Validation and Transformation Language (VTL)

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...	...	@@ -80,9 +80,9 @@
80	80
81	81	For example, by using the URN, the VTL Transformation that sums two SDMX Dataflows DF1 and DF2 and assigns the result to a third persistent Dataflow DFR, assuming that DF1, DF2 and DFR are the maintainedobject-id of the three Dataflows, that their version is 1.0.0 and their Agency is AG, would be written as{{footnote}}Since these references to SDMX objects include non-permitted characters as per the VTL ID notation, they need to be included between single quotes, according to the VTL rules for irregular names.{{/footnote}}:
82	82
83		->(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
84		->(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
85		->(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
	83	+> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
	84	+> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
	85	+> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
86	86
87	87	=== 12.2.3 Abbreviation of the URN ===
88	88
...	...	@@ -97,7 +97,8 @@
97	97	** "codelist" for the class Codelist.
98	98	* The class-name can be omitted as it can be deduced from the VTL invocation. In particular, starting from the VTL class of the invoked artefact (e.g. dataset, component, identifier, measure, attribute, variable, valuedomain), which is known given the syntax of the invoking VTL operator{{footnote}}For the syntax of the VTL operators see the VTL Reference Manual{{/footnote}}, the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section "Mapping between VTL and SDMX" hereinafter){{footnote}}In case the invoked artefact is a VTL component, which can be invoked only within the invocation of a VTL data set (SDMX Dataflow), the specific SDMX class-name (e.g. Dimension, TimeDimension, Measure or DataAttribute) can be deduced from the data structure of the SDMX Dataflow, which the component belongs to.{{/footnote}}.
99	99	* If the agency-id is not specified, it is assumed by default equal to the agency-id of the TransformationScheme, UserDefinedOperatorScheme or RulesetScheme from which the artefact is invoked. For example, the agencyid can be omitted if it is the same as the invoking TransformationScheme and cannot be omitted if the artefact comes from another agency{{footnote}}If the Agency is composite (for example AgencyA.Dept1.Unit2), the agency is considered different even if only part of the composite name is different (for example AgencyA.Dept1.Unit3 is a different Agency than the previous one). Moreover the agency-id cannot be omitted in part (i.e., if a TransformationScheme owned by AgencyA.Dept1.Unit2 references an artefact coming from AgencyA.Dept1.Unit3, the specification of the agency-id becomes mandatory and must be complete, without omitting the possibly equal parts like AgencyA.Dept1){{/footnote}}. Take also into account that, according to the VTL consistency rules, the agency of the result of a Transformation must be the same as its TransformationScheme, therefore the agency-id can be omitted for all the results (left part of Transformation statements).
100		-* As for the maintainedobject-id, this is essential in some cases while in other cases it can be omitted: o if the referenced artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the dataflow-id and obviously cannot be omitted;
	100	+* As for the maintainedobject-id, this is essential in some cases while in other cases it can be omitted:
	101	+** if the referenced artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the dataflow-id and obviously cannot be omitted;
101	101	** if the referenced artefact is a Dimension, TimeDimension, Measure, DataAttribute, which are not maintainable and belong to the DataStructure maintainable class, the maintainedobject-id is the dataStructure-id and can be omitted, given that these components are always invoked within the invocation of a Dataflow, whose dataStructure-id can be deduced from the SDMX structural definitions;
102	102	** if the referenced artefact is a Concept, which is not maintainable and belong to the ConceptScheme maintainable class, the maintained object is the conceptScheme-id and cannot be omitted;
103	103	** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted.
...	...	@@ -109,51 +109,47 @@
109	109
110	110	For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
111	111
112		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
	113	+> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
	114	+> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
	115	+> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
113	113
114		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
115		-
116		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
117		-
118	118	by omitting all the non-essential parts would become simply:
119	119
120		-DFR := DF1 + DF2
	119	+> DFR  : =  DF1 + DF2
121	121
122	122	The references to the Codelists can be simplified similarly. For example, given the non-abbreviated reference to the Codelist AG:CL_FREQ(1.0.0), which is{{footnote}}Single quotes are needed because this reference is not a VTL regular name. 19 Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}:
123	123
124		-'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
	123	+> 'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
125	125
126	126	if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply^^19^^:
127	127
128		-CL_FREQ
	127	+> CL_FREQ
129	129
130	130	As for the references to the components, it can be enough to specify the componentId, given that the dataStructure-Id can be omitted. An example of non-abbreviated reference, if the data structure is DST1 and the component is SECTOR, is the following:
131	131
132		-'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).S
	131	+> 'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).S ECTOR'
133	133
134		-ECTOR'
135		-
136	136	The corresponding fully abbreviated reference, if made from a TransformationScheme belonging to AG, would become simply:
137	137
138		-SECTOR
	135	+> SECTOR
139	139
140	140	For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as{{footnote}}The result DFR(1.0.0) is be equal to DF1(1.0.0) save that the component SECTOR is called SEC{{/footnote}}:
141	141
142		-'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
	139	+> 'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
143	143
144	144	In the references to the Concepts, which can exist for example in the definition of the VTL Rulesets, at least the conceptScheme-id and the concept-id must be specified.
145	145
146	146	An example of non-abbreviated reference, if the conceptScheme-id is CS1 and the concept-id is SECTOR, is the following:
147	147
148		-'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR'
	145	+> 'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR'
149	149
150	150	The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
151	151
152		-CS1(1.0.0).SECTOR
	149	+> CS1(1.0.0).SECTOR
153	153
154	154	The Codes and in general all the Values can be written without any other specification, for example, the transformation to check if the values of the measures of the Dataflow DF1 are between 0 and 25000 can be written like follows:
155	155
156		-'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
	153	+> 'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
157	157
158	158	The artefact (Component, Concept, Codelist …) which the Values are referred to can be deduced from the context in which the reference is made, taking also into account the VTL syntax. In the Transformation above, for example, the values 0 and 2500 are compared to the values of the measures of DF1(1.0.0).
159	159
...	...	@@ -201,7 +201,7 @@
201	201
202	202	The possible mapping options are described in more detail in the following sections.
203	203
204		-=== 12.3.2 Mapping from SDMX to VTL data structures ===
	201	+=== 12.3.3 Mapping from SDMX to VTL data structures ===
205	205
206	206	==== 12.3.3.1 Basic Mapping ====
207	207
...	...	@@ -209,11 +209,12 @@
209	209
210	210	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:
211	211
212		-|**SDMX**|**VTL**
213		-|Dimension|(Simple) Identifier
214		-|TimeDimension|(Time) Identifier
215		-|Measure|Measure
216		-|DataAttribute|Attribute
	209	+(% style="width:468.294px" %)
	210	+|(% style="width:196px" %)**SDMX**|(% style="width:269px" %)**VTL**
	211	+|(% style="width:196px" %)Dimension|(% style="width:269px" %)(Simple) Identifier
	212	+|(% style="width:196px" %)TimeDimension|(% style="width:269px" %)(Time) Identifier
	213	+|(% style="width:196px" %)Measure|(% style="width:269px" %)Measure
	214	+|(% style="width:196px" %)DataAttribute|(% style="width:269px" %)Attribute
217	217
218	218	The SDMX DataAttributes, in VTL they are all considered "at data point / observation level" (i.e. dependent on all the VTL Identifiers), because VTL does not have the SDMX AttributeRelationships, which defines the construct to which the DataAttribute is related (e.g. observation, dimension or set or group of dimensions, whole data set).
219	219
...	...	@@ -223,10 +223,8 @@
223	223
224	224	An alternative mapping method from SDMX to VTL is the **Pivot **mapping, which makes sense and is different from the Basic method only for the SDMX data structures that contain a Dimension that plays the role of measure dimension (like in SDMX 2.1) and just one Measure. Through this method, these structures can be mapped to multimeasure VTL data structures. Besides that, a user may choose to use any Dimension acting as a list of Measures (e.g., a Dimension with indicators), either by considering the “Measure” role of a Dimension, or at will using any coded Dimension. Of course, in SDMX 3.0, this can only work when only one Measure is defined in the DSD.
225	225
226		-In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the
	224	+In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.
227	227
228		-MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.
229		-
230	230	Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
231	231
232	232	If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
...	...	@@ -239,16 +239,18 @@
239	239	* The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
240	240	* An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
241	241	** 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		-** 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). o 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	+** 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).
	239	+** 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.
243	243
244	244	The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
245	245
246		-|**SDMX**|**VTL**
247		-|Dimension|(Simple) Identifier
248		-|TimeDimension|(Time) Identifier
249		-|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension
250		-|DataAttribute not depending on the MeasureDimension|Attribute
251		-|DataAttribute depending on the MeasureDimension|(((
	243	+(% style="width:739.294px" %)
	244	+|(% style="width:335px" %)**SDMX**|(% style="width:400px" %)**VTL**
	245	+|(% style="width:335px" %)Dimension|(% style="width:400px" %)(Simple) Identifier
	246	+|(% style="width:335px" %)TimeDimension|(% style="width:400px" %)(Time) Identifier
	247	+|(% style="width:335px" %)MeasureDimension & one Measure|(% style="width:400px" %)One Measure for each Code of the SDMX MeasureDimension
	248	+|(% style="width:335px" %)DataAttribute not depending on the MeasureDimension|(% style="width:400px" %)Attribute
	249	+|(% style="width:335px" %)DataAttribute depending on the MeasureDimension|(% style="width:400px" %)(((
252	252	One Attribute for each Code of the
253	253	SDMX MeasureDimension
254	254	)))
...	...	@@ -258,19 +258,14 @@
258	258	At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
259	259
260	260	* 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;
261		-* 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)
262		-
263		-Identifiers, (time) Identifier and Attributes.
264		-
	259	+* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
265	265	* 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
266	266	* 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
267	267
268	268	==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
269	269
270		-* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain
	265	+* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain Attributes.
271	271
272		-Attributes.
273		-
274	274	The Basic_A2M and Pivot_A2M behaves respectively like the Basic and Pivot methods, except that the final VTL components, which according to the Basic and Pivot methods would have had the role of Attribute, assume instead the role of Measure.
275	275
276	276	Proper VTL features allow changing the role of specific attributes even after the SDMX to VTL mapping: they can be useful when only some of the DataAttributes need to be managed as VTL Measures.
...	...	@@ -287,11 +287,12 @@
287	287
288	288	Mapping table:
289	289
290		-|**VTL**|**SDMX**
291		-|(Simple) Identifier|Dimension
292		-|(Time) Identifier|TimeDimension
293		-|Measure|Measure
294		-|Attribute|DataAttribute
	283	+(% style="width:470.294px" %)
	284	+|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX**
	285	+|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension
	286	+|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension
	287	+|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure
	288	+|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute
295	295
296	296	If the distinction between simple identifier and time identifier is not maintained in the VTL environment, the classification between Dimension and TimeDimension exists only in SDMX, as declared in the relevant DataStructureDefinition.
297	297
...	...	@@ -319,11 +319,12 @@
319	319
320	320	The summary mapping table of the **unpivot** mapping method is the following:
321	321
322		-|**VTL**|**SDMX**
323		-|(Simple) Identifier|Dimension
324		-|(Time) Identifier|TimeDimension
325		-|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
326		-|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
	316	+(% style="width:638.294px" %)
	317	+|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX**
	318	+|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension
	319	+|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension
	320	+|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
	321	+|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
327	327
328	328	At observation / data point level:
329	329
...	...	@@ -345,12 +345,13 @@
345	345
346	346	The mapping table is the following:
347	347
348		-|VTL|SDMX
349		-|(Simple) Identifier|Dimension
350		-|(Time) Identifier|TimeDimension
351		-|Some Measures|Measure
352		-|Other Measures|DataAttribute
353		-|Attribute|DataAttribute
	343	+(% style="width:467.294px" %)
	344	+|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
	345	+|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
	346	+|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
	347	+|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
	348	+|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
	349	+|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
354	354
355	355	Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the attributeRelationship for the DataAttributes, which does not exist in VTL.
356	356
...	...	@@ -388,11 +388,11 @@
388	388
389	389	Therefore, the generic name of this kind of VTL datasets would be:
390	390
391		-'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
	387	+> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
392	392
393	393	Where DF(1.0.0) is the Dataflow and //INDICATORvalue// and //COUNTRYvalue //are placeholders for one value of the INDICATOR and COUNTRY dimensions. Instead the specific name of one of these VTL datasets would be:
394	394
395		-‘DF(1.0.0)/POPULATION.USA’
	391	+> ‘DF(1.0.0)/POPULATION.USA’
396	396
397	397	In particular, this is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA.
398	398
...	...	@@ -406,26 +406,22 @@
406	406
407	407	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.
408	408
409		-In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
	405	+In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
410	410
411		-basic, pivot …).
412		-
413	413	In the example above, for all the datasets of the kind
414	414
415		-‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
	409	+> ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
416	416
417	417	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:
418	418
419		-‘DF1(1.0.0)/POPULATION.USA’ :=
	413	+> ‘DF1(1.0.0)/POPULATION.USA’ :=
	414	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
	415	+>
	416	+> ‘DF1(1.0.0)/POPULATION.CANADA’ :=
	417	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
	418	+>
	419	+> … … …
420	420
421		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
422		-
423		-‘DF1(1.0.0)/POPULATION.CANADA’ :=
424		-
425		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
426		-
427		-… … …
428		-
429	429	In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}}
430	430
431	431	In the direction from SDMX to VTL it is allowed to omit the value of one or more DimensionComponents on which the mapping is based, but maintaining all the separating dots (therefore it may happen to find two or more consecutive dots and dots in the beginning or in the end). The absence of value means that for the corresponding Dimension all the values are kept and the Dimension is not dropped.
...	...	@@ -434,10 +434,9 @@
434	434
435	435	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
436	436
437		-‘DF1(1.0.0)/POPULATION.’ :=
	429	+> ‘DF1(1.0.0)/POPULATION.’ :=
	430	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
438	438
439		-DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
440		-
441	441	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
442	442
443	443	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
...	...	@@ -455,41 +455,38 @@
455	455
456	456	The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:{{footnote}}the symbol of the VTL persistent assignment is used (<-){{/footnote}}
457	457
458		-‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
	449	+> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
459	459
460	460	Some examples follow, for some specific values of INDICATOR and COUNTRY:
461	461
462		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
463		-… … …
	453	+> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
	454	+> … … …
	455	+> ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
	456	+> ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
	457	+> … … …
464	464
465		-‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
466		-‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
467		-… … …
468		-
469	469	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:
470	470
471	471	VTL dataset   INDICATOR value COUNTRY value
472	472
473		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
474		-‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
475		-‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
476		-‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
	463	+> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
	464	+> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
	465	+> ‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
	466	+> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
	467	+> … … …
477	477
478		-… … …
479		-
480	480	It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be:
481	481
482		-DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
483		-DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
484		-DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
485		-[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
486		-DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
487		-DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
488		-DF2bis_GDPPERCAPITA_CANADA’,
489		-… ,
490		-DF2bis_POPGROWTH_USA’,
491		-DF2bis_POPGROWTH_CANADA’
492		-…);
	471	+> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
	472	+> DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
	473	+> DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’  [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
	474	+> DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
	475	+> DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
	476	+> DF2bis_GDPPERCAPITA_CANADA’,
	477	+> … ,
	478	+> DF2bis_POPGROWTH_USA’,
	479	+> DF2bis_POPGROWTH_CANADA’
	480	+> …);
493	493
494	494	In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
495	495
...	...	@@ -501,25 +501,26 @@
501	501
502	502	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
503	503
504		-|VTL|SDMX
505		-|**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^^
506		-|**Represented Variable**|**Concept** with a definite Representation
507		-|**Value Domain**|(((
	492	+(% style="width:706.294px" %)
	493	+|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX
	494	+|(% style="width:257px" %)**Data Set Component**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
	495	+|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation
	496	+|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)(((
508	508	**Representation** (see the Structure
509	509	Pattern in the Base Package)
510	510	)))
511		-|**Enumerated Value Domain / Code List**|**Codelist**
512		-|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
513		-|**Described Value Domain**|(((
	500	+|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
	501	+|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
	502	+|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
514	514	non-enumerated** Representation**
515	515	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
516	516	)))
517		-|**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
518		-| |to a valid **value **(for non-enumerated** **Representations)
519		-|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
520		-|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
521		-|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
522		-|**Set list**|This abstraction does not exist in SDMX
	506	+|(% style="width:257px" %)**Value**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
	507	+|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)
	508	+|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
	509	+|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
	510	+|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
	511	+|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX
523	523
524	524	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).
525	525
...	...	@@ -527,8 +527,10 @@
527	527
528	528	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
529	529
530		-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.
	519	+> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
531	531
	521	+if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
	522	+
532	532	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
533	533
534	534	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -543,8 +543,9 @@
543	543
544	544	The VTL data types are sub-divided in scalar types (like integers, strings, etc.), which are the types of the scalar values, and compound types (like Data Sets, Components, Rulesets, etc.), which are the types of the compound structures. See below the diagram of the VTL data types, taken from the VTL User Manual:
545	545
546		-[[image:1750067055028-964.png]]
547	547
	538	+[[image:1750070288958-132.png]]
	539	+
548	548	**Figure 22 – VTL Data Types**
549	549
550	550	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.
...	...	@@ -551,6 +551,8 @@
551	551
552	552	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):
553	553
	546	+[[image:1750070310572-584.png]]
	547	+
554	554	**Figure 23 – VTL Basic Scalar Types**
555	555
556	556	=== 12.4.2 VTL basic scalar types and SDMX data types ===
...	...	@@ -575,158 +575,157 @@
575	575
576	576	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
577	577
578		-|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
579		-|(((
	572	+(% style="width:583.294px" %)
	573	+|(% style="width:360px" %)SDMX data type (BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type
	574	+|(% style="width:360px" %)(((
580	580	String
581	581	(string allowing any character)
582		-)))|string
583		-|(((
584		-Alpha
585		-
	577	+)))|(% style="width:221px" %)string
	578	+|(% style="width:360px" %)(((
	579	+Alpha
586	586	(string which only allows A-z)
587		-)))|string
588		-|(((
	581	+)))|(% style="width:221px" %)string
	582	+|(% style="width:360px" %)(((
589	589	AlphaNumeric
590	590	(string which only allows A-z and 0-9)
591		-)))|string
592		-|(((
	585	+)))|(% style="width:221px" %)string
	586	+|(% style="width:360px" %)(((
593	593	Numeric
594		-
595	595	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
596		-)))|string
597		-|(((
	589	+)))|(% style="width:221px" %)string
	590	+|(% style="width:360px" %)(((
598	598	BigInteger
599	599	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
600		-)))|integer
601		-|(((
	593	+)))|(% style="width:221px" %)integer
	594	+|(% style="width:360px" %)(((
602	602	Integer
603	603	(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
604	604	(inclusive))
605		-)))|integer
606		-|(((
	598	+)))|(% style="width:221px" %)integer
	599	+|(% style="width:360px" %)(((
607	607	Long
608	608	(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
609	609	+9223372036854775807 (inclusive))
610		-)))|integer
611		-|(((
	603	+)))|(% style="width:221px" %)integer
	604	+|(% style="width:360px" %)(((
612	612	Short
613	613	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
614		-)))|integer
615		-|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
616		-|(((
	607	+)))|(% style="width:221px" %)integer
	608	+|(% style="width:360px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:221px" %)number
	609	+|(% style="width:360px" %)(((
617	617	Float
618	618	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
619		-)))|number
620		-|(((
	612	+)))|(% style="width:221px" %)number
	613	+|(% style="width:360px" %)(((
621	621	Double
622	622	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
623		-)))|number
624		-|(((
	616	+)))|(% style="width:221px" %)number
	617	+|(% style="width:360px" %)(((
625	625	Boolean
626	626	(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
627	627	binary-valued logic: {true, false})
628		-)))|boolean
629		-|(((
	621	+)))|(% style="width:221px" %)boolean
	622	+|(% style="width:360px" %)(((
630	630	URI
631	631	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
632		-)))|string
633		-|(((
	625	+)))|(% style="width:221px" %)string
	626	+|(% style="width:360px" %)(((
634	634	Count
635	635	(an integer following a sequential pattern, increasing by 1 for each occurrence)
636		-)))|integer
637		-|(((
	629	+)))|(% style="width:221px" %)integer
	630	+|(% style="width:360px" %)(((
638	638	InclusiveValueRange
639	639	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
640		-)))|number
641		-|(((
	633	+)))|(% style="width:221px" %)number
	634	+|(% style="width:360px" %)(((
642	642	ExclusiveValueRange
643	643	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
644		-)))|number
645		-|(((
	637	+)))|(% style="width:221px" %)number
	638	+|(% style="width:360px" %)(((
646	646	Incremental
647	647	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
648		-)))|number
649		-|(((
	641	+)))|(% style="width:221px" %)number
	642	+|(% style="width:360px" %)(((
650	650	ObservationalTimePeriod
651	651	(superset of StandardTimePeriod and TimeRange)
652		-)))|time
653		-|(((
	645	+)))|(% style="width:221px" %)time
	646	+|(% style="width:360px" %)(((
654	654	StandardTimePeriod
655	655	(superset of BasicTimePeriod and ReportingTimePeriod)
656		-)))|time
657		-|(((
	649	+)))|(% style="width:221px" %)time
	650	+|(% style="width:360px" %)(((
658	658	BasicTimePeriod
659	659	(superset of GregorianTimePeriod and DateTime)
660		-)))|date
661		-|(((
	653	+)))|(% style="width:221px" %)date
	654	+|(% style="width:360px" %)(((
662	662	GregorianTimePeriod
663	663	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
664		-)))|date
665		-|GregorianYear (YYYY)|date
666		-|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
667		-|GregorianDay (YYYY-MM-DD)|date
668		-|(((
	657	+)))|(% style="width:221px" %)date
	658	+|(% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date
	659	+|(% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date
	660	+|(% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date
	661	+|(% style="width:360px" %)(((
669	669	ReportingTimePeriod
670	670	(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
671		-)))|time_period
672		-|(((
	664	+)))|(% style="width:221px" %)time_period
	665	+|(% style="width:360px" %)(((
673	673	ReportingYear
674	674	(YYYY-A1 – 1 year period)
675		-)))|time_period
676		-|(((
	668	+)))|(% style="width:221px" %)time_period
	669	+|(% style="width:360px" %)(((
677	677	ReportingSemester
678	678	(YYYY-Ss – 6 month period)
679		-)))|time_period
680		-|(((
	672	+)))|(% style="width:221px" %)time_period
	673	+|(% style="width:360px" %)(((
681	681	ReportingTrimester
682	682	(YYYY-Tt – 4 month period)
683		-)))|time_period
684		-|(((
	676	+)))|(% style="width:221px" %)time_period
	677	+|(% style="width:360px" %)(((
685	685	ReportingQuarter
686	686	(YYYY-Qq – 3 month period)
687		-)))|time_period
688		-|(((
	680	+)))|(% style="width:221px" %)time_period
	681	+|(% style="width:360px" %)(((
689	689	ReportingMonth
690	690	(YYYY-Mmm – 1 month period)
691		-)))|time_period
692		-|ReportingWeek|time_period
693		-| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
694		-|(((
	684	+)))|(% style="width:221px" %)time_period
	685	+|(% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period
	686	+|(% style="width:360px" %) (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% style="width:221px" %)
	687	+|(% style="width:360px" %)(((
695	695	ReportingDay
696	696	(YYYY-Dddd – 1 day period)
697		-)))|time_period
698		-|(((
	690	+)))|(% style="width:221px" %)time_period
	691	+|(% style="width:360px" %)(((
699	699	DateTime
700	700	(YYYY-MM-DDThh:mm:ss)
701		-)))|date
702		-|(((
	694	+)))|(% style="width:221px" %)date
	695	+|(% style="width:360px" %)(((
703	703	TimeRange
704	704	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
705		-)))|time
706		-|(((
	698	+)))|(% style="width:221px" %)time
	699	+|(% style="width:360px" %)(((
707	707	Month
708	708	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
709		-)))|string
710		-|(((
	702	+)))|(% style="width:221px" %)string
	703	+|(% style="width:360px" %)(((
711	711	MonthDay
712	712	(~-~-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)
713		-)))|string
714		-|(((
	706	+)))|(% style="width:221px" %)string
	707	+|(% style="width:360px" %)(((
715	715	Day
716	716	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
717		-)))|string
718		-|(((
	710	+)))|(% style="width:221px" %)string
	711	+|(% style="width:360px" %)(((
719	719	Time
720	720	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
721		-)))|string
722		-|(((
	714	+)))|(% style="width:221px" %)string
	715	+|(% style="width:360px" %)(((
723	723	Duration
724	724	(corresponds to XML Schema xs:duration datatype)
725		-)))|duration
726		-|XHTML|Metadata type – not applicable
727		-|KeyValues|Metadata type – not applicable
728		-|IdentifiableReference|Metadata type – not applicable
729		-|DataSetReference|Metadata type – not applicable
	718	+)))|(% style="width:221px" %)duration
	719	+|(% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable
	720	+|(% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable
	721	+|(% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable
	722	+|(% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable
730	730
731	731	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
732	732
...	...	@@ -736,84 +736,82 @@
736	736
737	737	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
738	738
739		-|(((
740		-VTL basic
741		-scalar type
742		-)))|(((
	732	+(% style="width:748.294px" %)
	733	+|(% style="width:164px" %)(((
	734	+VTL basic scalar type
	735	+)))|(% style="width:304px" %)(((
743	743	Default SDMX data type
744		-(BasicComponentDataType
745		-)
746		-)))|Default output format
747		-|String|String|Like XML (xs:string)
748		-|Number|Float|Like XML (xs:float)
749		-|Integer|Integer|Like XML (xs:int)
750		-|Date|DateTime|YYYY-MM-DDT00:00:00Z
751		-|Time|StandardTimePeriod|<date>/<date> (as defined above)
752		-|time_period|(((
	737	+(BasicComponentDataType)
	738	+)))|(% style="width:277px" %)Default output format
	739	+|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string)
	740	+|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float)
	741	+|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int)
	742	+|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z
	743	+|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above)
	744	+|(% style="width:164px" %)time_period|(% style="width:304px" %)(((
753	753	ReportingTimePeriod
754	754	(StandardReportingPeriod)
755		-)))|(((
	747	+)))|(% style="width:277px" %)(((
756	756	YYYY-Pppp
757	757	(according to SDMX )
758	758	)))
759		-|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
760		-|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
	751	+|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS
	752	+|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"
761	761
762	762	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
763	763
764		-In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
	756	+In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
765	765
766		-Transformations and Expressions of the SDMX information model).
767		-
768	768	The custom output formats can be specified by means of the VTL formatting mask described in the section "Type Conversion and Formatting Mask" of the VTL Reference Manual. Such a section describes the masks for the VTL basic scalar types "number", "integer", "date", "time", "time_period" and "duration" and gives examples. As for the types "string" and "boolean" the VTL conventions are extended with some other special characters as described in the following table.
769	769
770		-|(% colspan="2" %)VTL special characters for the formatting masks
771		-|(% colspan="2" %)
772		-|(% colspan="2" %)Number
773		-|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
774		-|E|one numeric digit (for the exponent of the scientific notation)
775		-|. (dot)|possible separator between the integer and the decimal parts.
776		-|, (comma)|possible separator between the integer and the decimal parts.
777		-| |
778		-|(% colspan="2" %)Time and duration
779		-|C|century
780		-|Y|year
781		-|S|semester
782		-|Q|quarter
783		-|M|month
784		-|W|week
785		-|D|day
786		-|h|hour digit (by default on 24 hours)
787		-|M|minute
788		-|S|second
789		-|D|decimal of second
790		-|P|period indicator (representation in one digit for the duration)
791		-|P|number of the periods specified in the period indicator
792		-|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
793		-|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
794		-|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
795		-|Month|lowercase textual representation of the month (e.g., january)
796		-|Day|lowercase textual representation of the month (e.g., monday)
797		-|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
798		-|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
799		-| |
800		-|(% colspan="2" %)String
801		-|X|any string character
802		-|Z|any string character from "A" to "z"
803		-|9|any string character from "0" to "9"
804		-| |
805		-|(% colspan="2" %)Boolean
806		-|B|Boolean using "true" for True and "false" for False
807		-|1|Boolean using "1" for True and "0" for False
808		-|0|Boolean using "0" for True and "1" for False
809		-| |
810		-|(% colspan="2" %)Other qualifiers
811		-|*|an arbitrary number of digits (of the preceding type)
812		-|+|at least one digit (of the preceding type)
813		-|( )|optional digits (specified within the brackets)
814		-|\|prefix for the special characters that must appear in the mask
815		-|N|fixed number of digits used in the preceding textual representation of the month or the day
816		-| |
	760	+(% style="width:717.294px" %)
	761	+|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks
	762	+|(% colspan="2" style="width:714px" %)
	763	+|(% colspan="2" style="width:714px" %)Number
	764	+|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
	765	+|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation)
	766	+|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
	767	+|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
	768	+|(% style="width:122px" %) |(% style="width:591px" %)
	769	+|(% colspan="2" style="width:714px" %)Time and duration
	770	+|(% style="width:122px" %)C|(% style="width:591px" %)century
	771	+|(% style="width:122px" %)Y|(% style="width:591px" %)year
	772	+|(% style="width:122px" %)S|(% style="width:591px" %)semester
	773	+|(% style="width:122px" %)Q|(% style="width:591px" %)quarter
	774	+|(% style="width:122px" %)M|(% style="width:591px" %)month
	775	+|(% style="width:122px" %)W|(% style="width:591px" %)week
	776	+|(% style="width:122px" %)D|(% style="width:591px" %)day
	777	+|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours)
	778	+|(% style="width:122px" %)M|(% style="width:591px" %)minute
	779	+|(% style="width:122px" %)S|(% style="width:591px" %)second
	780	+|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second
	781	+|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration)
	782	+|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator
	783	+|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
	784	+|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January)
	785	+|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
	786	+|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january)
	787	+|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday)
	788	+|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
	789	+|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
	790	+|(% style="width:122px" %) |(% style="width:591px" %)
	791	+|(% colspan="2" style="width:714px" %)String
	792	+|(% style="width:122px" %)X|(% style="width:591px" %)any string character
	793	+|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z"
	794	+|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9"
	795	+|(% style="width:122px" %) |(% style="width:591px" %)
	796	+|(% colspan="2" style="width:714px" %)Boolean
	797	+|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False
	798	+|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False
	799	+|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False
	800	+|(% style="width:122px" %) |(% style="width:591px" %)
	801	+|(% colspan="2" style="width:714px" %)Other qualifiers
	802	+|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type)
	803	+|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type)
	804	+|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets)
	805	+|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask
	806	+|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day
	807	+|(% style="width:122px" %) |(% style="width:591px" %)
817	817
818	818	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}}.
819	819

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