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
...	...	@@ -110,51 +110,47 @@
110	110
111	111	For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
112	112
113		-'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)'
114	114
115		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
116		-
117		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
118		-
119	119	by omitting all the non-essential parts would become simply:
120	120
121		-DFR := DF1 + DF2
	119	+> DFR  : =  DF1 + DF2
122	122
123	123	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}}:
124	124
125		-'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)'
126	126
127	127	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^^:
128	128
129		-CL_FREQ
	127	+> CL_FREQ
130	130
131	131	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:
132	132
133		-'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'
134	134
135		-ECTOR'
136		-
137	137	The corresponding fully abbreviated reference, if made from a TransformationScheme belonging to AG, would become simply:
138	138
139		-SECTOR
	135	+> SECTOR
140	140
141	141	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}}:
142	142
143		-'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]
144	144
145	145	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.
146	146
147	147	An example of non-abbreviated reference, if the conceptScheme-id is CS1 and the concept-id is SECTOR, is the following:
148	148
149		-'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'
150	150
151	151	The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
152	152
153		-CS1(1.0.0).SECTOR
	149	+> CS1(1.0.0).SECTOR
154	154
155	155	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:
156	156
157		-'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
	153	+> 'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
158	158
159	159	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).
160	160
...	...	@@ -202,7 +202,7 @@
202	202
203	203	The possible mapping options are described in more detail in the following sections.
204	204
205		-=== 12.3.2 Mapping from SDMX to VTL data structures ===
	201	+=== 12.3.3 Mapping from SDMX to VTL data structures ===
206	206
207	207	==== 12.3.3.1 Basic Mapping ====
208	208
...	...	@@ -210,11 +210,12 @@
210	210
211	211	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:
212	212
213		-|**SDMX**|**VTL**
214		-|Dimension|(Simple) Identifier
215		-|TimeDimension|(Time) Identifier
216		-|Measure|Measure
217		-|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
218	218
219	219	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).
220	220
...	...	@@ -224,10 +224,8 @@
224	224
225	225	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.
226	226
227		-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}}.
228	228
229		-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}}.
230		-
231	231	Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
232	232
233	233	If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
...	...	@@ -240,16 +240,18 @@
240	240	* The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
241	241	* An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
242	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 AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension;
243		-** 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.
244	244
245	245	The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
246	246
247		-|**SDMX**|**VTL**
248		-|Dimension|(Simple) Identifier
249		-|TimeDimension|(Time) Identifier
250		-|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension
251		-|DataAttribute not depending on the MeasureDimension|Attribute
252		-|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" %)(((
253	253	One Attribute for each Code of the
254	254	SDMX MeasureDimension
255	255	)))
...	...	@@ -259,19 +259,14 @@
259	259	At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
260	260
261	261	* 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;
262		-* 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)
263		-
264		-Identifiers, (time) Identifier and Attributes.
265		-
	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.
266	266	* 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
267	267	* 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
268	268
269	269	==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
270	270
271		-* 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.
272	272
273		-Attributes.
274		-
275	275	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.
276	276
277	277	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.
...	...	@@ -288,11 +288,12 @@
288	288
289	289	Mapping table:
290	290
291		-|**VTL**|**SDMX**
292		-|(Simple) Identifier|Dimension
293		-|(Time) Identifier|TimeDimension
294		-|Measure|Measure
295		-|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
296	296
297	297	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.
298	298
...	...	@@ -320,11 +320,12 @@
320	320
321	321	The summary mapping table of the **unpivot** mapping method is the following:
322	322
323		-|**VTL**|**SDMX**
324		-|(Simple) Identifier|Dimension
325		-|(Time) Identifier|TimeDimension
326		-|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
327		-|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
328	328
329	329	At observation / data point level:
330	330
...	...	@@ -346,12 +346,13 @@
346	346
347	347	The mapping table is the following:
348	348
349		-|VTL|SDMX
350		-|(Simple) Identifier|Dimension
351		-|(Time) Identifier|TimeDimension
352		-|Some Measures|Measure
353		-|Other Measures|DataAttribute
354		-|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
355	355
356	356	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.
357	357
...	...	@@ -389,11 +389,11 @@
389	389
390	390	Therefore, the generic name of this kind of VTL datasets would be:
391	391
392		-'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
	387	+> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
393	393
394	394	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:
395	395
396		-‘DF(1.0.0)/POPULATION.USA’
	391	+> ‘DF(1.0.0)/POPULATION.USA’
397	397
398	398	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.
399	399
...	...	@@ -407,26 +407,22 @@
407	407
408	408	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.
409	409
410		-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 …).
411	411
412		-basic, pivot …).
413		-
414	414	In the example above, for all the datasets of the kind
415	415
416		-‘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.
417	417
418	418	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:
419	419
420		-‘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	+> … … …
421	421
422		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
423		-
424		-‘DF1(1.0.0)/POPULATION.CANADA’ :=
425		-
426		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
427		-
428		-… … …
429		-
430	430	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}}
431	431
432	432	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.
...	...	@@ -435,10 +435,9 @@
435	435
436	436	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
437	437
438		-‘DF1(1.0.0)/POPULATION.’ :=
	429	+> ‘DF1(1.0.0)/POPULATION.’ :=
	430	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
439	439
440		-DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
441		-
442	442	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
443	443
444	444	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
...	...	@@ -456,41 +456,38 @@
456	456
457	457	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}}
458	458
459		-‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
	449	+> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
460	460
461	461	Some examples follow, for some specific values of INDICATOR and COUNTRY:
462	462
463		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
464		-… … …
	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	+> … … …
465	465
466		-‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
467		-‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
468		-… … …
469		-
470	470	As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively:
471	471
472	472	VTL dataset   INDICATOR value COUNTRY value
473	473
474		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
475		-‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
476		-‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
477		-‘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	+> … … …
478	478
479		-… … …
480		-
481	481	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:
482	482
483		-DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
484		-DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
485		-DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
486		-[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
487		-DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
488		-DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
489		-DF2bis_GDPPERCAPITA_CANADA’,
490		-… ,
491		-DF2bis_POPGROWTH_USA’,
492		-DF2bis_POPGROWTH_CANADA’
493		-…);
	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	+> …);
494	494
495	495	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.
496	496
...	...	@@ -502,25 +502,26 @@
502	502
503	503	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
504	504
505		-|VTL|SDMX
506		-|**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^^
507		-|**Represented Variable**|**Concept** with a definite Representation
508		-|**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" %)(((
509	509	**Representation** (see the Structure
510	510	Pattern in the Base Package)
511	511	)))
512		-|**Enumerated Value Domain / Code List**|**Codelist**
513		-|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
514		-|**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" %)(((
515	515	non-enumerated** Representation**
516	516	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
517	517	)))
518		-|**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
519		-| |to a valid **value **(for non-enumerated** **Representations)
520		-|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
521		-|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
522		-|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
523		-|**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
524	524
525	525	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).
526	526
...	...	@@ -528,8 +528,10 @@
528	528
529	529	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
530	530
531		-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)
532	532
	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	+
533	533	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
534	534
535	535	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -544,8 +544,9 @@
544	544
545	545	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:
546	546
547		-[[image:1750067055028-964.png]]
548	548
	538	+[[image:1750070288958-132.png]]
	539	+
549	549	**Figure 22 – VTL Data Types**
550	550
551	551	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.

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