Changes for page 12 Validation and Transformation Language (VTL)

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...	...	@@ -19,6 +19,7 @@
19	19	This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts.
20	20
21	21	== 12.2 References to SDMX artefacts from VTL statements ==
	22	+
22	22	=== 12.2.1 Introduction ===
23	23
24	24	The VTL can manipulate SDMX artefacts (or objects) by referencing them through predefined conventional names (aliases).
...	...	@@ -48,10 +48,8 @@
48	48
49	49	The generic structure of the URN is the following:
50	50
51		-SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id
	52	+SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id (maintainedobject-version).*container-object-id.object-id
52	52
53		-(maintainedobject-version).*container-object-id.object-id
54		-
55	55	The **SDMXprefix** is "urn:sdmx:org", always the same for all SDMX artefacts.
56	56
57	57	The SDMX-IM-package-name** **is the concatenation of the string** **"sdmx.infomodel." with the package-name, which the artefact belongs to. For example, for referencing a Dataflow the SDMX-IM-package-name is "sdmx.infomodel.datastructure", because the class Dataflow belongs to the package "datastructure".
...	...	@@ -72,24 +72,19 @@
72	72
73	73	The maintainedobject-version is the version, according to the SDMX versioning rules, of the maintained object which the artefact belongs to (for example, possible versions might be 1.0, 2.3, 1.0.0, 2.1.0 or 3.1.2).
74	74
75		-The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN
	74	+The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN.
76	76
77	77	The object-id is the name of the non-maintainable artefact (when the artefact is maintainable its name is already specified as the maintainedobject-id, see above), in particular it has to be specified:
78	78
79		-* if the artefact is a Dimension, TimeDimension, Measure or
80		-
81		-DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components)
82		-
	78	+* if the artefact is a Dimension, TimeDimension, Measure or DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components)
83	83	* if the artefact is a Concept (the object-id is the name of the Concept)
84	84
85	85	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}}:
86	86
87		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(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)'
88	88
89		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
90		-
91		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
92		-
93	93	=== 12.2.3 Abbreviation of the URN ===
94	94
95	95	The complete formulation of the URN described above is exhaustive but verbose, even for very simple statements. In order to reduce the verbosity through a simplified identifier and make the work of transformation definers easier, proper abbreviations of the URN are possible. Using this approach, the referenced artefacts remain intelligible in the VTL code by a human reader.
...	...	@@ -98,10 +98,13 @@
98	98
99	99	* The SDMXprefix can be omitted for all the SDMX objects, because it is a prefixed string (urn:sdmx:org), always the same for SDMX objects.
100	100	* The SDMX-IM-package-name** **can be omitted as well because it can be deduced from the class-name that follows it (the table of the SDMX-IM packages and classes that allows this deduction is in the SDMX 2.1 Standards - Section 5 - Registry Specifications, paragraph 6.2.3). In particular, considering the object classes of the artefacts that VTL can reference, the package is:
101		-** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist.
	95	+** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute,
	96	+** "conceptscheme" for the class Concept,
	97	+** "codelist" for the class Codelist.
102	102	* 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}}.
103	103	* 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).
104		-* 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;
105	105	** 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;
106	106	** 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;
107	107	** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted.
...	...	@@ -113,51 +113,47 @@
113	113
114	114	For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
115	115
116		-'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)'
117	117
118		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
119		-
120		-'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
121		-
122	122	by omitting all the non-essential parts would become simply:
123	123
124		-DFR := DF1 + DF2
	119	+> DFR  : =  DF1 + DF2
125	125
126	126	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}}:
127	127
128		-'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)'
129	129
130	130	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^^:
131	131
132		-CL_FREQ
	127	+> CL_FREQ
133	133
134	134	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:
135	135
136		-'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'
137	137
138		-ECTOR'
139		-
140	140	The corresponding fully abbreviated reference, if made from a TransformationScheme belonging to AG, would become simply:
141	141
142		-SECTOR
	135	+> SECTOR
143	143
144	144	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}}:
145	145
146		-'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]
147	147
148	148	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.
149	149
150	150	An example of non-abbreviated reference, if the conceptScheme-id is CS1 and the concept-id is SECTOR, is the following:
151	151
152		-'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'
153	153
154	154	The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
155	155
156		-CS1(1.0.0).SECTOR
	149	+> CS1(1.0.0).SECTOR
157	157
158	158	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:
159	159
160		-'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
	153	+> 'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
161	161
162	162	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).
163	163
...	...	@@ -180,6 +180,7 @@
180	180	In the body of the Rulesets, the Codes and in general all the Values can be written without any other specification, because the artefact, which the Values are referred (Codelist, Concept) to can be deduced from the Ruleset signature.
181	181
182	182	== 12.3 Mapping between SDMX and VTL artefacts ==
	176	+
183	183	=== 12.3.1. When the mapping occurs ===
184	184
185	185	The mapping methods between the VTL and SDMX object classes allow transforming a SDMX definition in a VTL one and vice-versa for the artefacts to be manipulated. It should be remembered that VTL programs (i.e. Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformations (nameable artefacts). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result: the input operands of the expression and the result can be SDMX artefacts. Every time a SDMX object is referenced in a VTL Transformation as an input operand, there is the need to generate a VTL definition of the object, so that the VTL operations can take place. This can be made starting from the SDMX definition and applying a SDMX-VTL mapping method in the direction from SDMX to VTL. The possible mapping methods from SDMX to VTL are described in the following paragraphs and are conceived to allow the automatic deduction of the VTL definition of the object from the knowledge of the SDMX definition.
...	...	@@ -204,7 +204,7 @@
204	204
205	205	The possible mapping options are described in more detail in the following sections.
206	206
207		-=== 12.3.2 Mapping from SDMX to VTL data structures ===
	201	+=== 12.3.3 Mapping from SDMX to VTL data structures ===
208	208
209	209	==== 12.3.3.1 Basic Mapping ====
210	210
...	...	@@ -212,24 +212,23 @@
212	212
213	213	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:
214	214
215		-|**SDMX**|**VTL**
216		-|Dimension|(Simple) Identifier
217		-|TimeDimension|(Time) Identifier
218		-|Measure|Measure
219		-|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
220	220
221	221	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).
222	222
223	223	With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point.
224	224
225		-**12.3.3.2 Pivot Mapping**
	220	+==== 12.3.3.2 Pivot Mapping ====
226	226
227	227	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.
228	228
229		-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}}.
230	230
231		-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}}.
232		-
233	233	Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
234	234
235	235	If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
...	...	@@ -242,18 +242,19 @@
242	242	* The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
243	243	* An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
244	244	** 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;
245		-** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators). 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.
246	246
247	247	The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
248	248
249		-|**SDMX**|**VTL**
250		-|Dimension|(Simple) Identifier
251		-|TimeDimension|(Time) Identifier
252		-|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension
253		-|DataAttribute not depending on the MeasureDimension|Attribute
254		-|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" %)(((
255	255	One Attribute for each Code of the
256		-
257	257	SDMX MeasureDimension
258	258	)))
259	259
...	...	@@ -262,31 +262,21 @@
262	262	At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
263	263
264	264	* 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;
265		-* 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)
266		-
267		-Identifiers, (time) Identifier and Attributes.
268		-
269		-* 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
270		-
271		-Cj
272		-
	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.
	260	+* 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
273	273	* 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
274	274
275		-**12.3.3.3 From SDMX DataAttributes to VTL Measures**
	263	+==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
276	276
277		-* 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.
278	278
279		-Attributes.
280		-
281	281	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.
282	282
283	283	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.
284	284
285		-1.
286		-11.
287		-111. Mapping from VTL to SDMX data structures
	271	+=== 12.3.4 Mapping from VTL to SDMX data structures ===
288	288
289		-**12.3.4.1 Basic Mapping**
	273	+==== 12.3.4.1 Basic Mapping ====
290	290
291	291	The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
292	292
...	...	@@ -296,11 +296,12 @@
296	296
297	297	Mapping table:
298	298
299		-|**VTL**|**SDMX**
300		-|(Simple) Identifier|Dimension
301		-|(Time) Identifier|TimeDimension
302		-|Measure|Measure
303		-|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
304	304
305	305	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.
306	306
...	...	@@ -310,7 +310,7 @@
310	310
311	311	As said, 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.
312	312
313		-**12.3.4.2 Unpivot Mapping**
	298	+==== 12.3.4.2 Unpivot Mapping ====
314	314
315	315	An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
316	316
...	...	@@ -328,11 +328,12 @@
328	328
329	329	The summary mapping table of the **unpivot** mapping method is the following:
330	330
331		-|**VTL**|**SDMX**
332		-|(Simple) Identifier|Dimension
333		-|(Time) Identifier|TimeDimension
334		-|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
335		-|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
336	336
337	337	At observation / data point level:
338	338
...	...	@@ -346,7 +346,7 @@
346	346
347	347	In any case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the possible Codes of the SDMX MeasureDimension need to be listed in a SDMX Codelist, with proper id, agency and version; moreover, the SDMX DSD must have the AttributeRelationship for the DataAttributes, which does not exist in VTL.
348	348
349		-**12.3.4.3 From VTL Measures to SDMX Data Attributes**
	335	+==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ====
350	350
351	351	More than all for the multi-measure VTL structures (having more than one Measure Component), it may happen that the Measures of the VTL Data Structure need to be managed as DataAttributes in SDMX. Therefore, a third mapping method consists in transforming some VTL measures in a corresponding SDMX Measures and all the other VTL Measures in SDMX DataAttributes. This method is called M2A (“M2A” stands for “Measures to DataAttributes”).
352	352
...	...	@@ -354,18 +354,17 @@
354	354
355	355	The mapping table is the following:
356	356
357		-|VTL|SDMX
358		-|(Simple) Identifier|Dimension
359		-|(Time) Identifier|TimeDimension
360		-|Some Measures|Measure
361		-|Other Measures|DataAttribute
362		-|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
363	363
364	364	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.
365	365
366		-1.
367		-11.
368		-111. Declaration of the mapping methods between data structures
	353	+=== 12.3.5 Declaration of the mapping methods between data structures ===
369	369
370	370	In order to define and understand properly VTL Transformations, the applied mapping methods must be specified in the SDMX structural metadata. If the default mapping method (Basic) is applied, no specification is needed.
371	371
...	...	@@ -375,14 +375,10 @@
375	375
376	376	The VtlMappingScheme is a container for zero or more VtlDataflowMapping (it may contain also mappings towards artefacts other than dataflows).
377	377
378		-1.
379		-11.
380		-111. Mapping dataflow subsets to distinct VTL Data Sets
	363	+=== 12.3.6 Mapping dataflow subsets to distinct VTL Data Sets ===
381	381
382		-Until now it has been assumed to map one SMDX Dataflow to one VTL Data Set and vice-versa. This mapping one-to-one is not mandatory according to VTL because a VTL Data Set is meant to be a set of observations (data points) on a logical plane, having the same logical data structure and the same general meaning, independently of the possible physical representation or storage (see VTL 2.0 User Manual page 24), therefore a SDMX Dataflow can be seen either as a unique set of data observations
	365	+Until now it has been assumed to map one SMDX Dataflow to one VTL Data Set and vice-versa. This mapping one-to-one is not mandatory according to VTL because a VTL Data Set is meant to be a set of observations (data points) on a logical plane, having the same logical data structure and the same general meaning, independently of the possible physical representation or storage (see VTL 2.0 User Manual page 24), therefore a SDMX Dataflow can be seen either as a unique set of data observations (corresponding to one VTL Data Set) or as the union of many sets of data observations (each one corresponding to a distinct VTL Data Set).
383	383
384		-(corresponding to one VTL Data Set) or as the union of many sets of data observations (each one corresponding to a distinct VTL Data Set).
385		-
386	386	As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.{{footnote}}A typical example of this kind is the validation, and more in general the manipulation, of individual time series belonging to the same Dataflow, identifiable through the DimensionComponents of the Dataflow except the TimeDimension. The coding of these kind of operations might be simplified by mapping distinct time series (i.e. different parts of a SDMX Dataflow) to distinct VTL Data Sets.{{/footnote}}
387	387
388	388	Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL Data Sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.{{footnote}}Please note that this kind of mapping is only an option at disposal of the definer of VTL Transformations; in fact it remains always possible to manipulate the needed parts of SDMX Dataflows by means of VTL operators (e.g. “sub”, “filter”, “calc”, “union” …), maintaining a mapping one-to-one between SDMX Dataflows and VTL Data Sets.{{/footnote}}
...	...	@@ -403,11 +403,11 @@
403	403
404	404	Therefore, the generic name of this kind of VTL datasets would be:
405	405
406		-'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
	387	+> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
407	407
408	408	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:
409	409
410		-‘DF(1.0.0)/POPULATION.USA’
	391	+> ‘DF(1.0.0)/POPULATION.USA’
411	411
412	412	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.
413	413
...	...	@@ -421,26 +421,22 @@
421	421
422	422	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.
423	423
424		-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 …).
425	425
426		-basic, pivot …).
427		-
428	428	In the example above, for all the datasets of the kind
429	429
430		-‘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.
431	431
432	432	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:
433	433
434		-‘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	+> … … …
435	435
436		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
437		-
438		-‘DF1(1.0.0)/POPULATION.CANADA’ :=
439		-
440		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
441		-
442		-… … …
443		-
444	444	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}}
445	445
446	446	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.
...	...	@@ -449,10 +449,9 @@
449	449
450	450	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
451	451
452		-‘DF1(1.0.0)/POPULATION.’ :=
	429	+> ‘DF1(1.0.0)/POPULATION.’ :=
	430	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
453	453
454		-DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
455		-
456	456	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
457	457
458	458	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
...	...	@@ -470,59 +470,39 @@
470	470
471	471	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}}
472	472
473		-‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
	449	+> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
474	474
475	475	Some examples follow, for some specific values of INDICATOR and COUNTRY:
476	476
477		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
	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	+> … … …
478	478
479		-… … …
480		-
481		-‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
482		-
483		-‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
484		-
485		-… … …
486		-
487	487	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:
488	488
489	489	VTL dataset   INDICATOR value COUNTRY value
490	490
	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	+> … … …
491	491
492		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
493		-
494		-‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
495		-
496		-‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
497		-
498		-‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
499		-
500		-… … …
501		-
502	502	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:
503	503
504		-DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
	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	+> …);
505	505
506		-DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
507		-
508		-DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
509		-
510		-[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
511		-
512		-DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
513		-
514		-DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
515		-
516		-DF2bis_GDPPERCAPITA_CANADA’,
517		-
518		-… ,
519		-
520		-DF2bis_POPGROWTH_USA’,
521		-
522		-DF2bis_POPGROWTH_CANADA’
523		-
524		-…);
525		-
526	526	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.
527	527
528	528	Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets.{{footnote}}In case the ordered concatenation notation from VTL to SDMX is used, the set of Transformations described above is implicitly performed; therefore, in order to test the overall compliance of the VTL program to the VTL consistency rules, these implicit Transformations have to be considered as part of the VTL program even if they are not explicitly coded.{{/footnote}}{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
...	...	@@ -529,33 +529,30 @@
529	529
530	530	It is worth noting that in the direction from VTL to SDMX it is mandatory to specify the value for every Dimension on which the mapping is based (in other word, in the name of the calculated VTL dataset is not possible to omit the value of some of the Dimensions).
531	531
532		-1.
533		-11.
534		-111. Mapping variables and value domains between VTL and SDMX
	488	+=== 12.3.7 Mapping variables and value domains between VTL and SDMX ===
535	535
536	536	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
537	537
538		-|VTL|SDMX
539		-|**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^^
540		-|**Represented Variable**|**Concept** with a definite Representation
541		-|**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" %)(((
542	542	**Representation** (see the Structure
543		-
544	544	Pattern in the Base Package)
545	545	)))
546		-|**Enumerated Value Domain / Code List**|**Codelist**
547		-|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
548		-|**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" %)(((
549	549	non-enumerated** Representation**
550		-
551	551	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
552	552	)))
553		-|**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
554		-| |to a valid **value **(for non-enumerated** **Representations)
555		-|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
556		-|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
557		-|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
558		-|**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
559	559
560	560	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).
561	561
...	...	@@ -563,8 +563,10 @@
563	563
564	564	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
565	565
566		-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)
567	567
	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	+
568	568	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
569	569
570	570	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -571,28 +571,29 @@
571	571
572	572	It remains up to the SDMX-VTL definer also the assurance of the consistency between a VTL Ruleset defined on Variables and the SDMX Components on which the Ruleset is applied. In fact, a VTL Ruleset is expressed by means of the values of the Variables (i.e. SDMX Concepts), i.e. assuming definite representations for them (e.g. ISOalpha-3 for country). If the Ruleset is applied to SDMX Components that have the same name of the Concept they refer to but different representations (e.g. ISO-alpha-2 for country), the Ruleset cannot work properly.
573	573
574		-1.
575		-11. Mapping between SDMX and VTL Data Types
576		-111. VTL Data types
	529	+== 12.4 Mapping between SDMX and VTL Data Types ==
577	577
	531	+=== 12.4.1 VTL Data types ===
	532	+
578	578	According to the VTL User Guide the possible operations in VTL depend on the data types of the artefacts. For example, numbers can be multiplied but text strings cannot. In the VTL Transformations, the compliance between the operators and the data types of their operands is statically checked, i.e., violations result in compile-time errors.
579	579
580	580	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:
581	581
582		-[[image:1750067055028-964.png]]
583	583
584		-==== Figure 22 – VTL Data Types ====
	538	+[[image:1750070288958-132.png]]
585	585
	540	+**Figure 22 – VTL Data Types**
	541	+
586	586	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.
587	587
588	588	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):
589	589
590		-==== Figure 23 – VTL Basic Scalar Types ====
	546	+[[image:1750070310572-584.png]]
591	591
592		-1.
593		-11.
594		-111. VTL basic scalar types and SDMX data types
	548	+**Figure 23 – VTL Basic Scalar Types**
595	595
	550	+=== 12.4.2 VTL basic scalar types and SDMX data types ===
	551	+
596	596	The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
597	597
598	598	The internal representation is the format used within a VTL system to represent (and process) all the scalar values of a certain type. In principle, this format is hidden and not necessarily known by users. The external representations are instead the external formats of the values of a certain basic scalar type, i.e. the formats known by the users. For example, the internal representation of the dates can be an integer counting the days since a predefined date (e.g. from 01/01/4713 BC up to 31/12/5874897 AD like in Postgres) while two possible external representations are the formats YYYY-MMGG and MM-GG-YYYY (e.g. respectively 2010-12-31 and 12-31-2010).
...	...	@@ -609,309 +609,256 @@
609	609
610	610	The opposite conversion, i.e. from VTL to SDMX, happens when a VTL result, i.e. a VTL Data Set output of a Transformation, must become a SDMX artefact (or part of it). The values of the VTL result must be converted into the desired (SDMX) external representations (data types) of the SDMX artefact.
611	611
612		-1.
613		-11.
614		-111. Mapping SDMX data types to VTL basic scalar types
	568	+=== 12.4.3 Mapping SDMX data types to VTL basic scalar types ===
615	615
616	616	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
617	617
618		-|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
619		-|(((
	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" %)(((
620	620	String
621		-
622	622	(string allowing any character)
623		-)))|string
624		-|(((
625		-Alpha
626		-
	577	+)))|(% style="width:221px" %)string
	578	+|(% style="width:360px" %)(((
	579	+Alpha
627	627	(string which only allows A-z)
628		-)))|string
629		-|(((
	581	+)))|(% style="width:221px" %)string
	582	+|(% style="width:360px" %)(((
630	630	AlphaNumeric
631		-
632	632	(string which only allows A-z and 0-9)
633		-)))|string
634		-|(((
	585	+)))|(% style="width:221px" %)string
	586	+|(% style="width:360px" %)(((
635	635	Numeric
636		-
637	637	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
638		-)))|string
639		-|(((
	589	+)))|(% style="width:221px" %)string
	590	+|(% style="width:360px" %)(((
640	640	BigInteger
641		-
642	642	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
643		-)))|integer
644		-|(((
	593	+)))|(% style="width:221px" %)integer
	594	+|(% style="width:360px" %)(((
645	645	Integer
646		-
647	647	(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
648		-
649	649	(inclusive))
650		-)))|integer
651		-|(((
	598	+)))|(% style="width:221px" %)integer
	599	+|(% style="width:360px" %)(((
652	652	Long
653		-
654	654	(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
655		-
656	656	+9223372036854775807 (inclusive))
657		-)))|integer
658		-|(((
	603	+)))|(% style="width:221px" %)integer
	604	+|(% style="width:360px" %)(((
659	659	Short
660		-
661	661	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
662		-)))|integer
663		-|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
664		-|(((
	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" %)(((
665	665	Float
666		-
667	667	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
668		-)))|number
669		-|(((
	612	+)))|(% style="width:221px" %)number
	613	+|(% style="width:360px" %)(((
670	670	Double
671		-
672	672	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
673		-)))|number
674		-|(((
	616	+)))|(% style="width:221px" %)number
	617	+|(% style="width:360px" %)(((
675	675	Boolean
676		-
677	677	(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
678		-
679	679	binary-valued logic: {true, false})
680		-)))|boolean
681		-|(((
	621	+)))|(% style="width:221px" %)boolean
	622	+|(% style="width:360px" %)(((
682	682	URI
683		-
684	684	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
685		-)))|string
686		-|(((
	625	+)))|(% style="width:221px" %)string
	626	+|(% style="width:360px" %)(((
687	687	Count
688		-
689	689	(an integer following a sequential pattern, increasing by 1 for each occurrence)
690		-)))|integer
691		-|(((
	629	+)))|(% style="width:221px" %)integer
	630	+|(% style="width:360px" %)(((
692	692	InclusiveValueRange
693		-
694	694	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
695		-)))|number
696		-|(((
	633	+)))|(% style="width:221px" %)number
	634	+|(% style="width:360px" %)(((
697	697	ExclusiveValueRange
698		-
699	699	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
700		-)))|number
701		-|(((
	637	+)))|(% style="width:221px" %)number
	638	+|(% style="width:360px" %)(((
702	702	Incremental
703		-
704	704	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
705		-)))|number
706		-|(((
	641	+)))|(% style="width:221px" %)number
	642	+|(% style="width:360px" %)(((
707	707	ObservationalTimePeriod
708		-
709	709	(superset of StandardTimePeriod and TimeRange)
710		-)))|time
711		-|(((
	645	+)))|(% style="width:221px" %)time
	646	+|(% style="width:360px" %)(((
712	712	StandardTimePeriod
713		-
714	714	(superset of BasicTimePeriod and ReportingTimePeriod)
715		-)))|time
716		-|(((
	649	+)))|(% style="width:221px" %)time
	650	+|(% style="width:360px" %)(((
717	717	BasicTimePeriod
718		-
719	719	(superset of GregorianTimePeriod and DateTime)
720		-)))|date
721		-|(((
	653	+)))|(% style="width:221px" %)date
	654	+|(% style="width:360px" %)(((
722	722	GregorianTimePeriod
723		-
724	724	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
725		-)))|date
726		-|GregorianYear (YYYY)|date
727		-|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
728		-|GregorianDay (YYYY-MM-DD)|date
729		-|(((
	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" %)(((
730	730	ReportingTimePeriod
731		-
732	732	(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
733		-)))|time_period
734		-|(((
	664	+)))|(% style="width:221px" %)time_period
	665	+|(% style="width:360px" %)(((
735	735	ReportingYear
736		-
737	737	(YYYY-A1 – 1 year period)
738		-)))|time_period
739		-|(((
	668	+)))|(% style="width:221px" %)time_period
	669	+|(% style="width:360px" %)(((
740	740	ReportingSemester
741		-
742	742	(YYYY-Ss – 6 month period)
743		-)))|time_period
744		-|(((
	672	+)))|(% style="width:221px" %)time_period
	673	+|(% style="width:360px" %)(((
745	745	ReportingTrimester
746		-
747	747	(YYYY-Tt – 4 month period)
748		-)))|time_period
749		-|(((
	676	+)))|(% style="width:221px" %)time_period
	677	+|(% style="width:360px" %)(((
750	750	ReportingQuarter
751		-
752	752	(YYYY-Qq – 3 month period)
753		-)))|time_period
754		-|(((
	680	+)))|(% style="width:221px" %)time_period
	681	+|(% style="width:360px" %)(((
755	755	ReportingMonth
756		-
757	757	(YYYY-Mmm – 1 month period)
758		-)))|time_period
759		-|ReportingWeek|time_period
760		-| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
761		-|(((
	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" %)(((
762	762	ReportingDay
763		-
764	764	(YYYY-Dddd – 1 day period)
765		-)))|time_period
766		-|(((
	690	+)))|(% style="width:221px" %)time_period
	691	+|(% style="width:360px" %)(((
767	767	DateTime
768		-
769	769	(YYYY-MM-DDThh:mm:ss)
770		-)))|date
771		-|(((
	694	+)))|(% style="width:221px" %)date
	695	+|(% style="width:360px" %)(((
772	772	TimeRange
773		-
774	774	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
775		-)))|time
776		-|(((
	698	+)))|(% style="width:221px" %)time
	699	+|(% style="width:360px" %)(((
777	777	Month
778		-
779	779	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
780		-)))|string
781		-|(((
	702	+)))|(% style="width:221px" %)string
	703	+|(% style="width:360px" %)(((
782	782	MonthDay
783		-
784	784	(~-~-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)
785		-)))|string
786		-|(((
	706	+)))|(% style="width:221px" %)string
	707	+|(% style="width:360px" %)(((
787	787	Day
788		-
789	789	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
790		-)))|string
791		-|(((
	710	+)))|(% style="width:221px" %)string
	711	+|(% style="width:360px" %)(((
792	792	Time
793		-
794	794	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
795		-)))|string
796		-|(((
	714	+)))|(% style="width:221px" %)string
	715	+|(% style="width:360px" %)(((
797	797	Duration
798		-
799	799	(corresponds to XML Schema xs:duration datatype)
800		-)))|duration
801		-|XHTML|Metadata type – not applicable
802		-|KeyValues|Metadata type – not applicable
803		-|IdentifiableReference|Metadata type – not applicable
804		-|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
805	805
806		-додол
	724	+**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
807	807
808		-==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
809		-
810	810	When VTL takes in input SDMX artefacts, it is assumed that a type conversion according to the table above always happens. In case a different VTL basic scalar type is desired, it can be achieved in the VTL program taking in input the default VTL basic scalar type above and applying to it the VTL type conversion features (see the implicit and explicit type conversion and the "cast" operator in the VTL Reference Manual).
811	811
812		-1.
813		-11.
814		-111. Mapping VTL basic scalar types to SDMX data types
	728	+=== 12.4.4 Mapping VTL basic scalar types to SDMX data types ===
815	815
816	816	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
817	817
818		-|(((
819		-VTL basic
820		-
821		-scalar type
822		-)))|(((
	732	+(% style="width:748.294px" %)
	733	+|(% style="width:164px" %)(((
	734	+VTL basic scalar type
	735	+)))|(% style="width:304px" %)(((
823	823	Default SDMX data type
824		-
825		-(BasicComponentDataType
826		-
827		-)
828		-)))|Default output format
829		-|String|String|Like XML (xs:string)
830		-|Number|Float|Like XML (xs:float)
831		-|Integer|Integer|Like XML (xs:int)
832		-|Date|DateTime|YYYY-MM-DDT00:00:00Z
833		-|Time|StandardTimePeriod|<date>/<date> (as defined above)
834		-|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" %)(((
835	835	ReportingTimePeriod
836		-
837	837	(StandardReportingPeriod)
838		-)))|(((
	747	+)))|(% style="width:277px" %)(((
839	839	YYYY-Pppp
840		-
841	841	(according to SDMX )
842	842	)))
843		-|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
844		-|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"
845	845
846		-==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
	754	+**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
847	847
848		-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).
849	849
850		-Transformations and Expressions of the SDMX information model).
851		-
852	852	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.
853	853
854		-|(% colspan="2" %)VTL special characters for the formatting masks
855		-|(% colspan="2" %)
856		-|(% colspan="2" %)Number
857		-|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
858		-|E|one numeric digit (for the exponent of the scientific notation)
859		-|. (dot)|possible separator between the integer and the decimal parts.
860		-|, (comma)|possible separator between the integer and the decimal parts.
861		-| |
862		-|(% colspan="2" %)Time and duration
863		-|C|century
864		-|Y|year
865		-|S|semester
866		-|Q|quarter
867		-|M|month
868		-|W|week
869		-|D|day
870		-|h|hour digit (by default on 24 hours)
871		-|M|minute
872		-|S|second
873		-|D|decimal of second
874		-|P|period indicator (representation in one digit for the duration)
875		-|P|number of the periods specified in the period indicator
876		-|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
877		-|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
878		-|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
879		-|Month|lowercase textual representation of the month (e.g., january)
880		-|Day|lowercase textual representation of the month (e.g., monday)
881		-|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
882		-|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
883		-| |
884		-|(% colspan="2" %)String
885		-|X|any string character
886		-|Z|any string character from "A" to "z"
887		-|9|any string character from "0" to "9"
888		-| |
889		-|(% colspan="2" %)Boolean
890		-|B|Boolean using "true" for True and "false" for False
891		-|1|Boolean using "1" for True and "0" for False
892		-|0|Boolean using "0" for True and "1" for False
893		-| |
894		-|(% colspan="2" %)Other qualifiers
895		-|*|an arbitrary number of digits (of the preceding type)
896		-|+|at least one digit (of the preceding type)
897		-|( )|optional digits (specified within the brackets)
898		-|\|prefix for the special characters that must appear in the mask
899		-|N|fixed number of digits used in the preceding textual representation of the month or the day
900		-| |
	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" %)
901	901
902	902	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}}.
903	903
904		-1.
905		-11.
906		-111. Null Values
	811	+=== 12.4.3 Null Values ===
907	907
908	908	In the conversions from SDMX to VTL it is assumed by default that a missing value in SDMX becomes a NULL in VTL. After the conversion, the NULLs can be manipulated through the proper VTL operators.
909	909
910	910	On the other side, the VTL programs can produce in output NULL values for Measures and Attributes (Null values are not allowed in the Identifiers). In the conversion from VTL to SDMX, it is assumed that a NULL in VTL becomes a missing value in SDMX. In the conversion from VTL to SDMX, the default assumption can be overridden, separately for each VTL basic scalar type, by specifying which the value that represents the NULL in SDMX is. This can be specified in the attribute "nullValue" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model). A CustomType belongs to a CustomTypeScheme, which can be referenced by one or more TransformationScheme (i.e. VTL programs). The overriding assumption is applied for all the SDMX Dataflows calculated in the TransformationScheme.
911	911
912		-1.
913		-11.
914		-111. Format of the literals used in VTL Transformations
	817	+=== 12.4.5 Format of the literals used in VTL Transformations ===
915	915
916	916	The VTL programs can contain literals, i.e. specific values of certain data types written directly in the VTL definitions or expressions. The VTL does not prescribe a specific format for the literals and leave the specific VTL systems and the definers of VTL Transformations free of using their preferred formats.
917	917
...	...	@@ -925,7 +925,6 @@
925	925
926	926	In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
927	927
928		-
929	929	----
930	930
931	931	{{putFootnotes/}}

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