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
...	...	@@ -212,11 +212,12 @@
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
...	...	@@ -226,10 +226,8 @@
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).
...	...	@@ -242,16 +242,18 @@
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	256	SDMX MeasureDimension
257	257	)))
...	...	@@ -261,19 +261,14 @@
261	261	At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
262	262
263	263	* 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;
264		-* 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)
265		-
266		-Identifiers, (time) Identifier and Attributes.
267		-
	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.
268	268	* 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
269	269	* 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
270	270
271	271	==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
272	272
273		-* 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.
274	274
275		-Attributes.
276		-
277	277	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.
278	278
279	279	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.
...	...	@@ -290,11 +290,12 @@
290	290
291	291	Mapping table:
292	292
293		-|**VTL**|**SDMX**
294		-|(Simple) Identifier|Dimension
295		-|(Time) Identifier|TimeDimension
296		-|Measure|Measure
297		-|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
298	298
299	299	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.
300	300
...	...	@@ -322,11 +322,12 @@
322	322
323	323	The summary mapping table of the **unpivot** mapping method is the following:
324	324
325		-|**VTL**|**SDMX**
326		-|(Simple) Identifier|Dimension
327		-|(Time) Identifier|TimeDimension
328		-|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
329		-|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
330	330
331	331	At observation / data point level:
332	332
...	...	@@ -348,12 +348,13 @@
348	348
349	349	The mapping table is the following:
350	350
351		-|VTL|SDMX
352		-|(Simple) Identifier|Dimension
353		-|(Time) Identifier|TimeDimension
354		-|Some Measures|Measure
355		-|Other Measures|DataAttribute
356		-|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
357	357
358	358	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.
359	359
...	...	@@ -391,11 +391,11 @@
391	391
392	392	Therefore, the generic name of this kind of VTL datasets would be:
393	393
394		-'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
	387	+> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
395	395
396	396	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:
397	397
398		-‘DF(1.0.0)/POPULATION.USA’
	391	+> ‘DF(1.0.0)/POPULATION.USA’
399	399
400	400	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.
401	401
...	...	@@ -409,26 +409,22 @@
409	409
410	410	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.
411	411
412		-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 …).
413	413
414		-basic, pivot …).
415		-
416	416	In the example above, for all the datasets of the kind
417	417
418		-‘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.
419	419
420	420	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:
421	421
422		-‘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	+> … … …
423	423
424		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
425		-
426		-‘DF1(1.0.0)/POPULATION.CANADA’ :=
427		-
428		-DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
429		-
430		-… … …
431		-
432	432	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}}
433	433
434	434	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.
...	...	@@ -437,10 +437,9 @@
437	437
438	438	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
439	439
440		-‘DF1(1.0.0)/POPULATION.’ :=
	429	+> ‘DF1(1.0.0)/POPULATION.’ :=
	430	+> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
441	441
442		-DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
443		-
444	444	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
445	445
446	446	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
...	...	@@ -458,41 +458,38 @@
458	458
459	459	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}}
460	460
461		-‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
	449	+> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
462	462
463	463	Some examples follow, for some specific values of INDICATOR and COUNTRY:
464	464
465		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
466		-… … …
	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	+> … … …
467	467
468		-‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
469		-‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
470		-… … …
471		-
472	472	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:
473	473
474	474	VTL dataset   INDICATOR value COUNTRY value
475	475
476		-‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
477		-‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
478		-‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
479		-‘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	+> … … …
480	480
481		-… … …
482		-
483	483	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:
484	484
485		-DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
486		-DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
487		-DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
488		-[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
489		-DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
490		-DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
491		-DF2bis_GDPPERCAPITA_CANADA’,
492		-… ,
493		-DF2bis_POPGROWTH_USA’,
494		-DF2bis_POPGROWTH_CANADA’
495		-…);
	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	+> …);
496	496
497	497	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.
498	498
...	...	@@ -504,25 +504,26 @@
504	504
505	505	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
506	506
507		-|VTL|SDMX
508		-|**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^^
509		-|**Represented Variable**|**Concept** with a definite Representation
510		-|**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" %)(((
511	511	**Representation** (see the Structure
512	512	Pattern in the Base Package)
513	513	)))
514		-|**Enumerated Value Domain / Code List**|**Codelist**
515		-|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
516		-|**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" %)(((
517	517	non-enumerated** Representation**
518	518	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
519	519	)))
520		-|**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
521		-| |to a valid **value **(for non-enumerated** **Representations)
522		-|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
523		-|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
524		-|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
525		-|**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
526	526
527	527	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).
528	528
...	...	@@ -530,8 +530,10 @@
530	530
531	531	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
532	532
533		-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)
534	534
	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	+
535	535	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
536	536
537	537	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -539,6 +539,7 @@
539	539	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.
540	540
541	541	== 12.4 Mapping between SDMX and VTL Data Types ==
	530	+
542	542	=== 12.4.1 VTL Data types ===
543	543
544	544	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.
...	...	@@ -545,8 +545,9 @@
545	545
546	546	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:
547	547
548		-[[image:1750067055028-964.png]]
549	549
	538	+[[image:1750070288958-132.png]]
	539	+
550	550	**Figure 22 – VTL Data Types**
551	551
552	552	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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