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1		-12 Validation and Transformation Language (VTL)

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1		-{{box title="**Contents**"}}
2		-{{toc/}}
3		-{{/box}}
	1	+= 12 Validation and Transformation Language (VTL) =
4	4
5	5	== 12.1 Introduction ==
6	6
7		-The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones{{footnote}}The Validation and Transformation Language is a standard language designed and published under the SDMX initiative. VTL is described in the VTL User and Reference Guides available on the SDMX website https://sdmx.org.{{/footnote}}. The purpose of the VTL in the SDMX context is to enable the:
	5	+The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones^^[[^^5^^>>path:#sdfootnote5sym||name="sdfootnote5anc"]]^^. The purpose of the VTL in the SDMX context is to enable the:
8	8
9	9	* definition of validation and transformation algorithms, in order to specify how to calculate new data from existing ones;
10	10	* exchange of the definition of VTL algorithms, also together the definition of the data structures of the involved data (for example, exchange the data structures of a reporting framework together with the validation rules to be applied, exchange the input and output data structures of a calculation task together with the VTL Transformations describing the calculation algorithms);
...	...	@@ -12,7 +12,7 @@
12	12
13	13	It is important to note that the VTL has its own information model (IM), derived from the Generic Statistical Information Model (GSIM) and described in the VTL User Guide. The VTL IM is designed to be compatible with more standards, like SDMX, DDI (Data Documentation Initiative) and GSIM, and includes the model artefacts that can be manipulated (inputs and/or outputs of Transformations, e.g. "Data Set", "Data Structure") and the model artefacts that allow the definition of the transformation algorithms (e.g. "Transformation", "Transformation Scheme").
14	14
15		-The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate{{footnote}}In this chapter, in order to distinguish VTL and SDMX model artefacts, the VTL ones are written in the Arial font while the SDMX ones in Courier New{{/footnote}}. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of Transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL "Data Set", which do not correspond one another: as a matter of fact, the VTL "Data Set" maps to the SDMX "Dataflow", while the SDMX "Dataset" has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL Transformations). A SDMX "Dataset", however, is an instance of a SDMX "Dataflow" and can be the artefact on which the VTL transformations are executed (i.e., the Transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
	13	+The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate^^[[^^6^^>>path:#sdfootnote6sym||name="sdfootnote6anc"]]^^. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of Transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL "Data Set", which do not correspond one another: as a matter of fact, the VTL "Data Set" maps to the SDMX "Dataflow", while the SDMX "Dataset" has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL Transformations). A SDMX "Dataset", however, is an instance of a SDMX "Dataflow" and can be the artefact on which the VTL transformations are executed (i.e., the Transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
16	16
17	17	The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of
18	18
...	...	@@ -30,7 +30,7 @@
30	30
31	31	In any case, the aliases used in the VTL Transformations have to be mapped to the
32	32
33		-SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
	31	+SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets^^[[^^7^^>>path:#sdfootnote7sym||name="sdfootnote7anc"]]^^ or User Defined Operators^^[[^^8^^>>path:#sdfootnote8sym||name="sdfootnote8anc"]]^^ to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
34	34
35	35	The correspondence between an alias and a SDMX artefact must be one-to-one, meaning that a generic alias identifies one and just one SDMX artefact while a SDMX artefact is identified by one and just one alias. In other words, within a VtlMappingScheme an artefact can have just one alias and different artefacts cannot have the same alias.
36	36
...	...	@@ -40,7 +40,7 @@
40	40
41	41	This approach has the advantage that in the VTL code the URN of the referenced artefacts is directly intelligible by a human reader but has the drawback that the references are verbose.
42	42
43		-The SDMX URN{{footnote}}For a complete description of the structure of the URN see the SDMX 2.1 Standards - Section 5 - Registry Specifications, paragraph 6.2.2 ("Universal Resource Name (URN)").{{/footnote}} is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:
	41	+The SDMX URN^^[[^^9^^>>path:#sdfootnote9sym||name="sdfootnote9anc"]]^^ is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:
44	44
45	45	* SDMXprefix
46	46	* SDMX-IM-package-name
...	...	@@ -48,13 +48,15 @@
48	48	* agency-id
49	49	* maintainedobject-id
50	50	* maintainedobject-version
51		-* container-object-id{{footnote}}The container-object-id can repeat and may not be present.{{/footnote}}
	49	+* container-object-id ^^[[^^10^^>>path:#sdfootnote10sym||name="sdfootnote10anc"]]^^
52	52	* object-id
53	53
54	54	The generic structure of the URN is the following:
55	55
56		-SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id (maintainedobject-version).*container-object-id.object-id
	54	+SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id
57	57
	56	+(maintainedobject-version).*container-object-id.object-id
	57	+
58	58	The **SDMXprefix** is "urn:sdmx:org", always the same for all SDMX artefacts.
59	59
60	60	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".
...	...	@@ -63,10 +63,13 @@
63	63
64	64	The agency-id is the acronym of the agency that owns the definition of the artefact, for example for the Eurostat artefacts the agency-id is "ESTAT"). The agency-id can be composite (for example AgencyA.Dept1.Unit2).
65	65
66		-The maintainedobject-id is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable{{footnote}}i.e., the artefact belongs to a maintainable class{{/footnote}}, coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
	66	+The maintainedobject-id is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable^^[[^^11^^>>path:#sdfootnote11sym||name="sdfootnote11anc"]]^^, coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
67	67
68	68	* if the artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the Dataflow name (dataflow-id);
69		-* if the artefact is a Dimension, Measure, TimeDimension or DataAttribute, which are not maintainable and belong to the DataStructure maintainable class, the maintainedobject-id is the name of the DataStructure (dataStructure-id) which the artefact belongs to;
	69	+* if the artefact is a Dimension, Measure, TimeDimension or DataAttribute, which are not maintainable and belong to the
	70	+
	71	+DataStructure maintainable class, the maintainedobject-id is the name of the DataStructure (dataStructure-id) which the artefact belongs to;
	72	+
70	70	* if the artefact is a Concept, which is not maintainable and belongs to the ConceptScheme maintainable class, the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id) which the artefact belongs to;
71	71	* if the artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the Codelist name (codelist-id).
72	72
...	...	@@ -79,10 +79,12 @@
79	79	* 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)
80	80	* if the artefact is a Concept (the object-id is the name of the Concept)
81	81
82		-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}}:
	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^^[[^^12^^>>path:#sdfootnote12sym||name="sdfootnote12anc"]]^^:
83	83
84	84	'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
	88	+
85	85	'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
	90	+
86	86	'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
87	87
88	88	=== 12.2.3 Abbreviation of the URN ===
...	...	@@ -91,10 +91,10 @@
91	91
92	92	The URN can be abbreviated by omitting the parts that are not essential for the identification of the artefact or that can be deduced from other available information, including the context in which the invocation is made. The possible abbreviations are described below.
93	93
94		-* 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. • 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:
	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. • The SDMX-IM-package-name** &nbsp;**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:
95	95	** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist.
96		-* 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}}.
97		-* 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).
	101	+* 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^^[[^^13^^>>path:#sdfootnote13sym||name="sdfootnote13anc"]]^^, the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section "Mapping between VTL and SDMX" hereinafter)^^[[^^14^^>>path:#sdfootnote14sym||name="sdfootnote14anc"]]^^.
	102	+* 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^^[[^^15^^>>path:#sdfootnote15sym||name="sdfootnote15anc"]]^^. 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).
98	98	* 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;
99	99	** 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;
100	100	** 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;
...	...	@@ -107,7 +107,9 @@
107	107	For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
108	108
109	109	'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
	115	+
110	110	'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
	117	+
111	111	'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
112	112
113	113	by omitting all the non-essential parts would become simply:
...	...	@@ -114,11 +114,11 @@
114	114
115	115	DFR := DF1 + DF2
116	116
117		-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.{{/footnote}}:
	124	+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^^[[^^16^^>>path:#sdfootnote16sym||name="sdfootnote16anc"]]^^:
118	118
119	119	'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
120	120
121		-if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply{{footnote}}Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}:
	128	+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^^:
122	122
123	123	CL_FREQ
124	124
...	...	@@ -132,7 +132,7 @@
132	132
133	133	SECTOR
134	134
135		-For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as{{footnote}}The result DFR(1.0.0) is be equal to DF1(1.0.0) save that the component SECTOR is called SEC{{/footnote}}:
	142	+For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as^^[[^^17^^>>path:#sdfootnote17sym||name="sdfootnote17anc"]]^^:
136	136
137	137	'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
138	138
...	...	@@ -164,9 +164,9 @@
164	164
165	165	The VTL Rulesets have a signature, in which the Value Domains or the Variables on which the Ruleset is defined are declared, and a body, which contains the Rules.
166	166
167		-In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist, while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation{{footnote}}Rulesets of this kind cannot be reused when the referenced Concept has a different representation.{{/footnote}}.
	174	+In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist, while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation^^[[^^18^^>>path:#sdfootnote18sym||name="sdfootnote18anc"]]^^.
168	168
169		-In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called "valueDomain" and "variable" for the Datapoint Rulesets and "ruleValueDomain", "ruleVariable", "condValueDomain" "condVariable" for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific Ruleset definition statement and cannot be mapped to SDMX.{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}}
	176	+In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called "valueDomain" and "variable" for the Datapoint Rulesets and "ruleValueDomain", "ruleVariable", "condValueDomain" "condVariable" for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific Ruleset definition statement and cannot be mapped to SDMX.^^[[^^19^^>>path:#sdfootnote19sym||name="sdfootnote19anc"]]^^
170	170
171	171	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.
172	172
...	...	@@ -178,15 +178,15 @@
178	178
179	179	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.
180	180
181		-In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged{{footnote}}If a calculated artefact is persistent, it needs a persistent definition, i.e. a SDMX definition in a SDMX environment. In addition, possible calculated artefact that are not persistent may require a SDMX definition, for example when the result of a non-persistent calculation is disseminated through SDMX tools (like an inquiry tool).{{/footnote}}.
	188	+In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged^^[[^^20^^>>path:#sdfootnote20sym||name="sdfootnote20anc"]]^^.
182	182
183	183	The mapping methods from VTL to SDMX are described in the following paragraphs as well, however they do not allow the complete SDMX definition to be automatically deduced from the VTL definition, more than all because the former typically contains additional information in respect to the latter. For example, the definition of a SDMX DSD includes also some mandatory information not available in VTL (like the concept scheme to which the SDMX components refer, the ‘usage’ and ‘attributeRelationship’ for the DataAttributes and so on). Therefore the mapping methods from VTL to SDMX provide only a general guidance for generating SDMX definitions properly starting from the information available in VTL, independently of how the SDMX definition it is actually generated (manually, automatically or part and part).
184	184
185	185	=== 12.3.2 General mapping of VTL and SDMX data structures ===
186	186
187		-This section makes reference to the VTL "Model for data and their structure"{{footnote}}See the VTL 2.0 User Manual{{/footnote}} and the correspondent SDMX "Data Structure Definition"{{footnote}}See the SDMX Standards Section 2 – Information Model{{/footnote}}.
	194	+This section makes reference to the VTL "Model for data and their structure"^^[[^^21^^>>path:#sdfootnote21sym||name="sdfootnote21anc"]]^^ and the correspondent SDMX "Data Structure Definition"^^[[^^22^^>>path:#sdfootnote22sym||name="sdfootnote22anc"]]^^.
188	188
189		-The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).{{footnote}}Besides the mapping between one SDMX Dataflow and one VTL Data Set, it is also possible to map distinct parts of a SDMX Dataflow to different VTL Data Set, as explained in a following paragraph.{{/footnote}}
	196	+The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).^^[[^^23^^>>path:#sdfootnote23sym||name="sdfootnote23anc"]]^^
190	190
191	191	While the VTL Transformations are defined in term of Dataflow definitions, they are assumed to be executed on instances of such Dataflows, provided at runtime to the VTL engine (the mechanism for identifying the instances to be processed are not part of the VTL specifications and depend on the implementation of the VTL-based systems). As already said, the SDMX Datasets are instances of SDMX Dataflows, therefore a VTL Transformation defined on some SDMX Dataflows can be applied on some corresponding SDMX Datasets.
192	192
...	...	@@ -206,28 +206,32 @@
206	206
207	207	The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes. When transforming **from SDMX to VTL**, this method consists in leaving the components unchanged and maintaining their names and roles, according to the following table:
208	208
209		-(% style="width:529.294px" %)
210		-|(% style="width:151px" %)**SDMX**|(% style="width:375px" %)**VTL**
211		-|(% style="width:151px" %)Dimension|(% style="width:375px" %)(Simple) Identifier
212		-|(% style="width:151px" %)TimeDimension|(% style="width:375px" %)(Time) Identifier
213		-|(% style="width:151px" %)Measure|(% style="width:375px" %)Measure
214		-|(% style="width:151px" %)DataAttribute|(% style="width:375px" %)Attribute
	216	+|**SDMX**|**VTL**
	217	+|Dimension|(Simple) Identifier
	218	+|TimeDimension|(Time) Identifier
215	215
	220	+[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape4" height="1" width="192"]]
	221	+
	222	+|Measure|Measure
	223	+|DataAttribute|Attribute
	224	+
216	216	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).
217	217
218		-With the Basic mapping, one SDMX observation{{footnote}}Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.{{/footnote}} generates one VTL data point.
	227	+With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point.
219	219
220		-==== 12.3.3.2 Pivot Mapping ====
	229	+**12.3.3.2 Pivot Mapping**
221	221
222	222	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.
223	223
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}}.
	233	+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
225	225
	235	+MeasureDimensions considered as a joint variable^^[[^^24^^>>path:#sdfootnote24sym||name="sdfootnote24anc"]]^^.
	236	+
226	226	Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
227	227
228	228	If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
229	229
230		-Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
	241	+^^27^^ Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
231	231
232	232	The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation):
233	233
...	...	@@ -249,16 +249,19 @@
249	249
250	250	The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
251	251
252		-(% style="width:769.294px" %)
253		-|(% style="width:401px" %)**SDMX**|(% style="width:366px" %)**VTL**
254		-|(% style="width:401px" %)Dimension|(% style="width:366px" %)(Simple) Identifier
255		-|(% style="width:401px" %)TimeDimension|(% style="width:366px" %)(Time) Identifier
256		-|(% style="width:401px" %)MeasureDimension & one Measure|(% style="width:366px" %)(((
257		-One Measure for each Code of the SDMX MeasureDimension
	263	+|**SDMX**|**VTL**
	264	+|Dimension|(Simple) Identifier
	265	+|TimeDimension|(Time) Identifier
	266	+|MeasureDimension & one Measure|(((
	267	+One Measure for each Code of the
	268	+
	269	+SDMX MeasureDimension
258	258	)))
259		-|(% style="width:401px" %)DataAttribute not depending on the MeasureDimension|(% style="width:366px" %)Attribute
260		-|(% style="width:401px" %)DataAttribute depending on the MeasureDimension|(% style="width:366px" %)(((
261		-One Attribute for each Code of the SDMX MeasureDimension
	271	+|DataAttribute not depending on the MeasureDimension|Attribute
	272	+|DataAttribute depending on the MeasureDimension|(((
	273	+One Attribute for each Code of the
	274	+
	275	+SDMX MeasureDimension
262	262	)))
263	263
264	264	Using this mapping method, the components of the data structure can change in the conversion from SDMX to VTL and it must be taken into account that the VTL statements can reference only the components of the resulting VTL data structure.
...	...	@@ -273,7 +273,7 @@
273	273	* 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
274	274	* 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
275	275
276		-==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
	290	+**12.3.3.3 From SDMX DataAttributes to VTL Measures**
277	277
278	278	* 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
279	279
...	...	@@ -285,7 +285,7 @@
285	285
286	286	=== 12.3.4 Mapping from VTL to SDMX data structures ===
287	287
288		-==== 12.3.4.1 Basic Mapping ====
	302	+**12.3.4.1 Basic Mapping**
289	289
290	290	The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
291	291
...	...	@@ -295,12 +295,11 @@
295	295
296	296	Mapping table:
297	297
298		-(% style="width:667.294px" %)
299		-|(% style="width:272px" %)**VTL**|(% style="width:392px" %)**SDMX**
300		-|(% style="width:272px" %)(Simple) Identifier|(% style="width:392px" %)Dimension
301		-|(% style="width:272px" %)(Time) Identifier|(% style="width:392px" %)TimeDimension
302		-|(% style="width:272px" %)Measure|(% style="width:392px" %)Measure
303		-|(% style="width:272px" %)Attribute|(% style="width:392px" %)DataAttribute
	312	+|**VTL**|**SDMX**
	313	+|(Simple) Identifier|Dimension
	314	+|(Time) Identifier|TimeDimension
	315	+|Measure|Measure
	316	+|Attribute|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 ====
	326	+**12.3.4.2 Unpivot Mapping**
314	314
315	315	An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
316	316
...	...	@@ -334,12 +334,11 @@
334	334
335	335	The summary mapping table of the **unpivot** mapping method is the following:
336	336
337		-(% style="width:994.294px" %)
338		-|(% style="width:306px" %)**VTL**|(% style="width:684px" %)**SDMX**
339		-|(% style="width:306px" %)(Simple) Identifier|(% style="width:684px" %)Dimension
340		-|(% style="width:306px" %)(Time) Identifier|(% style="width:684px" %)TimeDimension
341		-|(% style="width:306px" %)All Measure Components|(% style="width:684px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
342		-|(% style="width:306px" %)Attribute|(% style="width:684px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
	350	+|**VTL**|**SDMX**
	351	+|(Simple) Identifier|Dimension
	352	+|(Time) Identifier|TimeDimension
	353	+|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
	354	+|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
343	343
344	344	At observation / data point level:
345	345
...	...	@@ -353,7 +353,7 @@
353	353
354	354	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.
355	355
356		-==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ====
	368	+**12.3.4.3 From VTL Measures to SDMX Data Attributes**
357	357
358	358	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”).
359	359
...	...	@@ -361,13 +361,12 @@
361	361
362	362	The mapping table is the following:
363	363
364		-(% style="width:689.294px" %)
365		-|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX
366		-|(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension
367		-|(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension
368		-|(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure
369		-|(% style="width:344px" %)Other Measures|(% style="width:341px" %)DataAttribute
370		-|(% style="width:344px" %)Attribute|(% style="width:341px" %)DataAttribute
	376	+|VTL|SDMX
	377	+|(Simple) Identifier|Dimension
	378	+|(Time) Identifier|TimeDimension
	379	+|Some Measures|Measure
	380	+|Other Measures|DataAttribute
	381	+|Attribute|DataAttribute
371	371
372	372	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.
373	373
...	...	@@ -385,20 +385,20 @@
385	385
386	386	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).
387	387
388		-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}}
	399	+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.^^[[^^25^^>>path:#sdfootnote25sym||name="sdfootnote25anc"]]^^
389	389
390		-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}}
	401	+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.^^[[^^26^^>>path:#sdfootnote26sym||name="sdfootnote26anc"]]^^
391	391
392	392	Given a SDMX Dataflow and some predefined Dimensions of its DataStructure, it is allowed to map the subsets of observations that have the same combination of values for such Dimensions to correspondent VTL datasets.
393	393
394	394	For example, assuming that the SDMX Dataflow DF1(1.0.0) has the Dimensions INDICATOR, TIME_PERIOD and COUNTRY, and that the user declares the Dimensions INDICATOR and COUNTRY as basis for the mapping (i.e. the mapping dimensions): the observations that have the same values for INDICATOR and COUNTRY would be mapped to the same VTL dataset (and vice-versa). In practice, this kind mapping is obtained like follows:
395	395
396		-* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order.{{footnote}}This definition is made through the ToVtlSubspace and ToVtlSpaceKey classes and/or the FromVtlSuperspace and FromVtlSpaceKey classes, depending on the direction of the mapping (“key” means “dimension”). The mapping of Dataflow subsets can be applied independently in the two directions, also according to different Dimensions. When no Dimension is declared for a given direction, it is assumed that the option of mapping different parts of a SDMX Dataflow to different VTL Data Sets is not used.{{/footnote}} Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.
	407	+* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order.^^[[^^27^^>>path:#sdfootnote27sym||name="sdfootnote27anc"]]^^ Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.
397	397	* The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts:
398	398	** The reference to the SDMX Dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated URN or another alias); for example DF(1.0.0);
399		-** a slash (“/”) as a separator;{{footnote}}As a consequence of this formalism, a slash in the name of the VTL Data Set assumes the specific meaning of separator between the name of the Dataflow and the values of some of its Dimensions.{{/footnote}}
	410	+** a slash (“/”) as a separator; ^^[[^^28^^>>path:#sdfootnote28sym||name="sdfootnote28anc"]]^^
400	400
401		-The reference to a specific part of the SDMX Dataflow above, expressed as the concatenation of the values that the SDMX DimensionComponents declared above must have, separated by dots (“.”) and written in the order in which these DimensionComponents are defined{{footnote}}This is the order in which the dimensions are defined in the ToVtlSpaceKey class or in the FromVtlSpaceKey class, depending on the direction of the mapping.{{/footnote}}. For example POPULATION.USA would mean that such a VTL Data Set is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.
	412	+The reference to a specific part of the SDMX Dataflow above, expressed as the concatenation of the values that the SDMX DimensionComponents declared above must have, separated by dots (“.”) and written in the order in which these DimensionComponents are defined^^[[^^29^^>>path:#sdfootnote29sym||name="sdfootnote29anc"]]^^. For example POPULATION.USA would mean that such a VTL Data Set is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.
402	402
403	403	In the VTL Transformations, this kind of dataset name must be referenced between single quotes because the slash (“/”) is not a regular character according to the VTL rules.
404	404
...	...	@@ -414,15 +414,15 @@
414	414
415	415	Let us now analyse the different meaning of this kind of mapping in the two mapping directions, i.e. from SDMX to VTL and from VTL to SDMX.
416	416
417		-As already said, the mapping from SDMX to VTL happens when the SDMX dataflows are operand of VTL Transformations, instead the mapping from VTL to SDMX happens when the VTL Data Sets that is result of Transformations{{footnote}}It should be remembered that, according to the VTL consistency rules, a given VTL dataset cannot be the result of more than one VTL Transformation.{{/footnote}} need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively.
	428	+As already said, the mapping from SDMX to VTL happens when the SDMX dataflows are operand of VTL Transformations, instead the mapping from VTL to SDMX happens when the VTL Data Sets that is result of Transformations^^[[^^30^^>>path:#sdfootnote30sym||name="sdfootnote30anc"]]^^ need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively.
418	418
419	419	First, let us see what happens in the __mapping direction from SDMX to VTL__, i.e. when parts of a SDMX Dataflow (e.g. DF1(1.0.0)) need to be mapped to distinct VTL Data Sets that are operand of some VTL Transformations.
420	420
421	421	As already said, each VTL Data Set is assumed to contain all the observations of the
422	422
423		-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.
	434	+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.
424	424
425		-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.
	436	+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^^[[^^31^^>>path:#sdfootnote31sym||name="sdfootnote31anc"]]^^. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
426	426
427	427	basic, pivot …).
428	428
...	...	@@ -442,7 +442,7 @@
442	442
443	443	… … …
444	444
445		-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}}
	456	+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. ^^[[^^32^^>>path:#sdfootnote32sym||name="sdfootnote32anc"]]^^
446	446
447	447	In the direction from SDMX to VTL it is allowed to omit the value of one or more
448	448
...	...	@@ -470,12 +470,12 @@
470	470
471	471	Dataflow DF2(1.0.0) having the Dimensions TIME_PERIOD, INDICATOR, and COUNTRY and that such a programmer finds it convenient to calculate separately the parts of DF2(1.0.0) that have different combinations of values for INDICATOR and COUNTRY:
472	472
473		-* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation;{{footnote}}If the whole DF2(1.0) is calculated by means of just one VTL Transformation, then the mapping between the SDMX Dataflow and the corresponding VTL dataset is one-to-one and this kind of mapping (one SDMX Dataflow to many VTL datasets) does not apply.{{/footnote}}
474		-* the data structure of all these VTL Data Sets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.{{footnote}}This is possible as each VTL dataset corresponds to one particular combination of values of INDICATOR and COUNTRY.{{/footnote}}
	484	+* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation; ^^[[^^33^^>>path:#sdfootnote33sym||name="sdfootnote33anc"]]^^
	485	+* the data structure of all these VTL Data Sets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.^^[[^^34^^>>path:#sdfootnote34sym||name="sdfootnote34anc"]]^^
475	475
476		-Under these hypothesis, such derived VTL Data Sets can be mapped to DF2(1.0.0) by declaring the DimensionComponents INDICATOR and COUNTRY as mapping dimensions{{footnote}}The mapping dimensions are defined as FromVtlSpaceKeys of the FromVtlSuperSpace of the VtlDataflowMapping relevant to DF2(1.0).{{/footnote}}.
	487	+Under these hypothesis, such derived VTL Data Sets can be mapped to DF2(1.0.0) by declaring the DimensionComponents INDICATOR and COUNTRY as mapping dimensions^^[[^^35^^>>path:#sdfootnote35sym||name="sdfootnote35anc"]]^^.
477	477
478		-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}}
	489	+The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:^^ [[^^36^^>>path:#sdfootnote36sym||name="sdfootnote36anc"]]^^
479	479
480	480	‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
481	481
...	...	@@ -531,9 +531,9 @@
531	531
532	532	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
533	533
534		-DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{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.
	545	+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)^^[[^^37^^>>path:#sdfootnote37sym||name="sdfootnote37anc"]]^^, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
535	535
536		-Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets.{{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}}
	547	+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. ^^[[^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]][[^^39^^>>path:#sdfootnote39sym||name="sdfootnote39anc"]]^^
537	537
538	538	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).
539	539
...	...	@@ -541,51 +541,52 @@
541	541
542	542	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
543	543
544		-(% style="width:1170.29px" %)
545		-|**VTL**|(% style="width:754px" %)**SDMX**
546		-|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
547		-|**Represented Variable**|(% style="width:754px" %)(((
	555	+|VTL|SDMX
	556	+|**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^^
	557	+|**Represented Variable**|(((
548	548	**Concept** with a definite
549	549
550	550	Representation
551	551	)))
552		-|**Value Domain**|(% style="width:754px" %)(((
	562	+|**Value Domain**|(((
553	553	**Representation** (see the Structure
554	554
555	555	Pattern in the Base Package)
556	556	)))
557		-|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
558		-|**Code**|(% style="width:754px" %)(((
	567	+|**Enumerated Value Domain / Code List**|**Codelist**
	568	+|**Code**|(((
559	559	**Code** (for enumerated
560	560
561	561	DimensionComponent, Measure, DataAttribute)
562	562	)))
563		-|**Described Value Domain**|(% style="width:754px" %)(((
564		-non-enumerated** Representation**
	573	+|**Described Value Domain**|(((
	574	+non-enumerated** &nbsp;&nbsp;&nbsp;Representation**
565	565
566	566	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
567	567	)))
568		-|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
569		-| |(% style="width:754px" %)(((
570		-to a valid **value **(for non-enumerated** **Representations)
	578	+|**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
	579	+||(((
	580	+to a valid **value &nbsp;&nbsp;&nbsp;**(for non-enumerated** &nbsp;&nbsp;&nbsp;**
	581	+
	582	+Representations)
571	571	)))
572		-|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
573		-|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
574		-|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
575		-|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
	584	+|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
	585	+|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
	586	+|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
	587	+|**Set list**|This abstraction does not exist in SDMX
576	576
577	577	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).
578	578
579		-Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear{{footnote}}By using represented variables, VTL can assume that data structures having the same variables as identifiers can be composed one another because the correspondent values can match.{{/footnote}}, while the SDMX Concepts can have different Representations in different DataStructures.{{footnote}}A Concept becomes a Component in a DataStructureDefinition, and Components can have different LocalRepresentations in different DataStructureDefinitions, also overriding the (possible) base representation of the Concept.{{/footnote}} This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
	591	+Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear^^[[^^40^^>>path:#sdfootnote40sym||name="sdfootnote40anc"]]^^, while the SDMX Concepts can have different Representations in different DataStructures.^^[[^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]]^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
580	580
581	581	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
582	582
583		-DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
	595	+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.
584	584
585		-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.
586		-
587	587	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
588	588
	599	+[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape5" height="1" width="192"]]
	600	+
589	589	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
590	590
591	591	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.
...	...	@@ -600,8 +600,7 @@
600	600
601	601	[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
602	602
603		-(% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
604		-**Figure 22 – VTL Data Types**
	615	+==== Figure 22 – VTL Data Types ====
605	605
606	606	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.
607	607
...	...	@@ -608,12 +608,131 @@
608	608	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):
609	609
610	610
611		-**Figure 23 – VTL Basic Scalar Types**
612	612
613	613	(((
614		-
	624	+//n//
	625	+
	626	+//a//
	627	+
	628	+//e//
	629	+
	630	+//l//
	631	+
	632	+//o//
	633	+
	634	+//o//
	635	+
	636	+//B//
	637	+
	638	+//n//
	639	+
	640	+//o//
	641	+
	642	+//i//
	643	+
	644	+//t//
	645	+
	646	+//a//
	647	+
	648	+//r//
	649	+
	650	+//u//
	651	+
	652	+//D//
	653	+
	654	+//d//
	655	+
	656	+//o//
	657	+
	658	+//i//
	659	+
	660	+//r//
	661	+
	662	+//e//
	663	+
	664	+//p//
	665	+
	666	+//_//
	667	+
	668	+//e//
	669	+
	670	+//m//
	671	+
	672	+//i//
	673	+
	674	+//T//
	675	+
	676	+//e//
	677	+
	678	+//t//
	679	+
	680	+//a//
	681	+
	682	+//D//
	683	+
	684	+//e//
	685	+
	686	+//m//
	687	+
	688	+//i//
	689	+
	690	+//T//
	691	+
	692	+//r//
	693	+
	694	+//e//
	695	+
	696	+//g//
	697	+
	698	+//e//
	699	+
	700	+//t//
	701	+
	702	+//n//
	703	+
	704	+//I//
	705	+
	706	+//r//
	707	+
	708	+//e//
	709	+
	710	+//b//
	711	+
	712	+//m//
	713	+
	714	+//u//
	715	+
	716	+//N//
	717	+
	718	+//g//
	719	+
	720	+//n//
	721	+
	722	+//i//
	723	+
	724	+//r//
	725	+
	726	+//t//
	727	+
	728	+//S//
	729	+
	730	+//r//
	731	+
	732	+//a//
	733	+
	734	+//l//
	735	+
	736	+//a//
	737	+
	738	+//c//
	739	+
	740	+//S//
	741	+
	742	+[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_82d45833.gif||alt="Shape6" height="231" width="184"]]
615	615	)))
616	616
	745	+==== Figure 23 – VTL Basic Scalar Types ====
	746	+
617	617	=== 12.4.2 VTL basic scalar types and SDMX data types ===
618	618
619	619	The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
...	...	@@ -700,37 +700,37 @@
700	700	binary-valued logic: {true, false})
701	701	)))|boolean
702	702
703		-| |(% colspan="2" %)(((
	833	+||(% colspan="2" %)(((
704	704	URI
705	705
706	706	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
707	707	)))|(% colspan="2" %)string
708		-| |(% colspan="2" %)(((
	838	+||(% colspan="2" %)(((
709	709	Count
710	710
711	711	(an integer following a sequential pattern, increasing by 1 for each occurrence)
712	712	)))|(% colspan="2" %)integer
713		-| |(% colspan="2" %)(((
	843	+||(% colspan="2" %)(((
714	714	InclusiveValueRange
715	715
716	716	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
717	717	)))|(% colspan="2" %)number
718		-| |(% colspan="2" %)(((
	848	+||(% colspan="2" %)(((
719	719	ExclusiveValueRange
720	720
721	721	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
722	722	)))|(% colspan="2" %)number
723		-| |(% colspan="2" %)(((
	853	+||(% colspan="2" %)(((
724	724	Incremental
725	725
726	726	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
727	727	)))|(% colspan="2" %)number
728		-| |(% colspan="2" %)(((
	858	+||(% colspan="2" %)(((
729	729	ObservationalTimePeriod
730	730
731	731	(superset of StandardTimePeriod and TimeRange)
732	732	)))|(% colspan="2" %)time
733		-| |(% colspan="2" %)(((
	863	+||(% colspan="2" %)(((
734	734	StandardTimePeriod
735	735
736	736	(superset of BasicTimePeriod and
...	...	@@ -737,20 +737,20 @@
737	737
738	738	ReportingTimePeriod)
739	739	)))|(% colspan="2" %)time
740		-| |(% colspan="2" %)(((
	870	+||(% colspan="2" %)(((
741	741	BasicTimePeriod
742	742
743	743	(superset of GregorianTimePeriod and DateTime)
744	744	)))|(% colspan="2" %)date
745		-| |(% colspan="2" %)(((
	875	+||(% colspan="2" %)(((
746	746	GregorianTimePeriod
747	747
748	748	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
749	749	)))|(% colspan="2" %)date
750		-| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
751		-| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
752		-| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
753		-| |(% colspan="2" %)(((
	880	+||(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
	881	+||(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
	882	+||(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
	883	+||(% colspan="2" %)(((
754	754	ReportingTimePeriod
755	755
756	756	(superset of RepostingYear, ReportingSemester,
...	...	@@ -759,79 +759,79 @@
759	759
760	760	ReportingMonth, ReportingWeek, ReportingDay)
761	761	)))|(% colspan="2" %)time_period
762		-| |(% colspan="2" %)(((
	892	+||(% colspan="2" %)(((
763	763	ReportingYear
764	764
765	765	(YYYY-A1 – 1 year period)
766	766	)))|(% colspan="2" %)time_period
767		-| |(% colspan="2" %)(((
	897	+||(% colspan="2" %)(((
768	768	ReportingSemester
769	769
770	770	(YYYY-Ss – 6 month period)
771	771	)))|(% colspan="2" %)time_period
772		-| |(% colspan="2" %)(((
	902	+||(% colspan="2" %)(((
773	773	ReportingTrimester
774	774
775	775	(YYYY-Tt – 4 month period)
776	776	)))|(% colspan="2" %)time_period
777		-| |(% colspan="2" %)(((
	907	+||(% colspan="2" %)(((
778	778	ReportingQuarter
779	779
780	780	(YYYY-Qq – 3 month period)
781	781	)))|(% colspan="2" %)time_period
782		-| |(% colspan="2" %)(((
	912	+||(% colspan="2" %)(((
783	783	ReportingMonth
784	784
785	785	(YYYY-Mmm – 1 month period)
786	786	)))|(% colspan="2" %)time_period
787		-| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
788		-| |(% colspan="2" %) |(% colspan="2" %)
789		-| |(% colspan="2" %) |(% colspan="2" %)
790		-|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) |
	917	+||(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
	918	+||(% colspan="2" %)|(% colspan="2" %)
	919	+||(% colspan="2" %)|(% colspan="2" %)
	920	+|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %)|
791	791	|(% colspan="2" %)(((
792	792	ReportingDay
793	793
794	794	(YYYY-Dddd – 1 day period)
795		-)))|(% colspan="2" %)time_period|
	925	+)))|(% colspan="2" %)time_period|
796	796	|(% colspan="2" %)(((
797	797	DateTime
798	798
799	799	(YYYY-MM-DDThh:mm:ss)
800		-)))|(% colspan="2" %)date|
	930	+)))|(% colspan="2" %)date|
801	801	|(% colspan="2" %)(((
802	802	TimeRange
803	803
804	804	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
805		-)))|(% colspan="2" %)time|
	935	+)))|(% colspan="2" %)time|
806	806	|(% colspan="2" %)(((
807	807	Month
808	808
809	809	(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
810		-)))|(% colspan="2" %)string|
	940	+)))|(% colspan="2" %)string|
811	811	|(% colspan="2" %)(((
812	812	MonthDay
813	813
814	814	(~-~-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)
815		-)))|(% colspan="2" %)string|
	945	+)))|(% colspan="2" %)string|
816	816	|(% colspan="2" %)(((
817	817	Day
818	818
819	819	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
820		-)))|(% colspan="2" %)string|
	950	+)))|(% colspan="2" %)string|
821	821	|(% colspan="2" %)(((
822	822	Time
823	823
824	824	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
825		-)))|(% colspan="2" %)string|
	955	+)))|(% colspan="2" %)string|
826	826	|(% colspan="2" %)(((
827	827	Duration
828	828
829	829	(corresponds to XML Schema xs:duration datatype)
830		-)))|(% colspan="2" %)duration|
831		-|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
832		-|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
833		-|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
834		-|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
	960	+)))|(% colspan="2" %)duration|
	961	+|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
	962	+|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
	963	+|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
	964	+|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
835	835
836	836	==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
837	837
...	...	@@ -880,13 +880,13 @@
880	880	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.
881	881
882	882	|(% colspan="2" %)VTL special characters for the formatting masks
883		-|(% colspan="2" %)
	1013	+|(% colspan="2" %)
884	884	|(% colspan="2" %)Number
885	885	|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
886	886	|E|one numeric digit (for the exponent of the scientific notation)
887	887	|. (dot)|possible separator between the integer and the decimal parts.
888	888	|, (comma)|possible separator between the integer and the decimal parts.
889		-| |
	1019	+||
890	890	|(% colspan="2" %)Time and duration
891	891	|C|century
892	892	|Y|year
...	...	@@ -908,17 +908,17 @@
908	908	|Day|lowercase textual representation of the month (e.g., monday)
909	909	|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
910	910	|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
911		-| |
	1041	+||
912	912	|(% colspan="2" %)String
913	913	|X|any string character
914	914	|Z|any string character from "A" to "z"
915	915	|9|any string character from "0" to "9"
916		-| |
	1046	+||
917	917	|(% colspan="2" %)Boolean
918	918	|B|Boolean using "true" for True and "false" for False
919	919	|1|Boolean using "1" for True and "0" for False
920	920	|0|Boolean using "0" for True and "1" for False
921		-| |
	1051	+||
922	922	|(% colspan="2" %)Other qualifiers
923	923	|*|an arbitrary number of digits (of the preceding type)
924	924	|+|at least one digit (of the preceding type)
...	...	@@ -925,9 +925,9 @@
925	925	|( )|optional digits (specified within the brackets)
926	926	|\|prefix for the special characters that must appear in the mask
927	927	|N|fixed number of digits used in the preceding textual representation of the month or the day
928		-| |
	1058	+||
929	929
930		-The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
	1060	+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^^[[^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]]^^.
931	931
932	932	=== 12.4.5 Null Values ===
933	933
...	...	@@ -950,5 +950,3 @@
950	950	TransformationScheme.
951	951
952	952	In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
953		-
954		-{{putFootnotes/}}

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1		-70.5 KB

Content