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1 -= 12 Validation and Transformation Language (VTL) =
1 +{{box title="**Contents**"}}
2 +{{toc/}}
3 +{{/box}}
2 2  
3 3  == 12.1 Introduction ==
4 4  
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:
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:
6 6  
7 7  * definition of validation and transformation algorithms, in order to specify how to calculate new data from existing ones;
8 8  * 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);
... ... @@ -10,7 +10,7 @@
10 10  
11 11  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").
12 12  
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).
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).
14 14  
15 15  The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of
16 16  
... ... @@ -28,7 +28,7 @@
28 28  
29 29  In any case, the aliases used in the VTL Transformations have to be mapped to the
30 30  
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.
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.
32 32  
33 33  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.
34 34  
... ... @@ -38,7 +38,7 @@
38 38  
39 39  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.
40 40  
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:
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:
42 42  
43 43  * SDMXprefix
44 44  * SDMX-IM-package-name
... ... @@ -46,15 +46,13 @@
46 46  * agency-id
47 47  * maintainedobject-id
48 48  * maintainedobject-version
49 -* container-object-id ^^[[^^10^^>>path:#sdfootnote10sym||name="sdfootnote10anc"]]^^
51 +* container-object-id{{footnote}}The container-object-id can repeat and may not be present.{{/footnote}}
50 50  * object-id
51 51  
52 52  The generic structure of the URN is the following:
53 53  
54 -SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id
56 +SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id (maintainedobject-version).*container-object-id.object-id
55 55  
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".
... ... @@ -63,13 +63,10 @@
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^^[[^^11^^>>path:#sdfootnote11sym||name="sdfootnote11anc"]]^^, 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{{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:
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
70 -
71 -DataStructure maintainable class, the maintainedobject-id is the name of the DataStructure (dataStructure-id) which the artefact belongs to;
72 -
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;
73 73  * 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;
74 74  * if the artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the Codelist name (codelist-id).
75 75  
... ... @@ -82,12 +82,10 @@
82 82  * 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 -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"]]^^:
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}}:
86 86  
87 87  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
88 -
89 89  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
90 -
91 91  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
92 92  
93 93  === 12.2.3 Abbreviation of the URN ===
... ... @@ -96,10 +96,10 @@
96 96  
97 97  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.
98 98  
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:
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:
100 100  ** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist.
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).
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).
103 103  * 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;
104 104  ** 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;
105 105  ** 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;
... ... @@ -112,9 +112,7 @@
112 112  For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
113 113  
114 114  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
115 -
116 116  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
117 -
118 118  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
119 119  
120 120  by omitting all the non-essential parts would become simply:
... ... @@ -121,11 +121,11 @@
121 121  
122 122  DFR := DF1 + DF2
123 123  
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"]]^^:
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}}:
125 125  
126 126  'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
127 127  
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^^:
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}}:
129 129  
130 130  CL_FREQ
131 131  
... ... @@ -139,7 +139,7 @@
139 139  
140 140  SECTOR
141 141  
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"]]^^:
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}}:
143 143  
144 144  'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
145 145  
... ... @@ -171,9 +171,9 @@
171 171  
172 172  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.
173 173  
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"]]^^.
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}}.
175 175  
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"]]^^
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}}
177 177  
178 178  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.
179 179  
... ... @@ -185,15 +185,15 @@
185 185  
186 186  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.
187 187  
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"]]^^.
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}}.
189 189  
190 190  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).
191 191  
192 192  === 12.3.2 General mapping of VTL and SDMX data structures ===
193 193  
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"]]^^.
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}}.
195 195  
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"]]^^
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}}
197 197  
198 198  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.
199 199  
... ... @@ -213,32 +213,28 @@
213 213  
214 214  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:
215 215  
216 -|**SDMX**|**VTL**
217 -|Dimension|(Simple) Identifier
218 -|TimeDimension|(Time) Identifier
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
219 219  
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 -
225 225  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).
226 226  
227 -With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point.
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.
228 228  
229 -**12.3.3.2 Pivot Mapping**
220 +==== 12.3.3.2 Pivot Mapping ====
230 230  
231 231  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.
232 232  
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
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}}.
234 234  
235 -MeasureDimensions considered as a joint variable^^[[^^24^^>>path:#sdfootnote24sym||name="sdfootnote24anc"]]^^.
236 -
237 237  Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
238 238  
239 239  If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
240 240  
241 -^^27^^ Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
230 +Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
242 242  
243 243  The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation):
244 244  
... ... @@ -260,19 +260,16 @@
260 260  
261 261  The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
262 262  
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
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
270 270  )))
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
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
276 276  )))
277 277  
278 278  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.
... ... @@ -287,7 +287,7 @@
287 287  * 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
288 288  * 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
289 289  
290 -**12.3.3.3 From SDMX DataAttributes to VTL Measures**
276 +==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
291 291  
292 292  * 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
293 293  
... ... @@ -299,7 +299,7 @@
299 299  
300 300  === 12.3.4 Mapping from VTL to SDMX data structures ===
301 301  
302 -**12.3.4.1 Basic Mapping**
288 +==== 12.3.4.1 Basic Mapping ====
303 303  
304 304  The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
305 305  
... ... @@ -309,11 +309,12 @@
309 309  
310 310  Mapping table:
311 311  
312 -|**VTL**|**SDMX**
313 -|(Simple) Identifier|Dimension
314 -|(Time) Identifier|TimeDimension
315 -|Measure|Measure
316 -|Attribute|DataAttribute
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
317 317  
318 318  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.
319 319  
... ... @@ -323,7 +323,7 @@
323 323  
324 324  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.
325 325  
326 -**12.3.4.2 Unpivot Mapping**
313 +==== 12.3.4.2 Unpivot Mapping ====
327 327  
328 328  An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
329 329  
... ... @@ -347,11 +347,12 @@
347 347  
348 348  The summary mapping table of the **unpivot** mapping method is the following:
349 349  
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
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
355 355  
356 356  At observation / data point level:
357 357  
... ... @@ -365,7 +365,7 @@
365 365  
366 366  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.
367 367  
368 -**12.3.4.3 From VTL Measures to SDMX Data Attributes**
356 +==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ====
369 369  
370 370  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”).
371 371  
... ... @@ -373,12 +373,13 @@
373 373  
374 374  The mapping table is the following:
375 375  
376 -|VTL|SDMX
377 -|(Simple) Identifier|Dimension
378 -|(Time) Identifier|TimeDimension
379 -|Some Measures|Measure
380 -|Other Measures|DataAttribute
381 -|Attribute|DataAttribute
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
382 382  
383 383  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.
384 384  
... ... @@ -396,20 +396,20 @@
396 396  
397 397  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).
398 398  
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"]]^^
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}}
400 400  
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"]]^^
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}}
402 402  
403 403  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.
404 404  
405 405  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:
406 406  
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.
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.
408 408  * The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts:
409 409  ** 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);
410 -** a slash (“/”) as a separator; ^^[[^^28^^>>path:#sdfootnote28sym||name="sdfootnote28anc"]]^^
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}}
411 411  
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.
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.
413 413  
414 414  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.
415 415  
... ... @@ -425,15 +425,15 @@
425 425  
426 426  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.
427 427  
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.
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.
429 429  
430 430  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.
431 431  
432 432  As already said, each VTL Data Set is assumed to contain all the observations of the
433 433  
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.
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.
435 435  
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.
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.
437 437  
438 438  basic, pivot …).
439 439  
... ... @@ -453,7 +453,7 @@
453 453  
454 454  … … …
455 455  
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"]]^^
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}}
457 457  
458 458  In the direction from SDMX to VTL it is allowed to omit the value of one or more
459 459  
... ... @@ -481,12 +481,12 @@
481 481  
482 482  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:
483 483  
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"]]^^
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}}
486 486  
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"]]^^.
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}}.
488 488  
489 -The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:^^ [[^^36^^>>path:#sdfootnote36sym||name="sdfootnote36anc"]]^^
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}}
490 490  
491 491  ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
492 492  
... ... @@ -542,9 +542,9 @@
542 542  
543 543  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
544 544  
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.
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.
546 546  
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"]]^^
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}}{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
548 548  
549 549  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).
550 550  
... ... @@ -552,43 +552,42 @@
552 552  
553 553  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
554 554  
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**|(((
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" %)(((
558 558  **Concept** with a definite
559 559  
560 560  Representation
561 561  )))
562 -|**Value Domain**|(((
552 +|**Value Domain**|(% style="width:754px" %)(((
563 563  **Representation** (see the Structure
564 564  
565 565  Pattern in the Base Package)
566 566  )))
567 -|**Enumerated Value Domain / Code List**|**Codelist**
568 -|**Code**|(((
557 +|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
558 +|**Code**|(% style="width:754px" %)(((
569 569  **Code** (for enumerated
570 570  
571 571  DimensionComponent, Measure, DataAttribute)
572 572  )))
573 -|**Described Value Domain**|(((
574 -non-enumerated** &nbsp;&nbsp;&nbsp;Representation**
563 +|**Described Value Domain**|(% style="width:754px" %)(((
564 +non-enumerated** Representation**
575 575  
576 576  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
577 577  )))
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)
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)
583 583  )))
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
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
588 588  
589 589  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).
590 590  
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.
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^^[[(% 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" %)^^40^^>>path:#sdfootnote40sym||name="sdfootnote40anc"]](%%)^^, while the SDMX Concepts can have different Representations in different DataStructures.^^[[(% 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" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
592 592  
593 593  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
594 594  
... ... @@ -830,37 +830,37 @@
830 830  binary-valued logic: {true, false})
831 831  )))|boolean
832 832  
833 -||(% colspan="2" %)(((
821 +| |(% colspan="2" %)(((
834 834  URI
835 835  
836 836  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
837 837  )))|(% colspan="2" %)string
838 -||(% colspan="2" %)(((
826 +| |(% colspan="2" %)(((
839 839  Count
840 840  
841 841  (an integer following a sequential pattern, increasing by 1 for each occurrence)
842 842  )))|(% colspan="2" %)integer
843 -||(% colspan="2" %)(((
831 +| |(% colspan="2" %)(((
844 844  InclusiveValueRange
845 845  
846 846  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
847 847  )))|(% colspan="2" %)number
848 -||(% colspan="2" %)(((
836 +| |(% colspan="2" %)(((
849 849  ExclusiveValueRange
850 850  
851 851  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
852 852  )))|(% colspan="2" %)number
853 -||(% colspan="2" %)(((
841 +| |(% colspan="2" %)(((
854 854  Incremental
855 855  
856 856  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
857 857  )))|(% colspan="2" %)number
858 -||(% colspan="2" %)(((
846 +| |(% colspan="2" %)(((
859 859  ObservationalTimePeriod
860 860  
861 861  (superset of StandardTimePeriod and TimeRange)
862 862  )))|(% colspan="2" %)time
863 -||(% colspan="2" %)(((
851 +| |(% colspan="2" %)(((
864 864  StandardTimePeriod
865 865  
866 866  (superset of BasicTimePeriod and
... ... @@ -867,20 +867,20 @@
867 867  
868 868  ReportingTimePeriod)
869 869  )))|(% colspan="2" %)time
870 -||(% colspan="2" %)(((
858 +| |(% colspan="2" %)(((
871 871  BasicTimePeriod
872 872  
873 873  (superset of GregorianTimePeriod and DateTime)
874 874  )))|(% colspan="2" %)date
875 -||(% colspan="2" %)(((
863 +| |(% colspan="2" %)(((
876 876  GregorianTimePeriod
877 877  
878 878  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
879 879  )))|(% colspan="2" %)date
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" %)(((
868 +| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
869 +| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
870 +| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
871 +| |(% colspan="2" %)(((
884 884  ReportingTimePeriod
885 885  
886 886  (superset of RepostingYear, ReportingSemester,
... ... @@ -889,79 +889,79 @@
889 889  
890 890  ReportingMonth, ReportingWeek, ReportingDay)
891 891  )))|(% colspan="2" %)time_period
892 -||(% colspan="2" %)(((
880 +| |(% colspan="2" %)(((
893 893  ReportingYear
894 894  
895 895  (YYYY-A1 – 1 year period)
896 896  )))|(% colspan="2" %)time_period
897 -||(% colspan="2" %)(((
885 +| |(% colspan="2" %)(((
898 898  ReportingSemester
899 899  
900 900  (YYYY-Ss – 6 month period)
901 901  )))|(% colspan="2" %)time_period
902 -||(% colspan="2" %)(((
890 +| |(% colspan="2" %)(((
903 903  ReportingTrimester
904 904  
905 905  (YYYY-Tt – 4 month period)
906 906  )))|(% colspan="2" %)time_period
907 -||(% colspan="2" %)(((
895 +| |(% colspan="2" %)(((
908 908  ReportingQuarter
909 909  
910 910  (YYYY-Qq – 3 month period)
911 911  )))|(% colspan="2" %)time_period
912 -||(% colspan="2" %)(((
900 +| |(% colspan="2" %)(((
913 913  ReportingMonth
914 914  
915 915  (YYYY-Mmm – 1 month period)
916 916  )))|(% colspan="2" %)time_period
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" %)|
905 +| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
906 +| |(% colspan="2" %) |(% colspan="2" %)
907 +| |(% colspan="2" %) |(% colspan="2" %)
908 +|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) |
921 921  |(% colspan="2" %)(((
922 922  ReportingDay
923 923  
924 924  (YYYY-Dddd – 1 day period)
925 -)))|(% colspan="2" %)time_period|
913 +)))|(% colspan="2" %)time_period|
926 926  |(% colspan="2" %)(((
927 927  DateTime
928 928  
929 929  (YYYY-MM-DDThh:mm:ss)
930 -)))|(% colspan="2" %)date|
918 +)))|(% colspan="2" %)date|
931 931  |(% colspan="2" %)(((
932 932  TimeRange
933 933  
934 934  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
935 -)))|(% colspan="2" %)time|
923 +)))|(% colspan="2" %)time|
936 936  |(% colspan="2" %)(((
937 937  Month
938 938  
939 939  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
940 -)))|(% colspan="2" %)string|
928 +)))|(% colspan="2" %)string|
941 941  |(% colspan="2" %)(((
942 942  MonthDay
943 943  
944 944  (~-~-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)
945 -)))|(% colspan="2" %)string|
933 +)))|(% colspan="2" %)string|
946 946  |(% colspan="2" %)(((
947 947  Day
948 948  
949 949  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
950 -)))|(% colspan="2" %)string|
938 +)))|(% colspan="2" %)string|
951 951  |(% colspan="2" %)(((
952 952  Time
953 953  
954 954  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
955 -)))|(% colspan="2" %)string|
943 +)))|(% colspan="2" %)string|
956 956  |(% colspan="2" %)(((
957 957  Duration
958 958  
959 959  (corresponds to XML Schema xs:duration datatype)
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|
948 +)))|(% colspan="2" %)duration|
949 +|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
950 +|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
951 +|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
952 +|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
965 965  
966 966  ==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
967 967  
... ... @@ -1010,13 +1010,13 @@
1010 1010  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.
1011 1011  
1012 1012  |(% colspan="2" %)VTL special characters for the formatting masks
1013 -|(% colspan="2" %)
1001 +|(% colspan="2" %)
1014 1014  |(% colspan="2" %)Number
1015 1015  |D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
1016 1016  |E|one numeric digit (for the exponent of the scientific notation)
1017 1017  |. (dot)|possible separator between the integer and the decimal parts.
1018 1018  |, (comma)|possible separator between the integer and the decimal parts.
1019 -||
1007 +| |
1020 1020  |(% colspan="2" %)Time and duration
1021 1021  |C|century
1022 1022  |Y|year
... ... @@ -1038,17 +1038,17 @@
1038 1038  |Day|lowercase textual representation of the month (e.g., monday)
1039 1039  |Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
1040 1040  |Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
1041 -||
1029 +| |
1042 1042  |(% colspan="2" %)String
1043 1043  |X|any string character
1044 1044  |Z|any string character from "A" to "z"
1045 1045  |9|any string character from "0" to "9"
1046 -||
1034 +| |
1047 1047  |(% colspan="2" %)Boolean
1048 1048  |B|Boolean using "true" for True and "false" for False
1049 1049  |1|Boolean using "1" for True and "0" for False
1050 1050  |0|Boolean using "0" for True and "1" for False
1051 -||
1039 +| |
1052 1052  |(% colspan="2" %)Other qualifiers
1053 1053  |*|an arbitrary number of digits (of the preceding type)
1054 1054  |+|at least one digit (of the preceding type)
... ... @@ -1055,9 +1055,9 @@
1055 1055  |( )|optional digits (specified within the brackets)
1056 1056  |\|prefix for the special characters that must appear in the mask
1057 1057  |N|fixed number of digits used in the preceding textual representation of the month or the day
1058 -||
1046 +| |
1059 1059  
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"]]^^.
1048 +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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
1061 1061  
1062 1062  === 12.4.5 Null Values ===
1063 1063  
... ... @@ -1080,3 +1080,5 @@
1080 1080  TransformationScheme.
1081 1081  
1082 1082  In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
1071 +
1072 +{{putFootnotes/}}
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