Changes for page 12 Validation and Transformation Language (VTL)
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... ... @@ -2,10 +2,9 @@ 2 2 {{toc/}} 3 3 {{/box}} 4 4 5 -1. 6 -11. Introduction 5 +== 12.1 Introduction == 7 7 8 -The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[1~]^^>>path:#_ftn1]](%%). 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: 9 9 10 10 * definition of validation and transformation algorithms, in order to specify how to calculate new data from existing ones; 11 11 * 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); ... ... @@ -13,33 +13,31 @@ 13 13 14 14 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"). 15 15 16 -The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[2~]^^>>path:#_ftn2]](%%). 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). 17 17 18 18 The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result. 19 19 20 20 This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts. 21 21 22 -1. 23 -11. References to SDMX artefacts from VTL statements 24 -111. Introduction 21 +== 12.2 References to SDMX artefacts from VTL statements == 25 25 23 +=== 12.2.1 Introduction === 24 + 26 26 The VTL can manipulate SDMX artefacts (or objects) by referencing them through predefined conventional names (aliases). 27 27 28 28 The alias of an SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name. 29 29 30 -In any case, the aliases used in the VTL Transformations have to be mapped to the 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 [[(%class="wikiinternallink wikiinternallinkwikiinternallink"%)^^~[3~]^^>>path:#_ftn3]](%%)or User Defined Operators[[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[4~]^^>>path:#_ftn4]](%%)to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.29 +In any case, the aliases used in the VTL Transformations have to be mapped to the 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 31 32 32 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. 33 33 34 34 The references through the URN and the abbreviated URN are described in the following paragraphs. 35 35 36 -1. 37 -11. 38 -111. References through the URN 35 +=== 12.2.2 References through the URN === 39 39 40 40 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. 41 41 42 -The SDMX URN [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[5~]^^>>path:#_ftn5]](%%) is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:39 +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}}(% style="font-size:12px" %) (%%)is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis: 43 43 44 44 * SDMXprefix 45 45 * SDMX-IM-package-name ... ... @@ -47,15 +47,13 @@ 47 47 * agency-id 48 48 * maintainedobject-id 49 49 * maintainedobject-version 50 -* container-object-id [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[6~]^^>>path:#_ftn6]]47 +* container-object-id{{footnote}}The container-object-id can repeat and may not be present.{{/footnote}} 51 51 * object-id 52 52 53 53 The generic structure of the URN is the following: 54 54 55 -SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id 52 +SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id (maintainedobject-version).*container-object-id.object-id 56 56 57 -(maintainedobject-version).*container-object-id.object-id 58 - 59 59 The **SDMXprefix** is "urn:sdmx:org", always the same for all SDMX artefacts. 60 60 61 61 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". ... ... @@ -64,7 +64,7 @@ 64 64 65 65 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). 66 66 67 -The maintainedobject-id is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable [[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[7~]^^>>path:#_ftn7]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:62 +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: 68 68 69 69 * if the artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the Dataflow name (dataflow-id); 70 70 * if the artefact is a Dimension, Measure, TimeDimension or DataAttribute, which are not maintainable and belong to the ... ... @@ -76,28 +76,21 @@ 76 76 77 77 The maintainedobject-version is the version, according to the SDMX versioning rules, of the maintained object which the artefact belongs to (for example, possible versions might be 1.0, 2.3, 1.0.0, 2.1.0 or 3.1.2). 78 78 79 -The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN 74 +The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN. 80 80 81 81 The object-id is the name of the non-maintainable artefact (when the artefact is maintainable its name is already specified as the maintainedobject-id, see above), in particular it has to be specified: 82 82 83 -* if the artefact is a Dimension, TimeDimension, Measure or 84 - 85 -DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components) 86 - 78 +* if the artefact is a Dimension, TimeDimension, Measure or DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components) 87 87 * if the artefact is a Concept (the object-id is the name of the Concept) 88 88 89 -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 [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[8~]^^>>path:#_ftn8]](%%):81 +For example, by using the URN, the VTL Transformation that sums two SDMX Dataflows DF1 and DF2 and assigns the result to a third persistent Dataflow DFR, assuming that DF1, DF2 and DFR are the maintainedobject-id of the three Dataflows, that their version is 1.0.0 and their Agency is AG, would be written as{{footnote}}Since these references to SDMX objects include non-permitted characters as per the VTL ID notation, they need to be included between single quotes, according to the VTL rules for irregular names.{{/footnote}}: 90 90 91 -'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <- 83 +> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <- 84 +> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' + 85 +> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 92 92 93 - 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)'+87 +=== 12.2.3 Abbreviation of the URN === 94 94 95 -'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 96 - 97 -1. 98 -11. 99 -111. Abbreviation of the URN 100 - 101 101 The complete formulation of the URN described above is exhaustive but verbose, even for very simple statements. In order to reduce the verbosity through a simplified identifier and make the work of transformation definers easier, proper abbreviations of the URN are possible. Using this approach, the referenced artefacts remain intelligible in the VTL code by a human reader. 102 102 103 103 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. ... ... @@ -104,15 +104,14 @@ 104 104 105 105 * 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. 106 106 * 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: 107 -** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist. 108 -* 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[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[9~]^^>>path:#_ftn9]](%%), the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section "Mapping between VTL and SDMX" hereinafter)[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[10~]^^>>path:#_ftn10]](%%). 109 -* 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[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[11~]^^>>path:#_ftn11]](%%). 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). 110 -* 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; 111 -** if the referenced artefact is a Dimension, TimeDimension, Measure, 112 - 113 -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; 114 - 115 -* 95 +** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, 96 +** "conceptscheme" for the class Concept, 97 +** "codelist" for the class Codelist. 98 +* 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}}. 99 +* 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). 100 +* As for the maintainedobject-id, this is essential in some cases while in other cases it can be omitted: 101 +** if the referenced artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the dataflow-id and obviously cannot be omitted; 102 +** 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; 116 116 ** 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; 117 117 ** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted. 118 118 * When the maintainedobject-id is omitted, the maintainedobject-version is omitted too. When the maintainedobject-id is not omitted and the maintainedobject-version is omitted, the version 1.0 is assumed by default. ... ... @@ -123,93 +123,83 @@ 123 123 124 124 For example, the full formulation that uses the complete URN shown at the end of the previous paragraph: 125 125 126 -'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' := 113 +> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' := 114 +> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' + 115 +> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 127 127 128 -'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' + 129 - 130 -'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 131 - 132 132 by omitting all the non-essential parts would become simply: 133 133 134 -DFR := DF1 + DF2 119 +> DFR : = DF1 + DF2 135 135 136 -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 [[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[12~]^^>>path:#_ftn12]](%%):121 +The references to the Codelists can be simplified similarly. For example, given the non-abbreviated reference to the Codelist AG:CL_FREQ(1.0.0), which is{{footnote}}Single quotes are needed because this reference is not a VTL regular name. 19 Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}: 137 137 138 -'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)' 123 +> 'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)' 139 139 140 140 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^^: 141 141 142 -CL_FREQ 127 +> CL_FREQ 143 143 144 144 As for the references to the components, it can be enough to specify the componentId, given that the dataStructure-Id can be omitted. An example of non-abbreviated reference, if the data structure is DST1 and the component is SECTOR, is the following: 145 145 146 -'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).S 131 +> 'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).S ECTOR' 147 147 148 -ECTOR' 149 - 150 150 The corresponding fully abbreviated reference, if made from a TransformationScheme belonging to AG, would become simply: 151 151 152 -SECTOR 135 +> SECTOR 153 153 154 -For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as [[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[13~]^^>>path:#_ftn13]](%%):137 +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}}: 155 155 156 -'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC] 139 +> 'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC] 157 157 158 158 In the references to the Concepts, which can exist for example in the definition of the VTL Rulesets, at least the conceptScheme-id and the concept-id must be specified. 159 159 160 160 An example of non-abbreviated reference, if the conceptScheme-id is CS1 and the concept-id is SECTOR, is the following: 161 161 162 -'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR' 145 +> 'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR' 163 163 164 164 The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply: 165 165 166 -CS1(1.0.0).SECTOR 149 +> CS1(1.0.0).SECTOR 167 167 168 168 The Codes and in general all the Values can be written without any other specification, for example, the transformation to check if the values of the measures of the Dataflow DF1 are between 0 and 25000 can be written like follows: 169 169 170 -'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 ) 153 +> 'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 ) 171 171 172 172 The artefact (Component, Concept, Codelist …) which the Values are referred to can be deduced from the context in which the reference is made, taking also into account the VTL syntax. In the Transformation above, for example, the values 0 and 2500 are compared to the values of the measures of DF1(1.0.0). 173 173 174 -1. 175 -11. 176 -111. User-defined alias 157 +=== 12.2.4 User-defined alias === 177 177 178 178 The third possibility for referencing SDMX artefacts from VTL statements is to use user-defined aliases not related to the SDMX URN of the artefact. 179 179 180 180 This approach gives preference to the use of symbolic names for the SDMX artefacts. As a consequence, in the VTL code the referenced artefacts may become not directly intelligible by a human reader. In any case, the VTL aliases are associated to the SDMX URN through the VtlMappingScheme and VtlMapping classes. These classes provide for structured references to SDMX artefacts whatever kind of reference is used in VTL statements (URN, abbreviated URN or user-defined aliases). 181 181 182 -1. 183 -11. 184 -111. References to SDMX artefacts from VTL Rulesets 163 +=== 12.2.5 References to SDMX artefacts from VTL Rulesets === 185 185 186 186 The VTL Rulesets allow defining sets of reusable Rules that can be applied by some VTL operators, like the ones for validation and hierarchical roll-up. A "Rule" consists in a relationship between Values belonging to some Value Domains or taken by some Variables, for example: (i) when the Country is USA then the Currency is USD; (ii) the Benelux is composed by Belgium, Luxembourg, Netherlands. 187 187 188 188 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. 189 189 190 -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 [[(% class="wikiinternallinkwikiinternallinkwikiinternallink" %)^^~[14~]^^>>path:#_ftn14]](%%).169 +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}}. 191 191 192 -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. [[(% class="wikiinternallinkwikiinternallinkwikiinternallink" %)^^~[15~]^^>>path:#_ftn15]]171 +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}} 193 193 194 194 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. 195 195 196 -1. 197 -11. Mapping between SDMX and VTL artefacts 198 -111. When the mapping occurs 175 +== 12.3 Mapping between SDMX and VTL artefacts == 199 199 177 +=== 12.3.1. When the mapping occurs === 178 + 200 200 The mapping methods between the VTL and SDMX object classes allow transforming a SDMX definition in a VTL one and vice-versa for the artefacts to be manipulated. It should be remembered that VTL programs (i.e. Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformations (nameable artefacts). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result: the input operands of the expression and the result can be SDMX artefacts. Every time a SDMX object is referenced in a VTL Transformation as an input operand, there is the need to generate a VTL definition of the object, so that the VTL operations can take place. This can be made starting from the SDMX definition and applying a SDMX-VTL mapping method in the direction from SDMX to VTL. The possible mapping methods from SDMX to VTL are described in the following paragraphs and are conceived to allow the automatic deduction of the VTL definition of the object from the knowledge of the SDMX definition. 201 201 202 -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 [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[16~]^^>>path:#_ftn16]](%%).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 nonpersistent calculation is disseminated through SDMX tools (like an inquiry tool).{{/footnote}}. 203 203 204 204 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). 205 205 206 -1. 207 -11. 208 -111. General mapping of VTL and SDMX data structures 185 +=== 12.3.2 General mapping of VTL and SDMX data structures === 209 209 210 -This section makes reference to the VTL "Model for data and their structure" [[(% class="wikiinternallinkwikiinternallinkwikiinternallink" %)^^~[17~]^^>>path:#_ftn17]](%%)and the correspondent SDMX "Data Structure Definition"[[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[18~]^^>>path:#_ftn18]](%%).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}}. 211 211 212 -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). [[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[19~]^^>>path:#_ftn19]]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}} 213 213 214 214 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. 215 215 ... ... @@ -221,34 +221,31 @@ 221 221 222 222 The possible mapping options are described in more detail in the following sections. 223 223 224 -1. 225 -11. 226 -111. Mapping from SDMX to VTL data structures 201 +=== 12.3.3 Mapping from SDMX to VTL data structures === 227 227 228 - **12.3.3.1 Basic Mapping**203 +==== 12.3.3.1 Basic Mapping ==== 229 229 230 230 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. 231 231 232 232 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: 233 233 234 -|**SDMX**|**VTL** 235 -|Dimension|(Simple) Identifier 236 -|TimeDimension|(Time) Identifier 237 -|Measure|Measure 238 -|DataAttribute|Attribute 209 +(% style="width:468.294px" %) 210 +|(% style="width:196px" %)**SDMX**|(% style="width:269px" %)**VTL** 211 +|(% style="width:196px" %)Dimension|(% style="width:269px" %)(Simple) Identifier 212 +|(% style="width:196px" %)TimeDimension|(% style="width:269px" %)(Time) Identifier 213 +|(% style="width:196px" %)Measure|(% style="width:269px" %)Measure 214 +|(% style="width:196px" %)DataAttribute|(% style="width:269px" %)Attribute 239 239 240 240 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). 241 241 242 242 With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point. 243 243 244 - **12.3.3.2 Pivot Mapping**220 +==== 12.3.3.2 Pivot Mapping ==== 245 245 246 246 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. 247 247 248 -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}}. 249 249 250 -MeasureDimensions considered as a joint variable[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%). 251 - 252 252 Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension. 253 253 254 254 If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph). ... ... @@ -261,18 +261,19 @@ 261 261 * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure); 262 262 * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship: 263 263 ** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension; 264 -** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators). o Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship. 238 +** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators). 239 +** Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship. 265 265 266 266 The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following: 267 267 268 -|**SDMX**|**VTL** 269 -|Dimension|(Simple) Identifier 270 -|TimeDimension|(Time) Identifier 271 -|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension 272 -|DataAttribute not depending on the MeasureDimension|Attribute 273 -|DataAttribute depending on the MeasureDimension|((( 243 +(% style="width:739.294px" %) 244 +|(% style="width:335px" %)**SDMX**|(% style="width:400px" %)**VTL** 245 +|(% style="width:335px" %)Dimension|(% style="width:400px" %)(Simple) Identifier 246 +|(% style="width:335px" %)TimeDimension|(% style="width:400px" %)(Time) Identifier 247 +|(% style="width:335px" %)MeasureDimension & one Measure|(% style="width:400px" %)One Measure for each Code of the SDMX MeasureDimension 248 +|(% style="width:335px" %)DataAttribute not depending on the MeasureDimension|(% style="width:400px" %)Attribute 249 +|(% style="width:335px" %)DataAttribute depending on the MeasureDimension|(% style="width:400px" %)((( 274 274 One Attribute for each Code of the 275 - 276 276 SDMX MeasureDimension 277 277 ))) 278 278 ... ... @@ -281,31 +281,21 @@ 281 281 At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension: 282 282 283 283 * The set of SDMX observations having the same values for all the Dimensions except than the MeasureDimension become one multi-measure VTL Data Point, having one Measure for each Code Cj of the SDMX MeasureDimension; 284 -* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) 285 - 286 -Identifiers, (time) Identifier and Attributes. 287 - 288 -* 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 289 - 290 -Cj 291 - 259 +* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes. 260 +* The value of the Measure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj 292 292 * 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 293 293 294 - **12.3.3.3 From SDMX DataAttributes to VTL Measures**263 +==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ==== 295 295 296 -* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain 265 +* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain Attributes. 297 297 298 -Attributes. 299 - 300 300 The Basic_A2M and Pivot_A2M behaves respectively like the Basic and Pivot methods, except that the final VTL components, which according to the Basic and Pivot methods would have had the role of Attribute, assume instead the role of Measure. 301 301 302 302 Proper VTL features allow changing the role of specific attributes even after the SDMX to VTL mapping: they can be useful when only some of the DataAttributes need to be managed as VTL Measures. 303 303 304 -1. 305 -11. 306 -111. Mapping from VTL to SDMX data structures 271 +=== 12.3.4 Mapping from VTL to SDMX data structures === 307 307 308 - **12.3.4.1 Basic Mapping**273 +==== 12.3.4.1 Basic Mapping ==== 309 309 310 310 The main mapping method **from VTL to SDMX** is called **Basic **mapping as well. 311 311 ... ... @@ -315,11 +315,12 @@ 315 315 316 316 Mapping table: 317 317 318 -|**VTL**|**SDMX** 319 -|(Simple) Identifier|Dimension 320 -|(Time) Identifier|TimeDimension 321 -|Measure|Measure 322 -|Attribute|DataAttribute 283 +(% style="width:470.294px" %) 284 +|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX** 285 +|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension 286 +|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension 287 +|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure 288 +|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute 323 323 324 324 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. 325 325 ... ... @@ -329,7 +329,7 @@ 329 329 330 330 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. 331 331 332 - **12.3.4.2 Unpivot Mapping**298 +==== 12.3.4.2 Unpivot Mapping ==== 333 333 334 334 An alternative mapping method from VTL to SDMX is the **Unpivot **mapping. 335 335 ... ... @@ -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 316 +(% style="width:638.294px" %) 317 +|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX** 318 +|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension 319 +|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension 320 +|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure 321 +|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension 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**335 +==== 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 ... ... @@ -373,18 +373,17 @@ 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 343 +(% style="width:467.294px" %) 344 +|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX 345 +|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension 346 +|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension 347 +|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure 348 +|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute 349 +|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute 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. 384 384 385 -1. 386 -11. 387 -111. Declaration of the mapping methods between data structures 353 +=== 12.3.5 Declaration of the mapping methods between data structures === 388 388 389 389 In order to define and understand properly VTL Transformations, the applied mapping methods must be specified in the SDMX structural metadata. If the default mapping method (Basic) is applied, no specification is needed. 390 390 ... ... @@ -394,27 +394,23 @@ 394 394 395 395 The VtlMappingScheme is a container for zero or more VtlDataflowMapping (it may contain also mappings towards artefacts other than dataflows). 396 396 397 -1. 398 -11. 399 -111. Mapping dataflow subsets to distinct VTL Data Sets 363 +=== 12.3.6 Mapping dataflow subsets to distinct VTL Data Sets === 400 400 401 -Until now it has been assumed to map one SMDX Dataflow to one VTL Data Set and vice-versa. This mapping one-to-one is not mandatory according to VTL because a VTL Data Set is meant to be a set of observations (data points) on a logical plane, having the same logical data structure and the same general meaning, independently of the possible physical representation or storage (see VTL 2.0 User Manual page 24), therefore a SDMX Dataflow can be seen either as a unique set of data observations 365 +Until now it has been assumed to map one SMDX Dataflow to one VTL Data Set and vice-versa. This mapping one-to-one is not mandatory according to VTL because a VTL Data Set is meant to be a set of observations (data points) on a logical plane, having the same logical data structure and the same general meaning, independently of the possible physical representation or storage (see VTL 2.0 User Manual page 24), therefore a SDMX Dataflow can be seen either as a unique set of data observations (corresponding to one VTL Data Set) or as the union of many sets of data observations (each one corresponding to a distinct VTL Data Set). 402 402 403 - (correspondingtoone VTLDataSet)or as theunion ofmanysetsof data observations(each one corresponding to a distinct VTL Data Set).367 +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}} 404 404 405 - As a matteroffact, insomecases itcan beusefultodefineVTL operations involvingdefinite parts of a SDMX Dataflow insteadthan thewhole.[[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[21~]^^>>path:#_ftn21]]369 +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}} 406 406 407 -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.[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[22~]^^>>path:#_ftn22]] 408 - 409 409 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. 410 410 411 411 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: 412 412 413 -* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order. [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[23~]^^>>path:#_ftn23]](%%)Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.375 +* 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. 414 414 * The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts: 415 415 ** 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); 416 -** a slash (“/”) as a separator; [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[24~]^^>>path:#_ftn24]]417 -** 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 [[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[25~]^^>>path:#_ftn25]](%%). For example378 +** 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}} 379 +** 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 418 418 419 419 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. 420 420 ... ... @@ -422,17 +422,17 @@ 422 422 423 423 Therefore, the generic name of this kind of VTL datasets would be: 424 424 425 -'DF(1.0.0)/INDICATORvalue.COUNTRYvalue' 387 +> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue' 426 426 427 427 Where DF(1.0.0) is the Dataflow and //INDICATORvalue// and //COUNTRYvalue //are placeholders for one value of the INDICATOR and COUNTRY dimensions. Instead the specific name of one of these VTL datasets would be: 428 428 429 -‘DF(1.0.0)/POPULATION.USA’ 391 +> ‘DF(1.0.0)/POPULATION.USA’ 430 430 431 431 In particular, this is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA. 432 432 433 433 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. 434 434 435 -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 [[(%class="wikiinternallinkwikiinternallink wikiinternallink"%)^^~[26~]^^>>path:#_ftn26]](%%)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.397 +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. 436 436 437 437 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. 438 438 ... ... @@ -440,28 +440,24 @@ 440 440 441 441 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. 442 442 443 -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 [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[27~]^^>>path:#_ftn27]](%%). After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.405 +In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …). 444 444 445 -basic, pivot …). 446 - 447 447 In the example above, for all the datasets of the kind 448 448 449 -‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only. 409 +> ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only. 450 450 451 451 It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression: 452 452 453 -‘DF1(1.0.0)/POPULATION.USA’ := 413 +> ‘DF1(1.0.0)/POPULATION.USA’ := 414 +> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ]; 415 +> 416 +> ‘DF1(1.0.0)/POPULATION.CANADA’ := 417 +> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ]; 418 +> 419 +> … … … 454 454 455 -DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];421 +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}} 456 456 457 -‘DF1(1.0.0)/POPULATION.CANADA’ := 458 - 459 -DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ]; 460 - 461 -… … … 462 - 463 -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. [[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[28~]^^>>path:#_ftn28]] 464 - 465 465 In the direction from SDMX to VTL it is allowed to omit the value of one or more DimensionComponents on which the mapping is based, but maintaining all the separating dots (therefore it may happen to find two or more consecutive dots and dots in the beginning or in the end). The absence of value means that for the corresponding Dimension all the values are kept and the Dimension is not dropped. 466 466 467 467 For example, ‘DF(1.0.0)/POPULATION.’ (note the dot in the end of the name) is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and COUNTRY = any value. ... ... @@ -468,10 +468,9 @@ 468 468 469 469 This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//: 470 470 471 -‘DF1(1.0.0)/POPULATION.’ := 429 +> ‘DF1(1.0.0)/POPULATION.’ := 430 +> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ]; 472 472 473 -DF1(1.0.0) [ sub INDICATOR=“POPULATION” ]; 474 - 475 475 Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD. 476 476 477 477 Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations. ... ... @@ -482,99 +482,76 @@ 482 482 483 483 For example, let us assume that the VTL programmer wants to calculate the SDMX 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: 484 484 485 -* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation; [[(%class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[29~]^^>>path:#_ftn29]]486 -* the data structure of all these VTL Data Sets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers. [[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[30~]^^>>path:#_ftn30]]442 +* 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}} 443 +* 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}} 487 487 488 -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 [[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[31~]^^>>path:#_ftn31]](%%).445 +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}}. 489 489 490 -The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind: ^^ ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallink"%)^^~[32~]^^>>path:#_ftn32]]447 +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}} 491 491 492 -‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression 449 +> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression 493 493 494 494 Some examples follow, for some specific values of INDICATOR and COUNTRY: 495 495 496 -‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12; 453 +> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12; 454 +> … … … 455 +> ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21; 456 +> ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22; 457 +> … … … 497 497 498 -… … … 499 - 500 -‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21; 501 - 502 -‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22; 503 - 504 -… … … 505 - 506 506 As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively: 507 507 508 508 VTL dataset INDICATOR value COUNTRY value 509 509 463 +> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA 464 +> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … … 465 +> ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA 466 +> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA 467 +> … … … 510 510 511 -‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA 512 - 513 -‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … … 514 - 515 -‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA 516 - 517 -‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA 518 - 519 -… … … 520 - 521 521 It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be: 522 522 523 -DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; 471 +> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; 472 +> DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … … 473 +> DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; 474 +> DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … … 475 +> DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’, 476 +> DF2bis_GDPPERCAPITA_CANADA’, 477 +> … , 478 +> DF2bis_POPGROWTH_USA’, 479 +> DF2bis_POPGROWTH_CANADA’ 480 +> …); 524 524 525 - DF2bis_GDPPERCAPITA_CANADA:=‘DF2(1.0.0)/GDPPERCAPITA.CANADA’[calc identifierINDICATOR:=”GDPPERCAPITA”,identifier COUNTRY:=”CANADA”];………482 +In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY. 526 526 527 - DF2bis_POPGROWTH_USA:=‘DF2(1.0.0)/POPGROWTH.USA’484 +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}} 528 528 529 -[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; 530 - 531 -DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … … 532 - 533 -DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’, 534 - 535 -DF2bis_GDPPERCAPITA_CANADA’, 536 - 537 -… , 538 - 539 -DF2bis_POPGROWTH_USA’, 540 - 541 -DF2bis_POPGROWTH_CANADA’ 542 - 543 -…); 544 - 545 -In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0)[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[33~]^^>>path:#_ftn33]](%%), which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY. 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. [[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[35~]^^>>path:#_ftn35]] 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). 550 550 551 -1. 552 -11. 553 -111. Mapping variables and value domains between VTL and SDMX 488 +=== 12.3.7 Mapping variables and value domains between VTL and SDMX === 554 554 555 555 With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered: 556 556 557 -|VTL|SDMX 558 -|**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^^ 559 -|**Represented Variable**|**Concept** with a definite Representation 560 -|**Value Domain**|((( 492 +(% style="width:706.294px" %) 493 +|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX 494 +|(% style="width:257px" %)**Data Set Component**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^ 495 +|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation 496 +|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)((( 561 561 **Representation** (see the Structure 562 - 563 563 Pattern in the Base Package) 564 564 ))) 565 -|**Enumerated Value Domain / Code List**|**Codelist** 566 -|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute) 567 -|**Described Value Domain**|((( 500 +|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist** 501 +|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute) 502 +|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)((( 568 568 non-enumerated** Representation** 569 - 570 570 (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package) 571 571 ))) 572 -|**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 573 -| |to a valid **value **(for non-enumerated** **Representations) 574 -|**Value Domain Subset / Set**|This abstraction does not exist in SDMX 575 -|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX 576 -|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX 577 -|**Set list**|This abstraction does not exist in SDMX 506 +|(% style="width:257px" %)**Value**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or 507 +|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations) 508 +|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX 509 +|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX 510 +|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX 511 +|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX 578 578 579 579 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). 580 580 ... ... @@ -582,8 +582,10 @@ 582 582 583 583 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 584 584 585 -DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.519 +> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) 586 586 521 +if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong. 522 + 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 588 588 589 589 Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts. ... ... @@ -590,28 +590,29 @@ 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. 592 592 593 -1. 594 -11. Mapping between SDMX and VTL Data Types 595 -111. VTL Data types 529 +== 12.4 Mapping between SDMX and VTL Data Types == 596 596 531 +=== 12.4.1 VTL Data types === 532 + 597 597 According to the VTL User Guide the possible operations in VTL depend on the data types of the artefacts. For example, numbers can be multiplied but text strings cannot. In the VTL Transformations, the compliance between the operators and the data types of their operands is statically checked, i.e., violations result in compile-time errors. 598 598 599 599 The VTL data types are sub-divided in scalar types (like integers, strings, etc.), which are the types of the scalar values, and compound types (like Data Sets, Components, Rulesets, etc.), which are the types of the compound structures. See below the diagram of the VTL data types, taken from the VTL User Manual: 600 600 601 -[[image:1750067055028-964.png]] 602 602 603 - ==== Figure22– VTL Data Types ====538 +[[image:1750070288958-132.png]] 604 604 540 +**Figure 22 – VTL Data Types** 541 + 605 605 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. 606 606 607 607 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): 608 608 609 - ==== Figure23– VTL Basic Scalar Types ====546 +[[image:1750070310572-584.png]] 610 610 611 -1. 612 -11. 613 -111. VTL basic scalar types and SDMX data types 548 +**Figure 23 – VTL Basic Scalar Types** 614 614 550 +=== 12.4.2 VTL basic scalar types and SDMX data types === 551 + 615 615 The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations. 616 616 617 617 The internal representation is the format used within a VTL system to represent (and process) all the scalar values of a certain type. In principle, this format is hidden and not necessarily known by users. The external representations are instead the external formats of the values of a certain basic scalar type, i.e. the formats known by the users. For example, the internal representation of the dates can be an integer counting the days since a predefined date (e.g. from 01/01/4713 BC up to 31/12/5874897 AD like in Postgres) while two possible external representations are the formats YYYY-MMGG and MM-GG-YYYY (e.g. respectively 2010-12-31 and 12-31-2010). ... ... @@ -628,309 +628,256 @@ 628 628 629 629 The opposite conversion, i.e. from VTL to SDMX, happens when a VTL result, i.e. a VTL Data Set output of a Transformation, must become a SDMX artefact (or part of it). The values of the VTL result must be converted into the desired (SDMX) external representations (data types) of the SDMX artefact. 630 630 631 -1. 632 -11. 633 -111. Mapping SDMX data types to VTL basic scalar types 568 +=== 12.4.3 Mapping SDMX data types to VTL basic scalar types === 634 634 635 635 The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types. 636 636 637 -|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type 638 -|((( 572 +(% style="width:583.294px" %) 573 +|(% style="width:360px" %)SDMX data type (BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type 574 +|(% style="width:360px" %)((( 639 639 String 640 - 641 641 (string allowing any character) 642 -)))|string 643 -|((( 644 -Alpha 645 - 577 +)))|(% style="width:221px" %)string 578 +|(% style="width:360px" %)((( 579 +Alpha 646 646 (string which only allows A-z) 647 -)))|string 648 -|((( 581 +)))|(% style="width:221px" %)string 582 +|(% style="width:360px" %)((( 649 649 AlphaNumeric 650 - 651 651 (string which only allows A-z and 0-9) 652 -)))|string 653 -|((( 585 +)))|(% style="width:221px" %)string 586 +|(% style="width:360px" %)((( 654 654 Numeric 655 - 656 656 (string which only allows 0-9, but is not numeric so that is can having leading zeros) 657 -)))|string 658 -|((( 589 +)))|(% style="width:221px" %)string 590 +|(% style="width:360px" %)((( 659 659 BigInteger 660 - 661 661 (corresponds to XML Schema xs:integer datatype; infinite set of integer values) 662 -)))|integer 663 -|((( 593 +)))|(% style="width:221px" %)integer 594 +|(% style="width:360px" %)((( 664 664 Integer 665 - 666 666 (corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 667 - 668 668 (inclusive)) 669 -)))|integer 670 -|((( 598 +)))|(% style="width:221px" %)integer 599 +|(% style="width:360px" %)((( 671 671 Long 672 - 673 673 (corresponds to XML Schema xs:long datatype; between -9223372036854775808 and 674 - 675 675 +9223372036854775807 (inclusive)) 676 -)))|integer 677 -|((( 603 +)))|(% style="width:221px" %)integer 604 +|(% style="width:360px" %)((( 678 678 Short 679 - 680 680 (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive)) 681 -)))|integer 682 -|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number 683 -|((( 607 +)))|(% style="width:221px" %)integer 608 +|(% style="width:360px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:221px" %)number 609 +|(% style="width:360px" %)((( 684 684 Float 685 - 686 686 (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type) 687 -)))|number 688 -|((( 612 +)))|(% style="width:221px" %)number 613 +|(% style="width:360px" %)((( 689 689 Double 690 - 691 691 (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type) 692 -)))|number 693 -|((( 616 +)))|(% style="width:221px" %)number 617 +|(% style="width:360px" %)((( 694 694 Boolean 695 - 696 696 (corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of 697 - 698 698 binary-valued logic: {true, false}) 699 -)))|boolean 700 -|((( 621 +)))|(% style="width:221px" %)boolean 622 +|(% style="width:360px" %)((( 701 701 URI 702 - 703 703 (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference) 704 -)))|string 705 -|((( 625 +)))|(% style="width:221px" %)string 626 +|(% style="width:360px" %)((( 706 706 Count 707 - 708 708 (an integer following a sequential pattern, increasing by 1 for each occurrence) 709 -)))|integer 710 -|((( 629 +)))|(% style="width:221px" %)integer 630 +|(% style="width:360px" %)((( 711 711 InclusiveValueRange 712 - 713 713 (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 714 -)))|number 715 -|((( 633 +)))|(% style="width:221px" %)number 634 +|(% style="width:360px" %)((( 716 716 ExclusiveValueRange 717 - 718 718 (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 719 -)))|number 720 -|((( 637 +)))|(% style="width:221px" %)number 638 +|(% style="width:360px" %)((( 721 721 Incremental 722 - 723 723 (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation) 724 -)))|number 725 -|((( 641 +)))|(% style="width:221px" %)number 642 +|(% style="width:360px" %)((( 726 726 ObservationalTimePeriod 727 - 728 728 (superset of StandardTimePeriod and TimeRange) 729 -)))|time 730 -|((( 645 +)))|(% style="width:221px" %)time 646 +|(% style="width:360px" %)((( 731 731 StandardTimePeriod 732 - 733 733 (superset of BasicTimePeriod and ReportingTimePeriod) 734 -)))|time 735 -|((( 649 +)))|(% style="width:221px" %)time 650 +|(% style="width:360px" %)((( 736 736 BasicTimePeriod 737 - 738 738 (superset of GregorianTimePeriod and DateTime) 739 -)))|date 740 -|((( 653 +)))|(% style="width:221px" %)date 654 +|(% style="width:360px" %)((( 741 741 GregorianTimePeriod 742 - 743 743 (superset of GregorianYear, GregorianYearMonth, and GregorianDay) 744 -)))|date 745 -|GregorianYear (YYYY)|date 746 -|GregorianYearMonth / GregorianMonth (YYYY-MM)|date 747 -|GregorianDay (YYYY-MM-DD)|date 748 -|((( 657 +)))|(% style="width:221px" %)date 658 +|(% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date 659 +|(% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date 660 +|(% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date 661 +|(% style="width:360px" %)((( 749 749 ReportingTimePeriod 750 - 751 751 (superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay) 752 -)))|time_period 753 -|((( 664 +)))|(% style="width:221px" %)time_period 665 +|(% style="width:360px" %)((( 754 754 ReportingYear 755 - 756 756 (YYYY-A1 – 1 year period) 757 -)))|time_period 758 -|((( 668 +)))|(% style="width:221px" %)time_period 669 +|(% style="width:360px" %)((( 759 759 ReportingSemester 760 - 761 761 (YYYY-Ss – 6 month period) 762 -)))|time_period 763 -|((( 672 +)))|(% style="width:221px" %)time_period 673 +|(% style="width:360px" %)((( 764 764 ReportingTrimester 765 - 766 766 (YYYY-Tt – 4 month period) 767 -)))|time_period 768 -|((( 676 +)))|(% style="width:221px" %)time_period 677 +|(% style="width:360px" %)((( 769 769 ReportingQuarter 770 - 771 771 (YYYY-Qq – 3 month period) 772 -)))|time_period 773 -|((( 680 +)))|(% style="width:221px" %)time_period 681 +|(% style="width:360px" %)((( 774 774 ReportingMonth 775 - 776 776 (YYYY-Mmm – 1 month period) 777 -)))|time_period 778 -|ReportingWeek|time_period 779 -| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)| 780 -|((( 684 +)))|(% style="width:221px" %)time_period 685 +|(% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period 686 +|(% style="width:360px" %) (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% style="width:221px" %) 687 +|(% style="width:360px" %)((( 781 781 ReportingDay 782 - 783 783 (YYYY-Dddd – 1 day period) 784 -)))|time_period 785 -|((( 690 +)))|(% style="width:221px" %)time_period 691 +|(% style="width:360px" %)((( 786 786 DateTime 787 - 788 788 (YYYY-MM-DDThh:mm:ss) 789 -)))|date 790 -|((( 694 +)))|(% style="width:221px" %)date 695 +|(% style="width:360px" %)((( 791 791 TimeRange 792 - 793 793 (YYYY-MM-DD(Thh:mm:ss)?/<duration>) 794 -)))|time 795 -|((( 698 +)))|(% style="width:221px" %)time 699 +|(% style="width:360px" %)((( 796 796 Month 797 - 798 798 (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States) 799 -)))|string 800 -|((( 702 +)))|(% style="width:221px" %)string 703 +|(% style="width:360px" %)((( 801 801 MonthDay 802 - 803 803 (~-~-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) 804 -)))|string 805 -|((( 706 +)))|(% style="width:221px" %)string 707 +|(% style="width:360px" %)((( 806 806 Day 807 - 808 808 (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday) 809 -)))|string 810 -|((( 710 +)))|(% style="width:221px" %)string 711 +|(% style="width:360px" %)((( 811 811 Time 812 - 813 813 (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM) 814 -)))|string 815 -|((( 714 +)))|(% style="width:221px" %)string 715 +|(% style="width:360px" %)((( 816 816 Duration 817 - 818 818 (corresponds to XML Schema xs:duration datatype) 819 -)))|duration 820 -|XHTML|Metadata type – not applicable 821 -|KeyValues|Metadata type – not applicable 822 -|IdentifiableReference|Metadata type – not applicable 823 -|DataSetReference|Metadata type – not applicable 718 +)))|(% style="width:221px" %)duration 719 +|(% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable 720 +|(% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable 721 +|(% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable 722 +|(% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable 824 824 825 - додол724 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 826 826 827 -==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ==== 828 - 829 829 When VTL takes in input SDMX artefacts, it is assumed that a type conversion according to the table above always happens. In case a different VTL basic scalar type is desired, it can be achieved in the VTL program taking in input the default VTL basic scalar type above and applying to it the VTL type conversion features (see the implicit and explicit type conversion and the "cast" operator in the VTL Reference Manual). 830 830 831 -1. 832 -11. 833 -111. Mapping VTL basic scalar types to SDMX data types 728 +=== 12.4.4 Mapping VTL basic scalar types to SDMX data types === 834 834 835 835 The following table describes the default conversion from the VTL basic scalar types to the SDMX data types . 836 836 837 -|((( 838 -VTL basic 839 - 840 -scalar type 841 -)))|((( 732 +(% style="width:748.294px" %) 733 +|(% style="width:164px" %)((( 734 +VTL basic scalar type 735 +)))|(% style="width:304px" %)((( 842 842 Default SDMX data type 843 - 844 -(BasicComponentDataType 845 - 846 -) 847 -)))|Default output format 848 -|String|String|Like XML (xs:string) 849 -|Number|Float|Like XML (xs:float) 850 -|Integer|Integer|Like XML (xs:int) 851 -|Date|DateTime|YYYY-MM-DDT00:00:00Z 852 -|Time|StandardTimePeriod|<date>/<date> (as defined above) 853 -|time_period|((( 737 +(BasicComponentDataType) 738 +)))|(% style="width:277px" %)Default output format 739 +|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string) 740 +|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float) 741 +|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int) 742 +|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z 743 +|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above) 744 +|(% style="width:164px" %)time_period|(% style="width:304px" %)((( 854 854 ReportingTimePeriod 855 - 856 856 (StandardReportingPeriod) 857 -)))|((( 747 +)))|(% style="width:277px" %)((( 858 858 YYYY-Pppp 859 - 860 860 (according to SDMX ) 861 861 ))) 862 -|Duration|Duration|Like XML(xs:duration) PnYnMnDTnHnMnS863 -|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false" 751 +|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS 752 +|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false" 864 864 865 - ====Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types====754 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 866 866 867 -In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section 756 +In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model). 868 868 869 -Transformations and Expressions of the SDMX information model). 870 - 871 871 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. 872 872 873 -|(% colspan="2" %)VTL special characters for the formatting masks 874 -|(% colspan="2" %) 875 -|(% colspan="2" %)Number 876 -|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa) 877 -|E|one numeric digit (for the exponent of the scientific notation) 878 -|. (dot)|possible separator between the integer and the decimal parts. 879 -|, (comma)|possible separator between the integer and the decimal parts. 880 -| | 881 -|(% colspan="2" %)Time and duration 882 -|C|century 883 -|Y|year 884 -|S|semester 885 -|Q|quarter 886 -|M|month 887 -|W|week 888 -|D|day 889 -|h|hour digit (by default on 24 hours) 890 -|M|minute 891 -|S|second 892 -|D|decimal of second 893 -|P|period indicator (representation in one digit for the duration) 894 -|P|number of the periods specified in the period indicator 895 -|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm") 896 -|MONTH|uppercase textual representation of the month (e.g., JANUARY for January) 897 -|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday) 898 -|Month|lowercase textual representation of the month (e.g., january) 899 -|Day|lowercase textual representation of the month (e.g., monday) 900 -|Month|First character uppercase, then lowercase textual representation of the month (e.g., January) 901 -|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday) 902 -| | 903 -|(% colspan="2" %)String 904 -|X|any string character 905 -|Z|any string character from "A" to "z" 906 -|9|any string character from "0" to "9" 907 -| | 908 -|(% colspan="2" %)Boolean 909 -|B|Boolean using "true" for True and "false" for False 910 -|1|Boolean using "1" for True and "0" for False 911 -|0|Boolean using "0" for True and "1" for False 912 -| | 913 -|(% colspan="2" %)Other qualifiers 914 -|*|an arbitrary number of digits (of the preceding type) 915 -|+|at least one digit (of the preceding type) 916 -|( )|optional digits (specified within the brackets) 917 -|\|prefix for the special characters that must appear in the mask 918 -|N|fixed number of digits used in the preceding textual representation of the month or the day 919 -| | 760 +(% style="width:717.294px" %) 761 +|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks 762 +|(% colspan="2" style="width:714px" %) 763 +|(% colspan="2" style="width:714px" %)Number 764 +|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa) 765 +|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation) 766 +|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts. 767 +|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts. 768 +|(% style="width:122px" %) |(% style="width:591px" %) 769 +|(% colspan="2" style="width:714px" %)Time and duration 770 +|(% style="width:122px" %)C|(% style="width:591px" %)century 771 +|(% style="width:122px" %)Y|(% style="width:591px" %)year 772 +|(% style="width:122px" %)S|(% style="width:591px" %)semester 773 +|(% style="width:122px" %)Q|(% style="width:591px" %)quarter 774 +|(% style="width:122px" %)M|(% style="width:591px" %)month 775 +|(% style="width:122px" %)W|(% style="width:591px" %)week 776 +|(% style="width:122px" %)D|(% style="width:591px" %)day 777 +|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours) 778 +|(% style="width:122px" %)M|(% style="width:591px" %)minute 779 +|(% style="width:122px" %)S|(% style="width:591px" %)second 780 +|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second 781 +|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration) 782 +|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator 783 +|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm") 784 +|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January) 785 +|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday) 786 +|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january) 787 +|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday) 788 +|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January) 789 +|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday) 790 +|(% style="width:122px" %) |(% style="width:591px" %) 791 +|(% colspan="2" style="width:714px" %)String 792 +|(% style="width:122px" %)X|(% style="width:591px" %)any string character 793 +|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z" 794 +|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9" 795 +|(% style="width:122px" %) |(% style="width:591px" %) 796 +|(% colspan="2" style="width:714px" %)Boolean 797 +|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False 798 +|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False 799 +|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False 800 +|(% style="width:122px" %) |(% style="width:591px" %) 801 +|(% colspan="2" style="width:714px" %)Other qualifiers 802 +|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type) 803 +|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type) 804 +|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets) 805 +|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask 806 +|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day 807 +|(% style="width:122px" %) |(% style="width:591px" %) 920 920 921 921 The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion{{footnote}}The representation given in the DSD should obviously be compatible with the VTL data type.{{/footnote}}. 922 922 923 -1. 924 -11. 925 -111. Null Values 811 +=== 12.4.3 Null Values === 926 926 927 927 In the conversions from SDMX to VTL it is assumed by default that a missing value in SDMX becomes a NULL in VTL. After the conversion, the NULLs can be manipulated through the proper VTL operators. 928 928 929 929 On the other side, the VTL programs can produce in output NULL values for Measures and Attributes (Null values are not allowed in the Identifiers). In the conversion from VTL to SDMX, it is assumed that a NULL in VTL becomes a missing value in SDMX. In the conversion from VTL to SDMX, the default assumption can be overridden, separately for each VTL basic scalar type, by specifying which the value that represents the NULL in SDMX is. This can be specified in the attribute "nullValue" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model). A CustomType belongs to a CustomTypeScheme, which can be referenced by one or more TransformationScheme (i.e. VTL programs). The overriding assumption is applied for all the SDMX Dataflows calculated in the TransformationScheme. 930 930 931 -1. 932 -11. 933 -111. Format of the literals used in VTL Transformations 817 +=== 12.4.5 Format of the literals used in VTL Transformations === 934 934 935 935 The VTL programs can contain literals, i.e. specific values of certain data types written directly in the VTL definitions or expressions. The VTL does not prescribe a specific format for the literals and leave the specific VTL systems and the definers of VTL Transformations free of using their preferred formats. 936 936 ... ... @@ -944,78 +944,6 @@ 944 944 945 945 In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats. 946 946 947 - 948 948 ---- 949 949 950 -[[~[1~]>>path:#_ftnref1]] 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>>url:https://sdmx.org/]][[.>>url:https://sdmx.org/]] 951 - 952 -[[~[2~]>>path:#_ftnref2]] 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 953 - 954 -[[~[3~]>>path:#_ftnref3]] See also the section "VTL-DL Rulesets" in the VTL Reference Manual. 955 - 956 -[[~[4~]>>path:#_ftnref4]] 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. 957 - 958 -[[~[5~]>>path:#_ftnref5]] 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)"). 959 - 960 -[[~[6~]>>path:#_ftnref6]] The container-object-id can repeat and may not be present. 961 - 962 -[[~[7~]>>path:#_ftnref7]] i.e., the artefact belongs to a maintainable class 963 - 964 -[[~[8~]>>path:#_ftnref8]] 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. 965 - 966 -[[~[9~]>>path:#_ftnref9]] For the syntax of the VTL operators see the VTL Reference Manual 967 - 968 -[[~[10~]>>path:#_ftnref10]] 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. 969 - 970 -[[~[11~]>>path:#_ftnref11]] 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) 971 - 972 -[[~[12~]>>path:#_ftnref12]] Single quotes are needed because this reference is not a VTL regular name. ^^19^^ Single quotes are not needed in this case because CL_FREQ is a VTL regular name. 973 - 974 -[[~[13~]>>path:#_ftnref13]] The result DFR(1.0.0) is be equal to DF1(1.0.0) save that the component SECTOR is called SEC 975 - 976 -[[~[14~]>>path:#_ftnref14]] Rulesets of this kind cannot be reused when the referenced Concept has a different representation. 977 - 978 -[[~[15~]>>path:#_ftnref15]] See also the section "VTL-DL Rulesets" in the VTL Reference Manual. 979 - 980 -[[~[16~]>>path:#_ftnref16]] 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 nonpersistent calculation is disseminated through SDMX tools (like an inquiry tool). 981 - 982 -[[~[17~]>>path:#_ftnref17]] See the VTL 2.0 User Manual 983 - 984 -[[~[18~]>>path:#_ftnref18]] See the SDMX Standards Section 2 – Information Model 985 - 986 -[[~[19~]>>path:#_ftnref19]] 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. 987 - 988 -[[~[20~]>>path:#_ftnref20]] 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)”. 989 - 990 -[[~[21~]>>path:#_ftnref21]] 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. 991 - 992 -[[~[22~]>>path:#_ftnref22]] 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. 993 - 994 -[[~[23~]>>path:#_ftnref23]] 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. 995 - 996 -[[~[24~]>>path:#_ftnref24]] 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. 997 - 998 -[[~[25~]>>path:#_ftnref25]] 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. 999 - 1000 -[[~[26~]>>path:#_ftnref26]] 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. 1001 - 1002 -[[~[27~]>>path:#_ftnref27]] 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). 1003 - 1004 -[[~[28~]>>path:#_ftnref28]] 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. 1005 - 1006 -[[~[29~]>>path:#_ftnref29]] 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. 1007 - 1008 -[[~[30~]>>path:#_ftnref30]] This is possible as each VTL dataset corresponds to one particular combination of values of INDICATOR and COUNTRY. 1009 - 1010 -[[~[31~]>>path:#_ftnref31]] The mapping dimensions are defined as FromVtlSpaceKeys of the FromVtlSuperSpace of the VtlDataflowMapping relevant to DF2(1.0). 1011 - 1012 -[[~[32~]>>path:#_ftnref32]] the symbol of the VTL persistent assignment is used (<-) 1013 - 1014 -[[~[33~]>>path:#_ftnref33]] The result is persistent in this example but it can be also non persistent if needed. 1015 - 1016 -[[~[34~]>>path:#_ftnref34]] 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. 1017 - 1018 -[[~[35~]>>path:#_ftnref35]] Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume. 1019 - 1020 - 1021 1021 {{putFootnotes/}}
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