Changes for page 12 Validation and Transformation Language (VTL)
Last modified by Artur on 2025/09/10 11:19
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... ... @@ -18,7 +18,7 @@ 18 18 19 19 This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts. 20 20 21 -== 12.2 References to SDMX artefacts from VTL statements == 21 +== 12.2 References to SDMX artefacts from VTL statements == 22 22 23 23 === 12.2.1 Introduction === 24 24 ... ... @@ -80,9 +80,9 @@ 80 80 81 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}}: 82 82 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)' 83 +>(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <- 84 +>(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' + 85 +>(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 86 86 87 87 === 12.2.3 Abbreviation of the URN === 88 88 ... ... @@ -92,13 +92,10 @@ 92 92 93 93 * 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. 94 94 * 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: 95 -** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, 96 -** "conceptscheme" for the class Concept, 97 -** "codelist" for the class Codelist. 95 +** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist. 98 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 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; 98 +* As for the maintainedobject-id, this is essential in some cases while in other cases it can be omitted: o if the referenced artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the dataflow-id and obviously cannot be omitted; 102 102 ** 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; 103 103 ** 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; 104 104 ** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted. ... ... @@ -110,47 +110,51 @@ 110 110 111 111 For example, the full formulation that uses the complete URN shown at the end of the previous paragraph: 112 112 113 -> '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)' 110 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' := 116 116 112 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' + 113 + 114 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 115 + 117 117 by omitting all the non-essential parts would become simply: 118 118 119 - >DFR:= DF1 + DF2118 +DFR := DF1 + DF2 120 120 121 121 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}}: 122 122 123 - >'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'122 +'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)' 124 124 125 125 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^^: 126 126 127 - >CL_FREQ126 +CL_FREQ 128 128 129 129 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: 130 130 131 - >'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).SECTOR'130 +'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).S 132 132 132 +ECTOR' 133 + 133 133 The corresponding fully abbreviated reference, if made from a TransformationScheme belonging to AG, would become simply: 134 134 135 - >SECTOR136 +SECTOR 136 136 137 137 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}}: 138 138 139 - >'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]140 +'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC] 140 140 141 141 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. 142 142 143 143 An example of non-abbreviated reference, if the conceptScheme-id is CS1 and the concept-id is SECTOR, is the following: 144 144 145 - >'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR'146 +'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR' 146 146 147 147 The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply: 148 148 149 - >CS1(1.0.0).SECTOR150 +CS1(1.0.0).SECTOR 150 150 151 151 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: 152 152 153 - >'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )154 +'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 ) 154 154 155 155 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). 156 156 ... ... @@ -198,7 +198,7 @@ 198 198 199 199 The possible mapping options are described in more detail in the following sections. 200 200 201 -=== 12.3. 3Mapping from SDMX to VTL data structures ===202 +=== 12.3.2 Mapping from SDMX to VTL data structures === 202 202 203 203 ==== 12.3.3.1 Basic Mapping ==== 204 204 ... ... @@ -206,12 +206,11 @@ 206 206 207 207 When transforming **from SDMX to VTL**, this method consists in leaving the components unchanged and maintaining their names and roles, according to the following table: 208 208 209 -(% style="width: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 210 +|**SDMX**|**VTL** 211 +|Dimension|(Simple) Identifier 212 +|TimeDimension|(Time) Identifier 213 +|Measure|Measure 214 +|DataAttribute|Attribute 215 215 216 216 The SDMX DataAttributes, in VTL they are all considered "at data point / observation level" (i.e. dependent on all the VTL Identifiers), because VTL does not have the SDMX AttributeRelationships, which defines the construct to which the DataAttribute is related (e.g. observation, dimension or set or group of dimensions, whole data set). 217 217 ... ... @@ -221,8 +221,10 @@ 221 221 222 222 An alternative mapping method from SDMX to VTL is the **Pivot **mapping, which makes sense and is different from the Basic method only for the SDMX data structures that contain a Dimension that plays the role of measure dimension (like in SDMX 2.1) and just one Measure. Through this method, these structures can be mapped to multimeasure VTL data structures. Besides that, a user may choose to use any Dimension acting as a list of Measures (e.g., a Dimension with indicators), either by considering the “Measure” role of a Dimension, or at will using any coded Dimension. Of course, in SDMX 3.0, this can only work when only one Measure is defined in the DSD. 223 223 224 -In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.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 225 225 226 +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}}. 227 + 226 226 Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension. 227 227 228 228 If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph). ... ... @@ -235,18 +235,16 @@ 235 235 * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure); 236 236 * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship: 237 237 ** 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; 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. 240 +** 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. 240 240 241 241 The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following: 242 242 243 -(% 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" %)((( 244 +|**SDMX**|**VTL** 245 +|Dimension|(Simple) Identifier 246 +|TimeDimension|(Time) Identifier 247 +|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension 248 +|DataAttribute not depending on the MeasureDimension|Attribute 249 +|DataAttribute depending on the MeasureDimension|((( 250 250 One Attribute for each Code of the 251 251 SDMX MeasureDimension 252 252 ))) ... ... @@ -256,14 +256,19 @@ 256 256 At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension: 257 257 258 258 * 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; 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. 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) 260 + 261 +Identifiers, (time) Identifier and Attributes. 262 + 260 260 * 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 261 261 * 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 262 262 263 263 ==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ==== 264 264 265 -* 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.268 +* 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 266 266 270 +Attributes. 271 + 267 267 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. 268 268 269 269 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. ... ... @@ -280,12 +280,11 @@ 280 280 281 281 Mapping table: 282 282 283 -(% 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 288 +|**VTL**|**SDMX** 289 +|(Simple) Identifier|Dimension 290 +|(Time) Identifier|TimeDimension 291 +|Measure|Measure 292 +|Attribute|DataAttribute 289 289 290 290 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. 291 291 ... ... @@ -313,12 +313,11 @@ 313 313 314 314 The summary mapping table of the **unpivot** mapping method is the following: 315 315 316 -(% 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 320 +|**VTL**|**SDMX** 321 +|(Simple) Identifier|Dimension 322 +|(Time) Identifier|TimeDimension 323 +|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure 324 +|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension 322 322 323 323 At observation / data point level: 324 324 ... ... @@ -340,13 +340,12 @@ 340 340 341 341 The mapping table is the following: 342 342 343 -(% 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 346 +|VTL|SDMX 347 +|(Simple) Identifier|Dimension 348 +|(Time) Identifier|TimeDimension 349 +|Some Measures|Measure 350 +|Other Measures|DataAttribute 351 +|Attribute|DataAttribute 350 350 351 351 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. 352 352 ... ... @@ -384,11 +384,11 @@ 384 384 385 385 Therefore, the generic name of this kind of VTL datasets would be: 386 386 387 - >'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'389 +'DF(1.0.0)/INDICATORvalue.COUNTRYvalue' 388 388 389 389 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: 390 390 391 - >‘DF(1.0.0)/POPULATION.USA’393 +‘DF(1.0.0)/POPULATION.USA’ 392 392 393 393 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. 394 394 ... ... @@ -402,22 +402,26 @@ 402 402 403 403 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. 404 404 405 -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 …).407 +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. 406 406 409 +basic, pivot …). 410 + 407 407 In the example above, for all the datasets of the kind 408 408 409 - >‘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.413 +‘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. 410 410 411 411 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: 412 412 413 -> ‘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 -> … … … 417 +‘DF1(1.0.0)/POPULATION.USA’ := 420 420 419 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ]; 420 + 421 +‘DF1(1.0.0)/POPULATION.CANADA’ := 422 + 423 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ]; 424 + 425 +… … … 426 + 421 421 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}} 422 422 423 423 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. ... ... @@ -426,9 +426,10 @@ 426 426 427 427 This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//: 428 428 429 -> ‘DF1(1.0.0)/POPULATION.’ := 430 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ]; 435 +‘DF1(1.0.0)/POPULATION.’ := 431 431 437 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ]; 438 + 432 432 Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD. 433 433 434 434 Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations. ... ... @@ -446,33 +446,41 @@ 446 446 447 447 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}} 448 448 449 - >‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression456 +‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression 450 450 451 451 Some examples follow, for some specific values of INDICATOR and COUNTRY: 452 452 453 -> ‘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 -> … … … 460 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12; 461 +… … … 458 458 463 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21; 464 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22; 465 +… … … 466 + 459 459 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: 460 460 461 -> VTL dataset INDICATOR value COUNTRY value 462 -> 463 -> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA 464 -> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … … 465 -> 466 -> ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA 467 -> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA 468 -> … … … 469 +VTL dataset INDICATOR value COUNTRY value 469 469 471 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA 472 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … … 473 +‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA 474 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA 475 + 476 +… … … 477 + 470 470 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: 471 471 472 -> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”];… … … DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”];… … … DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’, DF2bis_GDPPERCAPITA_CANADA’, 473 -> … , 474 -> DF2bis_POPGROWTH_USA’, DF2bis_POPGROWTH_CANADA’ 475 -> …); 480 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; 481 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … … 482 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’ 483 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; 484 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … … 485 +DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’, 486 +DF2bis_GDPPERCAPITA_CANADA’, 487 +… , 488 +DF2bis_POPGROWTH_USA’, 489 +DF2bis_POPGROWTH_CANADA’ 490 +…); 476 476 477 477 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. 478 478 ... ... @@ -484,26 +484,25 @@ 484 484 485 485 With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered: 486 486 487 -(% style="width:706.294px" %) 488 -|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX 489 -|(% 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^^ 490 -|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation 491 -|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)((( 502 +|VTL|SDMX 503 +|**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^^ 504 +|**Represented Variable**|**Concept** with a definite Representation 505 +|**Value Domain**|((( 492 492 **Representation** (see the Structure 493 493 Pattern in the Base Package) 494 494 ))) 495 -| (% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**496 -| (% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)497 -| (% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((509 +|**Enumerated Value Domain / Code List**|**Codelist** 510 +|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute) 511 +|**Described Value Domain**|((( 498 498 non-enumerated** Representation** 499 499 (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package) 500 500 ))) 501 -| (% 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) or502 -| (%style="width:257px" %)|(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)503 -| (% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX504 -| (% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX505 -| (% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX506 -| (% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX515 +|**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 516 +| |to a valid **value **(for non-enumerated** **Representations) 517 +|**Value Domain Subset / Set**|This abstraction does not exist in SDMX 518 +|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX 519 +|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX 520 +|**Set list**|This abstraction does not exist in SDMX 507 507 508 508 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). 509 509 ... ... @@ -511,10 +511,8 @@ 511 511 512 512 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 513 513 514 - >DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)528 +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. 515 515 516 -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. 517 - 518 518 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 519 519 520 520 Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts. ... ... @@ -529,9 +529,8 @@ 529 529 530 530 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: 531 531 544 +[[image:1750067055028-964.png]] 532 532 533 -[[image:1750070288958-132.png]] 534 - 535 535 **Figure 22 – VTL Data Types** 536 536 537 537 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. ... ... @@ -538,8 +538,6 @@ 538 538 539 539 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): 540 540 541 -[[image:1750070310572-584.png]] 542 - 543 543 **Figure 23 – VTL Basic Scalar Types** 544 544 545 545 === 12.4.2 VTL basic scalar types and SDMX data types === ... ... @@ -564,157 +564,158 @@ 564 564 565 565 The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types. 566 566 567 -(% style="width:583.294px" %) 568 -|(% style="width:360px" %)SDMX data type (BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type 569 -|(% style="width:360px" %)((( 576 +|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type 577 +|((( 570 570 String 571 571 (string allowing any character) 572 -)))|(% style="width:221px" %)string 573 -|(% style="width:360px" %)((( 574 -Alpha 580 +)))|string 581 +|((( 582 +Alpha 583 + 575 575 (string which only allows A-z) 576 -)))| (%style="width:221px" %)string577 -|( % style="width:360px" %)(((585 +)))|string 586 +|((( 578 578 AlphaNumeric 579 579 (string which only allows A-z and 0-9) 580 -)))| (%style="width:221px" %)string581 -|( % style="width:360px" %)(((589 +)))|string 590 +|((( 582 582 Numeric 592 + 583 583 (string which only allows 0-9, but is not numeric so that is can having leading zeros) 584 -)))| (%style="width:221px" %)string585 -|( % style="width:360px" %)(((594 +)))|string 595 +|((( 586 586 BigInteger 587 587 (corresponds to XML Schema xs:integer datatype; infinite set of integer values) 588 -)))| (% style="width:221px" %)integer589 -|( % style="width:360px" %)(((598 +)))|integer 599 +|((( 590 590 Integer 591 591 (corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 592 592 (inclusive)) 593 -)))| (% style="width:221px" %)integer594 -|( % style="width:360px" %)(((603 +)))|integer 604 +|((( 595 595 Long 596 596 (corresponds to XML Schema xs:long datatype; between -9223372036854775808 and 597 597 +9223372036854775807 (inclusive)) 598 -)))| (% style="width:221px" %)integer599 -|( % style="width:360px" %)(((608 +)))|integer 609 +|((( 600 600 Short 601 601 (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive)) 602 -)))| (% style="width:221px" %)integer603 -| (% style="width:360px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:221px" %)number604 -|( % style="width:360px" %)(((612 +)))|integer 613 +|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number 614 +|((( 605 605 Float 606 606 (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type) 607 -)))| (% style="width:221px" %)number608 -|( % style="width:360px" %)(((617 +)))|number 618 +|((( 609 609 Double 610 610 (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type) 611 -)))| (% style="width:221px" %)number612 -|( % style="width:360px" %)(((621 +)))|number 622 +|((( 613 613 Boolean 614 614 (corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of 615 615 binary-valued logic: {true, false}) 616 -)))| (% style="width:221px" %)boolean617 -|( % style="width:360px" %)(((626 +)))|boolean 627 +|((( 618 618 URI 619 619 (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference) 620 -)))| (%style="width:221px" %)string621 -|( % style="width:360px" %)(((630 +)))|string 631 +|((( 622 622 Count 623 623 (an integer following a sequential pattern, increasing by 1 for each occurrence) 624 -)))| (% style="width:221px" %)integer625 -|( % style="width:360px" %)(((634 +)))|integer 635 +|((( 626 626 InclusiveValueRange 627 627 (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 628 -)))| (% style="width:221px" %)number629 -|( % style="width:360px" %)(((638 +)))|number 639 +|((( 630 630 ExclusiveValueRange 631 631 (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 632 -)))| (% style="width:221px" %)number633 -|( % style="width:360px" %)(((642 +)))|number 643 +|((( 634 634 Incremental 635 635 (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation) 636 -)))| (% style="width:221px" %)number637 -|( % style="width:360px" %)(((646 +)))|number 647 +|((( 638 638 ObservationalTimePeriod 639 639 (superset of StandardTimePeriod and TimeRange) 640 -)))| (% style="width:221px" %)time641 -|( % style="width:360px" %)(((650 +)))|time 651 +|((( 642 642 StandardTimePeriod 643 643 (superset of BasicTimePeriod and ReportingTimePeriod) 644 -)))| (% style="width:221px" %)time645 -|( % style="width:360px" %)(((654 +)))|time 655 +|((( 646 646 BasicTimePeriod 647 647 (superset of GregorianTimePeriod and DateTime) 648 -)))| (% style="width:221px" %)date649 -|( % style="width:360px" %)(((658 +)))|date 659 +|((( 650 650 GregorianTimePeriod 651 651 (superset of GregorianYear, GregorianYearMonth, and GregorianDay) 652 -)))| (% style="width:221px" %)date653 -| (% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date654 -| (% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date655 -| (% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date656 -|( % style="width:360px" %)(((662 +)))|date 663 +|GregorianYear (YYYY)|date 664 +|GregorianYearMonth / GregorianMonth (YYYY-MM)|date 665 +|GregorianDay (YYYY-MM-DD)|date 666 +|((( 657 657 ReportingTimePeriod 658 658 (superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay) 659 -)))| (% style="width:221px" %)time_period660 -|( % style="width:360px" %)(((669 +)))|time_period 670 +|((( 661 661 ReportingYear 662 662 (YYYY-A1 – 1 year period) 663 -)))| (% style="width:221px" %)time_period664 -|( % style="width:360px" %)(((673 +)))|time_period 674 +|((( 665 665 ReportingSemester 666 666 (YYYY-Ss – 6 month period) 667 -)))| (% style="width:221px" %)time_period668 -|( % style="width:360px" %)(((677 +)))|time_period 678 +|((( 669 669 ReportingTrimester 670 670 (YYYY-Tt – 4 month period) 671 -)))| (% style="width:221px" %)time_period672 -|( % style="width:360px" %)(((681 +)))|time_period 682 +|((( 673 673 ReportingQuarter 674 674 (YYYY-Qq – 3 month period) 675 -)))| (% style="width:221px" %)time_period676 -|( % style="width:360px" %)(((685 +)))|time_period 686 +|((( 677 677 ReportingMonth 678 678 (YYYY-Mmm – 1 month period) 679 -)))| (% style="width:221px" %)time_period680 -| (% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period681 -| (%style="width:360px" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(%style="width:221px" %)682 -|( % style="width:360px" %)(((689 +)))|time_period 690 +|ReportingWeek|time_period 691 +| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)| 692 +|((( 683 683 ReportingDay 684 684 (YYYY-Dddd – 1 day period) 685 -)))| (% style="width:221px" %)time_period686 -|( % style="width:360px" %)(((695 +)))|time_period 696 +|((( 687 687 DateTime 688 688 (YYYY-MM-DDThh:mm:ss) 689 -)))| (% style="width:221px" %)date690 -|( % style="width:360px" %)(((699 +)))|date 700 +|((( 691 691 TimeRange 692 692 (YYYY-MM-DD(Thh:mm:ss)?/<duration>) 693 -)))| (% style="width:221px" %)time694 -|( % style="width:360px" %)(((703 +)))|time 704 +|((( 695 695 Month 696 696 (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States) 697 -)))| (%style="width:221px" %)string698 -|( % style="width:360px" %)(((707 +)))|string 708 +|((( 699 699 MonthDay 700 700 (~-~-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) 701 -)))| (%style="width:221px" %)string702 -|( % style="width:360px" %)(((711 +)))|string 712 +|((( 703 703 Day 704 704 (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday) 705 -)))| (%style="width:221px" %)string706 -|( % style="width:360px" %)(((715 +)))|string 716 +|((( 707 707 Time 708 708 (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM) 709 -)))| (%style="width:221px" %)string710 -|( % style="width:360px" %)(((719 +)))|string 720 +|((( 711 711 Duration 712 712 (corresponds to XML Schema xs:duration datatype) 713 -)))| (% style="width:221px" %)duration714 -| (% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable715 -| (% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable716 -| (% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable717 -| (% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable723 +)))|duration 724 +|XHTML|Metadata type – not applicable 725 +|KeyValues|Metadata type – not applicable 726 +|IdentifiableReference|Metadata type – not applicable 727 +|DataSetReference|Metadata type – not applicable 718 718 719 719 **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 720 720 ... ... @@ -724,82 +724,84 @@ 724 724 725 725 The following table describes the default conversion from the VTL basic scalar types to the SDMX data types . 726 726 727 -( % style="width:748.294px" %)728 - |(%style="width:164px" %)(((729 - VTL basicscalar type730 -)))|( % style="width:304px" %)(((737 +|((( 738 +VTL basic 739 +scalar type 740 +)))|((( 731 731 Default SDMX data type 732 -(BasicComponentDataType) 733 -)))|(% style="width:277px" %)Default output format 734 -|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string) 735 -|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float) 736 -|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int) 737 -|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z 738 -|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above) 739 -|(% style="width:164px" %)time_period|(% style="width:304px" %)((( 742 +(BasicComponentDataType 743 +) 744 +)))|Default output format 745 +|String|String|Like XML (xs:string) 746 +|Number|Float|Like XML (xs:float) 747 +|Integer|Integer|Like XML (xs:int) 748 +|Date|DateTime|YYYY-MM-DDT00:00:00Z 749 +|Time|StandardTimePeriod|<date>/<date> (as defined above) 750 +|time_period|((( 740 740 ReportingTimePeriod 741 741 (StandardReportingPeriod) 742 -)))|( % style="width:277px" %)(((753 +)))|((( 743 743 YYYY-Pppp 744 744 (according to SDMX ) 745 745 ))) 746 -| (% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS747 -| (% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"757 +|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS 758 +|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false" 748 748 749 749 **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 750 750 751 -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).762 +In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section 752 752 764 +Transformations and Expressions of the SDMX information model). 765 + 753 753 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. 754 754 755 -(% style="width:717.294px" %) 756 -|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks 757 -|(% colspan="2" style="width:714px" %) 758 -|(% colspan="2" style="width:714px" %)Number 759 -|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa) 760 -|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation) 761 -|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts. 762 -|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts. 763 -|(% style="width:122px" %) |(% style="width:591px" %) 764 -|(% colspan="2" style="width:714px" %)Time and duration 765 -|(% style="width:122px" %)C|(% style="width:591px" %)century 766 -|(% style="width:122px" %)Y|(% style="width:591px" %)year 767 -|(% style="width:122px" %)S|(% style="width:591px" %)semester 768 -|(% style="width:122px" %)Q|(% style="width:591px" %)quarter 769 -|(% style="width:122px" %)M|(% style="width:591px" %)month 770 -|(% style="width:122px" %)W|(% style="width:591px" %)week 771 -|(% style="width:122px" %)D|(% style="width:591px" %)day 772 -|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours) 773 -|(% style="width:122px" %)M|(% style="width:591px" %)minute 774 -|(% style="width:122px" %)S|(% style="width:591px" %)second 775 -|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second 776 -|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration) 777 -|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator 778 -|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm") 779 -|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January) 780 -|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday) 781 -|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january) 782 -|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday) 783 -|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January) 784 -|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday) 785 -|(% style="width:122px" %) |(% style="width:591px" %) 786 -|(% colspan="2" style="width:714px" %)String 787 -|(% style="width:122px" %)X|(% style="width:591px" %)any string character 788 -|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z" 789 -|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9" 790 -|(% style="width:122px" %) |(% style="width:591px" %) 791 -|(% colspan="2" style="width:714px" %)Boolean 792 -|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False 793 -|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False 794 -|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False 795 -|(% style="width:122px" %) |(% style="width:591px" %) 796 -|(% colspan="2" style="width:714px" %)Other qualifiers 797 -|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type) 798 -|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type) 799 -|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets) 800 -|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask 801 -|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day 802 -|(% style="width:122px" %) |(% style="width:591px" %) 768 +|(% colspan="2" %)VTL special characters for the formatting masks 769 +|(% colspan="2" %) 770 +|(% colspan="2" %)Number 771 +|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa) 772 +|E|one numeric digit (for the exponent of the scientific notation) 773 +|. (dot)|possible separator between the integer and the decimal parts. 774 +|, (comma)|possible separator between the integer and the decimal parts. 775 +| | 776 +|(% colspan="2" %)Time and duration 777 +|C|century 778 +|Y|year 779 +|S|semester 780 +|Q|quarter 781 +|M|month 782 +|W|week 783 +|D|day 784 +|h|hour digit (by default on 24 hours) 785 +|M|minute 786 +|S|second 787 +|D|decimal of second 788 +|P|period indicator (representation in one digit for the duration) 789 +|P|number of the periods specified in the period indicator 790 +|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm") 791 +|MONTH|uppercase textual representation of the month (e.g., JANUARY for January) 792 +|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday) 793 +|Month|lowercase textual representation of the month (e.g., january) 794 +|Day|lowercase textual representation of the month (e.g., monday) 795 +|Month|First character uppercase, then lowercase textual representation of the month (e.g., January) 796 +|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday) 797 +| | 798 +|(% colspan="2" %)String 799 +|X|any string character 800 +|Z|any string character from "A" to "z" 801 +|9|any string character from "0" to "9" 802 +| | 803 +|(% colspan="2" %)Boolean 804 +|B|Boolean using "true" for True and "false" for False 805 +|1|Boolean using "1" for True and "0" for False 806 +|0|Boolean using "0" for True and "1" for False 807 +| | 808 +|(% colspan="2" %)Other qualifiers 809 +|*|an arbitrary number of digits (of the preceding type) 810 +|+|at least one digit (of the preceding type) 811 +|( )|optional digits (specified within the brackets) 812 +|\|prefix for the special characters that must appear in the mask 813 +|N|fixed number of digits used in the preceding textual representation of the month or the day 814 +| | 803 803 804 804 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}}. 805 805
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