Changes for page 12 Validation and Transformation Language (VTL)
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... ... @@ -118,7 +118,7 @@ 118 118 119 119 'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)' 120 120 121 -if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply ^^19^^:121 +if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply{{footnote}}Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}: 122 122 123 123 CL_FREQ 124 124 ... ... @@ -132,7 +132,7 @@ 132 132 133 133 SECTOR 134 134 135 -For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as{{footnote}} Singlequotesarenotneededinthis casebecause CL_FREQis aVTL regular name.{{/footnote}}:135 +For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as{{footnote}}The result DFR(1.0.0) is be equal to DF1(1.0.0) save that the component SECTOR is called SEC{{/footnote}}: 136 136 137 137 'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC] 138 138 ... ... @@ -164,9 +164,9 @@ 164 164 165 165 The VTL Rulesets have a signature, in which the Value Domains or the Variables on which the Ruleset is defined are declared, and a body, which contains the Rules. 166 166 167 -In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist, while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink" %)^^18^^>>path:#sdfootnote18sym||name="sdfootnote18anc"]](%%)^^.167 +In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist, while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation{{footnote}}Rulesets of this kind cannot be reused when the referenced Concept has a different representation.{{/footnote}}. 168 168 169 -In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called "valueDomain" and "variable" for the Datapoint Rulesets and "ruleValueDomain", "ruleVariable", "condValueDomain" "condVariable" for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific Ruleset definition statement and cannot be mapped to SDMX. ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^19^^>>path:#sdfootnote19sym||name="sdfootnote19anc"]](%%)^^169 +In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called "valueDomain" and "variable" for the Datapoint Rulesets and "ruleValueDomain", "ruleVariable", "condValueDomain" "condVariable" for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific Ruleset definition statement and cannot be mapped to SDMX.{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} 170 170 171 171 In the body of the Rulesets, the Codes and in general all the Values can be written without any other specification, because the artefact, which the Values are referred (Codelist, Concept) to can be deduced from the Ruleset signature. 172 172 ... ... @@ -178,15 +178,15 @@ 178 178 179 179 Every time a SDMX object is referenced in a VTL Transformation as an input operand, there is the need to generate a VTL definition of the object, so that the VTL operations can take place. This can be made starting from the SDMX definition and applying a SDMX-VTL mapping method in the direction from SDMX to VTL. The possible mapping methods from SDMX to VTL are described in the following paragraphs and are conceived to allow the automatic deduction of the VTL definition of the object from the knowledge of the SDMX definition. 180 180 181 -In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged ^^[[(%class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^20^^>>path:#sdfootnote20sym||name="sdfootnote20anc"]](%%)^^.181 +In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged{{footnote}}If a calculated artefact is persistent, it needs a persistent definition, i.e. a SDMX definition in a SDMX environment. In addition, possible calculated artefact that are not persistent may require a SDMX definition, for example when the result of a non-persistent calculation is disseminated through SDMX tools (like an inquiry tool).{{/footnote}}. 182 182 183 183 The mapping methods from VTL to SDMX are described in the following paragraphs as well, however they do not allow the complete SDMX definition to be automatically deduced from the VTL definition, more than all because the former typically contains additional information in respect to the latter. For example, the definition of a SDMX DSD includes also some mandatory information not available in VTL (like the concept scheme to which the SDMX components refer, the ‘usage’ and ‘attributeRelationship’ for the DataAttributes and so on). Therefore the mapping methods from VTL to SDMX provide only a general guidance for generating SDMX definitions properly starting from the information available in VTL, independently of how the SDMX definition it is actually generated (manually, automatically or part and part). 184 184 185 185 === 12.3.2 General mapping of VTL and SDMX data structures === 186 186 187 -This section makes reference to the VTL "Model for data and their structure" ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^21^^>>path:#sdfootnote21sym||name="sdfootnote21anc"]](%%)^^and the correspondent SDMX "Data Structure Definition"^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink" %)^^22^^>>path:#sdfootnote22sym||name="sdfootnote22anc"]](%%)^^.187 +This section makes reference to the VTL "Model for data and their structure"{{footnote}}See the VTL 2.0 User Manual{{/footnote}} and the correspondent SDMX "Data Structure Definition"{{footnote}}See the SDMX Standards Section 2 – Information Model{{/footnote}}. 188 188 189 -The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived). ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^23^^>>path:#sdfootnote23sym||name="sdfootnote23anc"]](%%)^^189 +The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).{{footnote}}Besides the mapping between one SDMX Dataflow and one VTL Data Set, it is also possible to map distinct parts of a SDMX Dataflow to different VTL Data Set, as explained in a following paragraph.{{/footnote}} 190 190 191 191 While the VTL Transformations are defined in term of Dataflow definitions, they are assumed to be executed on instances of such Dataflows, provided at runtime to the VTL engine (the mechanism for identifying the instances to be processed are not part of the VTL specifications and depend on the implementation of the VTL-based systems). As already said, the SDMX Datasets are instances of SDMX Dataflows, therefore a VTL Transformation defined on some SDMX Dataflows can be applied on some corresponding SDMX Datasets. 192 192 ... ... @@ -206,32 +206,28 @@ 206 206 207 207 The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes. When transforming **from SDMX to VTL**, this method consists in leaving the components unchanged and maintaining their names and roles, according to the following table: 208 208 209 -|**SDMX**|**VTL** 210 -|Dimension|(Simple) Identifier 211 -|TimeDimension|(Time) Identifier 209 +(% style="width:529.294px" %) 210 +|(% style="width:151px" %)**SDMX**|(% style="width:375px" %)**VTL** 211 +|(% style="width:151px" %)Dimension|(% style="width:375px" %)(Simple) Identifier 212 +|(% style="width:151px" %)TimeDimension|(% style="width:375px" %)(Time) Identifier 213 +|(% style="width:151px" %)Measure|(% style="width:375px" %)Measure 214 +|(% style="width:151px" %)DataAttribute|(% style="width:375px" %)Attribute 212 212 213 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape4" height="1" width="192"]] 214 - 215 -|Measure|Measure 216 -|DataAttribute|Attribute 217 - 218 218 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). 219 219 220 -With the Basic mapping, one SDMX observation ^^27^^generates one VTL data point.218 +With the Basic mapping, one SDMX observation{{footnote}}Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.{{/footnote}} generates one VTL data point. 221 221 222 - **12.3.3.2 Pivot Mapping**220 +==== 12.3.3.2 Pivot Mapping ==== 223 223 224 224 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. 225 225 226 -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}}. 227 227 228 -MeasureDimensions considered as a joint variable^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^24^^>>path:#sdfootnote24sym||name="sdfootnote24anc"]](%%)^^. 229 - 230 230 Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension. 231 231 232 232 If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph). 233 233 234 - ^^27^^Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.230 +Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents. 235 235 236 236 The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation): 237 237 ... ... @@ -253,19 +253,16 @@ 253 253 254 254 The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following: 255 255 256 -|**SDMX**|**VTL** 257 -|Dimension|(Simple) Identifier 258 -|TimeDimension|(Time) Identifier 259 -|MeasureDimension & one Measure|((( 260 -One Measure for each Code of the 261 - 262 -SDMX MeasureDimension 252 +(% style="width:769.294px" %) 253 +|(% style="width:401px" %)**SDMX**|(% style="width:366px" %)**VTL** 254 +|(% style="width:401px" %)Dimension|(% style="width:366px" %)(Simple) Identifier 255 +|(% style="width:401px" %)TimeDimension|(% style="width:366px" %)(Time) Identifier 256 +|(% style="width:401px" %)MeasureDimension & one Measure|(% style="width:366px" %)((( 257 +One Measure for each Code of the SDMX MeasureDimension 263 263 ))) 264 -|DataAttribute not depending on the MeasureDimension|Attribute 265 -|DataAttribute depending on the MeasureDimension|((( 266 -One Attribute for each Code of the 267 - 268 -SDMX MeasureDimension 259 +|(% style="width:401px" %)DataAttribute not depending on the MeasureDimension|(% style="width:366px" %)Attribute 260 +|(% style="width:401px" %)DataAttribute depending on the MeasureDimension|(% style="width:366px" %)((( 261 +One Attribute for each Code of the SDMX MeasureDimension 269 269 ))) 270 270 271 271 Using this mapping method, the components of the data structure can change in the conversion from SDMX to VTL and it must be taken into account that the VTL statements can reference only the components of the resulting VTL data structure. ... ... @@ -280,7 +280,7 @@ 280 280 * 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 281 281 * 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 282 282 283 - **12.3.3.3 From SDMX DataAttributes to VTL Measures**276 +==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ==== 284 284 285 285 * 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 286 286 ... ... @@ -292,7 +292,7 @@ 292 292 293 293 === 12.3.4 Mapping from VTL to SDMX data structures === 294 294 295 - **12.3.4.1 Basic Mapping**288 +==== 12.3.4.1 Basic Mapping ==== 296 296 297 297 The main mapping method **from VTL to SDMX** is called **Basic **mapping as well. 298 298 ... ... @@ -302,11 +302,12 @@ 302 302 303 303 Mapping table: 304 304 305 -|**VTL**|**SDMX** 306 -|(Simple) Identifier|Dimension 307 -|(Time) Identifier|TimeDimension 308 -|Measure|Measure 309 -|Attribute|DataAttribute 298 +(% style="width:667.294px" %) 299 +|(% style="width:272px" %)**VTL**|(% style="width:392px" %)**SDMX** 300 +|(% style="width:272px" %)(Simple) Identifier|(% style="width:392px" %)Dimension 301 +|(% style="width:272px" %)(Time) Identifier|(% style="width:392px" %)TimeDimension 302 +|(% style="width:272px" %)Measure|(% style="width:392px" %)Measure 303 +|(% style="width:272px" %)Attribute|(% style="width:392px" %)DataAttribute 310 310 311 311 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. 312 312 ... ... @@ -316,7 +316,7 @@ 316 316 317 317 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. 318 318 319 - **12.3.4.2 Unpivot Mapping**313 +==== 12.3.4.2 Unpivot Mapping ==== 320 320 321 321 An alternative mapping method from VTL to SDMX is the **Unpivot **mapping. 322 322 ... ... @@ -340,11 +340,12 @@ 340 340 341 341 The summary mapping table of the **unpivot** mapping method is the following: 342 342 343 -|**VTL**|**SDMX** 344 -|(Simple) Identifier|Dimension 345 -|(Time) Identifier|TimeDimension 346 -|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure 347 -|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension 337 +(% style="width:994.294px" %) 338 +|(% style="width:306px" %)**VTL**|(% style="width:684px" %)**SDMX** 339 +|(% style="width:306px" %)(Simple) Identifier|(% style="width:684px" %)Dimension 340 +|(% style="width:306px" %)(Time) Identifier|(% style="width:684px" %)TimeDimension 341 +|(% style="width:306px" %)All Measure Components|(% style="width:684px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure 342 +|(% style="width:306px" %)Attribute|(% style="width:684px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension 348 348 349 349 At observation / data point level: 350 350 ... ... @@ -358,7 +358,7 @@ 358 358 359 359 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. 360 360 361 - **12.3.4.3 From VTL Measures to SDMX Data Attributes**356 +==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ==== 362 362 363 363 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”). 364 364 ... ... @@ -366,12 +366,13 @@ 366 366 367 367 The mapping table is the following: 368 368 369 -|VTL|SDMX 370 -|(Simple) Identifier|Dimension 371 -|(Time) Identifier|TimeDimension 372 -|Some Measures|Measure 373 -|Other Measures|DataAttribute 374 -|Attribute|DataAttribute 364 +(% style="width:689.294px" %) 365 +|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX 366 +|(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension 367 +|(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension 368 +|(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure 369 +|(% style="width:344px" %)Other Measures|(% style="width:341px" %)DataAttribute 370 +|(% style="width:344px" %)Attribute|(% style="width:341px" %)DataAttribute 375 375 376 376 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. 377 377 ... ... @@ -389,20 +389,20 @@ 389 389 390 390 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). 391 391 392 -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. ^^[[(%class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^25^^>>path:#sdfootnote25sym||name="sdfootnote25anc"]](%%)^^388 +As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.{{footnote}}A typical example of this kind is the validation, and more in general the manipulation, of individual time series belonging to the same Dataflow, identifiable through the DimensionComponents of the Dataflow except the TimeDimension. The coding of these kind of operations might be simplified by mapping distinct time series (i.e. different parts of a SDMX Dataflow) to distinct VTL Data Sets.{{/footnote}} 393 393 394 -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="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink"%)^^26^^>>path:#sdfootnote26sym||name="sdfootnote26anc"]](%%)^^390 +Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL Data Sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.{{footnote}}Please note that this kind of mapping is only an option at disposal of the definer of VTL Transformations; in fact it remains always possible to manipulate the needed parts of SDMX Dataflows by means of VTL operators (e.g. “sub”, “filter”, “calc”, “union” …), maintaining a mapping one-to-one between SDMX Dataflows and VTL Data Sets.{{/footnote}} 395 395 396 396 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. 397 397 398 398 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: 399 399 400 -* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order. ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^27^^>>path:#sdfootnote27sym||name="sdfootnote27anc"]](%%)^^Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.396 +* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order.{{footnote}}This definition is made through the ToVtlSubspace and ToVtlSpaceKey classes and/or the FromVtlSuperspace and FromVtlSpaceKey classes, depending on the direction of the mapping (“key” means “dimension”). The mapping of Dataflow subsets can be applied independently in the two directions, also according to different Dimensions. When no Dimension is declared for a given direction, it is assumed that the option of mapping different parts of a SDMX Dataflow to different VTL Data Sets is not used.{{/footnote}} Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY. 401 401 * The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts: 402 402 ** 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); 403 -** a slash (“/”) as a separator; ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^28^^>>path:#sdfootnote28sym||name="sdfootnote28anc"]](%%)^^399 +** a slash (“/”) as a separator;{{footnote}}As a consequence of this formalism, a slash in the name of the VTL Data Set assumes the specific meaning of separator between the name of the Dataflow and the values of some of its Dimensions.{{/footnote}} 404 404 405 -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="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^29^^>>path:#sdfootnote29sym||name="sdfootnote29anc"]](%%)^^. For example POPULATION.USA would mean that such a VTL Data Set is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.401 +The reference to a specific part of the SDMX Dataflow above, expressed as the concatenation of the values that the SDMX DimensionComponents declared above must have, separated by dots (“.”) and written in the order in which these DimensionComponents are defined{{footnote}}This is the order in which the dimensions are defined in the ToVtlSpaceKey class or in the FromVtlSpaceKey class, depending on the direction of the mapping.{{/footnote}}. For example POPULATION.USA would mean that such a VTL Data Set is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA. 406 406 407 407 In the VTL Transformations, this kind of dataset name must be referenced between single quotes because the slash (“/”) is not a regular character according to the VTL rules. 408 408 ... ... @@ -418,7 +418,7 @@ 418 418 419 419 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. 420 420 421 -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="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallink" %)^^30^^>>path:#sdfootnote30sym||name="sdfootnote30anc"]](%%)^^need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively.417 +As already said, the mapping from SDMX to VTL happens when the SDMX dataflows are operand of VTL Transformations, instead the mapping from VTL to SDMX happens when the VTL Data Sets that is result of Transformations{{footnote}}It should be remembered that, according to the VTL consistency rules, a given VTL dataset cannot be the result of more than one VTL Transformation.{{/footnote}} need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively. 422 422 423 423 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. 424 424 ... ... @@ -426,7 +426,7 @@ 426 426 427 427 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. 428 428 429 -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="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink" %)^^31^^>>path:#sdfootnote31sym||name="sdfootnote31anc"]](%%)^^. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.425 +In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. 430 430 431 431 basic, pivot …). 432 432 ... ... @@ -446,7 +446,7 @@ 446 446 447 447 … … … 448 448 449 -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="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^32^^>>path:#sdfootnote32sym||name="sdfootnote32anc"]](%%)^^445 +In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}} 450 450 451 451 In the direction from SDMX to VTL it is allowed to omit the value of one or more 452 452 ... ... @@ -474,12 +474,12 @@ 474 474 475 475 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: 476 476 477 -* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation; ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^33^^>>path:#sdfootnote33sym||name="sdfootnote33anc"]](%%)^^478 -* the data structure of all these VTL Data Sets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers. ^^[[(% class="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^34^^>>path:#sdfootnote34sym||name="sdfootnote34anc"]](%%)^^473 +* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation;{{footnote}}If the whole DF2(1.0) is calculated by means of just one VTL Transformation, then the mapping between the SDMX Dataflow and the corresponding VTL dataset is one-to-one and this kind of mapping (one SDMX Dataflow to many VTL datasets) does not apply.{{/footnote}} 474 +* the data structure of all these VTL Data Sets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.{{footnote}}This is possible as each VTL dataset corresponds to one particular combination of values of INDICATOR and COUNTRY.{{/footnote}} 479 479 480 -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="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink"%)^^35^^>>path:#sdfootnote35sym||name="sdfootnote35anc"]](%%)^^.476 +Under these hypothesis, such derived VTL Data Sets can be mapped to DF2(1.0.0) by declaring the DimensionComponents INDICATOR and COUNTRY as mapping dimensions{{footnote}}The mapping dimensions are defined as FromVtlSpaceKeys of the FromVtlSuperSpace of the VtlDataflowMapping relevant to DF2(1.0).{{/footnote}}. 481 481 482 -The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind: ^^ [[(% class="wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink" %)^^36^^>>path:#sdfootnote36sym||name="sdfootnote36anc"]](%%)^^478 +The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:{{footnote}}the symbol of the VTL persistent assignment is used (<-){{/footnote}} 483 483 484 484 ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression 485 485 ... ... @@ -535,9 +535,9 @@ 535 535 536 536 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 537 537 538 -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 wikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink" %)^^37^^>>path:#sdfootnote37sym||name="sdfootnote37anc"]](%%)^^, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.534 +DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY. 539 539 540 -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="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink" %)^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]](%%)[[(%class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^39^^>>path:#sdfootnote39sym||name="sdfootnote39anc"]](%%)^^536 +Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets.{{footnote}}In case the ordered concatenation notation from VTL to SDMX is used, the set of Transformations described above is implicitly performed; therefore, in order to test the overall compliance of the VTL program to the VTL consistency rules, these implicit Transformations have to be considered as part of the VTL program even if they are not explicitly coded.{{/footnote}}{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}} 541 541 542 542 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). 543 543 ... ... @@ -545,43 +545,42 @@ 545 545 546 546 With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered: 547 547 548 -|VTL|SDMX 549 -|**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^^ 550 -|**Represented Variable**|((( 544 +(% style="width:1170.29px" %) 545 +|**VTL**|(% style="width:754px" %)**SDMX** 546 +|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}} 547 +|**Represented Variable**|(% style="width:754px" %)((( 551 551 **Concept** with a definite 552 552 553 553 Representation 554 554 ))) 555 -|**Value Domain**|((( 552 +|**Value Domain**|(% style="width:754px" %)((( 556 556 **Representation** (see the Structure 557 557 558 558 Pattern in the Base Package) 559 559 ))) 560 -|**Enumerated Value Domain / Code List**|**Codelist** 561 -|**Code**|((( 557 +|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist** 558 +|**Code**|(% style="width:754px" %)((( 562 562 **Code** (for enumerated 563 563 564 564 DimensionComponent, Measure, DataAttribute) 565 565 ))) 566 -|**Described Value Domain**|((( 567 -non-enumerated** Representation**563 +|**Described Value Domain**|(% style="width:754px" %)((( 564 +non-enumerated** Representation** 568 568 569 569 (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package) 570 570 ))) 571 -|**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 572 -| |((( 573 -to a valid **value **(for non-enumerated** ** 574 - 575 -Representations) 568 +|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or 569 +| |(% style="width:754px" %)((( 570 +to a valid **value **(for non-enumerated** **Representations) 576 576 ))) 577 -|**Value Domain Subset / Set**|This abstraction does not exist in SDMX 578 -|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX 579 -|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX 580 -|**Set list**|This abstraction does not exist in SDMX 572 +|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX 573 +|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX 574 +|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX 575 +|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX 581 581 582 582 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). 583 583 584 -Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^40^^>>path:#sdfootnote40sym||name="sdfootnote40anc"]](%%)^^, while the SDMX Concepts can have different Representations in different DataStructures.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has. 579 +Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^40^^>>path:#sdfootnote40sym||name="sdfootnote40anc"]](%%)^^, while the SDMX Concepts can have different Representations in different DataStructures.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has. 585 585 586 586 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 587 587 ... ... @@ -1050,7 +1050,7 @@ 1050 1050 |N|fixed number of digits used in the preceding textual representation of the month or the day 1051 1051 | | 1052 1052 1053 -The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^. 1048 +The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^. 1054 1054 1055 1055 === 12.4.5 Null Values === 1056 1056