Changes for page 12 Validation and Transformation Language (VTL)
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... ... @@ -215,19 +215,21 @@ 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). 217 217 218 -With the Basic mapping, one SDMX observation {{footnote}}Herean SDMX observation is meant to correspond to one combination of values of the DimensionComponents.{{/footnote}}generates one VTL data point.218 +With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point. 219 219 220 220 ==== 12.3.3.2 Pivot Mapping ==== 221 221 222 222 An alternative mapping method from SDMX to VTL is the **Pivot **mapping, which makes sense and is different from the Basic method only for the SDMX data structures that contain a Dimension that plays the role of measure dimension (like in SDMX 2.1) and just one Measure. Through this method, these structures can be mapped to multimeasure VTL data structures. Besides that, a user may choose to use any Dimension acting as a list of Measures (e.g., a Dimension with indicators), either by considering the “Measure” role of a Dimension, or at will using any coded Dimension. Of course, in SDMX 3.0, this can only work when only one Measure is defined in the DSD. 223 223 224 -In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.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^^[[(% 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" %)^^24^^>>path:#sdfootnote24sym||name="sdfootnote24anc"]](%%)^^. 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). 229 229 230 -Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents. 232 +^^27^^ Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents. 231 231 232 232 The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation): 233 233 ... ... @@ -249,16 +249,19 @@ 249 249 250 250 The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following: 251 251 252 -(% style="width:769.294px" %) 253 -|(% style="width:401px" %)**SDMX**|(% style="width:366px" %)**VTL** 254 -|(% style="width:401px" %)Dimension|(% style="width:366px" %)(Simple) Identifier 255 -|(% style="width:401px" %)TimeDimension|(% style="width:366px" %)(Time) Identifier 256 -|(% style="width:401px" %)MeasureDimension & one Measure|(% style="width:366px" %)((( 257 -One Measure for each Code of the SDMX MeasureDimension 254 +|**SDMX**|**VTL** 255 +|Dimension|(Simple) Identifier 256 +|TimeDimension|(Time) Identifier 257 +|MeasureDimension & one Measure|((( 258 +One Measure for each Code of the 259 + 260 +SDMX MeasureDimension 258 258 ))) 259 -|(% style="width:401px" %)DataAttribute not depending on the MeasureDimension|(% style="width:366px" %)Attribute 260 -|(% style="width:401px" %)DataAttribute depending on the MeasureDimension|(% style="width:366px" %)((( 261 -One Attribute for each Code of the SDMX MeasureDimension 262 +|DataAttribute not depending on the MeasureDimension|Attribute 263 +|DataAttribute depending on the MeasureDimension|((( 264 +One Attribute for each Code of the 265 + 266 +SDMX MeasureDimension 262 262 ))) 263 263 264 264 Using this mapping method, the components of the data structure can change in the conversion from SDMX to VTL and it must be taken into account that the VTL statements can reference only the components of the resulting VTL data structure. ... ... @@ -273,7 +273,7 @@ 273 273 * The value of the Measure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj 274 274 * For the SDMX DataAttributes depending on the MeasureDimension, the value of the DataAttribute DA of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Attribute DA_Cj 275 275 276 - ====12.3.3.3 From SDMX DataAttributes to VTL Measures====281 +**12.3.3.3 From SDMX DataAttributes to VTL Measures** 277 277 278 278 * In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain 279 279 ... ... @@ -285,7 +285,7 @@ 285 285 286 286 === 12.3.4 Mapping from VTL to SDMX data structures === 287 287 288 - ====12.3.4.1 Basic Mapping====293 +**12.3.4.1 Basic Mapping** 289 289 290 290 The main mapping method **from VTL to SDMX** is called **Basic **mapping as well. 291 291 ... ... @@ -295,12 +295,11 @@ 295 295 296 296 Mapping table: 297 297 298 -(% style="width:667.294px" %) 299 -|(% style="width:272px" %)**VTL**|(% style="width:392px" %)**SDMX** 300 -|(% style="width:272px" %)(Simple) Identifier|(% style="width:392px" %)Dimension 301 -|(% style="width:272px" %)(Time) Identifier|(% style="width:392px" %)TimeDimension 302 -|(% style="width:272px" %)Measure|(% style="width:392px" %)Measure 303 -|(% style="width:272px" %)Attribute|(% style="width:392px" %)DataAttribute 303 +|**VTL**|**SDMX** 304 +|(Simple) Identifier|Dimension 305 +|(Time) Identifier|TimeDimension 306 +|Measure|Measure 307 +|Attribute|DataAttribute 304 304 305 305 If the distinction between simple identifier and time identifier is not maintained in the VTL environment, the classification between Dimension and TimeDimension exists only in SDMX, as declared in the relevant DataStructureDefinition. 306 306 ... ... @@ -310,7 +310,7 @@ 310 310 311 311 As said, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the AttributeRelationship for the DataAttributes, which does not exist in VTL. 312 312 313 - ====12.3.4.2 Unpivot Mapping====317 +**12.3.4.2 Unpivot Mapping** 314 314 315 315 An alternative mapping method from VTL to SDMX is the **Unpivot **mapping. 316 316 ... ... @@ -334,12 +334,11 @@ 334 334 335 335 The summary mapping table of the **unpivot** mapping method is the following: 336 336 337 -(% style="width:994.294px" %) 338 -|(% style="width:306px" %)**VTL**|(% style="width:684px" %)**SDMX** 339 -|(% style="width:306px" %)(Simple) Identifier|(% style="width:684px" %)Dimension 340 -|(% style="width:306px" %)(Time) Identifier|(% style="width:684px" %)TimeDimension 341 -|(% style="width:306px" %)All Measure Components|(% style="width:684px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure 342 -|(% style="width:306px" %)Attribute|(% style="width:684px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension 341 +|**VTL**|**SDMX** 342 +|(Simple) Identifier|Dimension 343 +|(Time) Identifier|TimeDimension 344 +|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure 345 +|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension 343 343 344 344 At observation / data point level: 345 345 ... ... @@ -353,7 +353,7 @@ 353 353 354 354 In any case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the possible Codes of the SDMX MeasureDimension need to be listed in a SDMX Codelist, with proper id, agency and version; moreover, the SDMX DSD must have the AttributeRelationship for the DataAttributes, which does not exist in VTL. 355 355 356 - ====12.3.4.3 From VTL Measures to SDMX Data Attributes====359 +**12.3.4.3 From VTL Measures to SDMX Data Attributes** 357 357 358 358 More than all for the multi-measure VTL structures (having more than one Measure Component), it may happen that the Measures of the VTL Data Structure need to be managed as DataAttributes in SDMX. Therefore, a third mapping method consists in transforming some VTL measures in a corresponding SDMX Measures and all the other VTL Measures in SDMX DataAttributes. This method is called M2A (“M2A” stands for “Measures to DataAttributes”). 359 359 ... ... @@ -361,13 +361,12 @@ 361 361 362 362 The mapping table is the following: 363 363 364 -(% style="width:689.294px" %) 365 -|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX 366 -|(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension 367 -|(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension 368 -|(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure 369 -|(% style="width:344px" %)Other Measures|(% style="width:341px" %)DataAttribute 370 -|(% style="width:344px" %)Attribute|(% style="width:341px" %)DataAttribute 367 +|VTL|SDMX 368 +|(Simple) Identifier|Dimension 369 +|(Time) Identifier|TimeDimension 370 +|Some Measures|Measure 371 +|Other Measures|DataAttribute 372 +|Attribute|DataAttribute 371 371 372 372 Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the attributeRelationship for the DataAttributes, which does not exist in VTL. 373 373 ... ... @@ -385,20 +385,20 @@ 385 385 386 386 Until now it has been assumed to map one SMDX Dataflow to one VTL Data Set and vice-versa. This mapping one-to-one is not mandatory according to VTL because a VTL Data Set is meant to be a set of observations (data points) on a logical plane, having the same logical data structure and the same general meaning, independently of the possible physical representation or storage (see VTL 2.0 User Manual page 24), therefore a SDMX Dataflow can be seen either as a unique set of data observations (corresponding to one VTL Data Set) or as the union of many sets of data observations (each one corresponding to a distinct VTL Data Set). 387 387 388 -As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole. {{footnote}}A typical example of thiskindisthevalidation,and moreingeneral themanipulation,ofindividualtimeseriesbelongingto thesameDataflow,identifiablethroughtheDimensionComponentsoftheDataflowexcepttheTimeDimension.The coding ofthesekind of operationsmightbesimplified by mappingdistincttimeseries(i.e. differentpartsofa SDMX Dataflow) todistinctVTL Data Sets.{{/footnote}}390 +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="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" %)^^25^^>>path:#sdfootnote25sym||name="sdfootnote25anc"]](%%)^^ 389 389 390 -Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL Data Sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below. {{footnote}}Pleasenotethat thiskind of mappingis onlyanoptionatdisposalofthedefinerof VTL Transformations;infact itremainsalwayspossible to manipulate the needed parts of SDMX Dataflowsby meansof VTL operators(e.g. “sub”, “filter”, “calc”,“union”…), maintainingamappingone-to-onebetweenSDMX Dataflowsand VTL Data Sets.{{/footnote}}392 +Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL Data Sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^26^^>>path:#sdfootnote26sym||name="sdfootnote26anc"]](%%)^^ 391 391 392 392 Given a SDMX Dataflow and some predefined Dimensions of its DataStructure, it is allowed to map the subsets of observations that have the same combination of values for such Dimensions to correspondent VTL datasets. 393 393 394 394 For example, assuming that the SDMX Dataflow DF1(1.0.0) has the Dimensions INDICATOR, TIME_PERIOD and COUNTRY, and that the user declares the Dimensions INDICATOR and COUNTRY as basis for the mapping (i.e. the mapping dimensions): the observations that have the same values for INDICATOR and COUNTRY would be mapped to the same VTL dataset (and vice-versa). In practice, this kind mapping is obtained like follows: 395 395 396 -* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order. {{footnote}}Thisdefinition is madethroughtheToVtlSubspace andToVtlSpaceKey classes and/ortheFromVtlSuperspace andFromVtlSpaceKey classes, dependingonthedirectionofthemapping(“key” means“dimension”).Themappingof Dataflowsubsets canbeappliedindependentlyinthe two directions,also accordingto differentDimensions.WhennoDimension is declared foragivendirection,itis assumedthat theoptionof mappingdifferentpartsofa SDMX Dataflow todifferentVTL Data Sets isnotused.{{/footnote}}Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.398 +* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order.^^[[(% 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" %)^^27^^>>path:#sdfootnote27sym||name="sdfootnote27anc"]](%%)^^ Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY. 397 397 * The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts: 398 398 ** The reference to the SDMX Dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated URN or another alias); for example DF(1.0.0); 399 -** a slash (“/”) as a separator; {{footnote}}Asaconsequenceofthisformalism,aslashin thenameoftheVTL DataSetassumesthespecific meaningof separatorbetween thenameoftheDataflow andthevaluesof someofitsDimensions.{{/footnote}}401 +** a slash (“/”) as a separator; ^^[[(% 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" %)^^28^^>>path:#sdfootnote28sym||name="sdfootnote28anc"]](%%)^^ 400 400 401 -The reference to a specific part of the SDMX Dataflow above, expressed as the concatenation of the values that the SDMX DimensionComponents declared above must have, separated by dots (“.”) and written in the order in which these DimensionComponents are defined {{footnote}}Thisistheorderin whichthedimensionsaredefinedin theToVtlSpaceKey classor in theFromVtlSpaceKeyclass,dependingon thedirectionofthemapping.{{/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.403 +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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^29^^>>path:#sdfootnote29sym||name="sdfootnote29anc"]](%%)^^. For example POPULATION.USA would mean that such a VTL Data Set is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA. 402 402 403 403 In the VTL Transformations, this kind of dataset name must be referenced between single quotes because the slash (“/”) is not a regular character according to the VTL rules. 404 404 ... ... @@ -414,7 +414,7 @@ 414 414 415 415 Let us now analyse the different meaning of this kind of mapping in the two mapping directions, i.e. from SDMX to VTL and from VTL to SDMX. 416 416 417 -As already said, the mapping from SDMX to VTL happens when the SDMX dataflows are operand of VTL Transformations, instead the mapping from VTL to SDMX happens when the VTL Data Sets that is result of Transformations {{footnote}}It shouldberememberedthat,accordingtotheVTL consistencyrules,agivenVTL datasetcannotbe the resultof more thanoneVTL 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.419 +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="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" %)^^30^^>>path:#sdfootnote30sym||name="sdfootnote30anc"]](%%)^^ need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively. 418 418 419 419 First, let us see what happens in the __mapping direction from SDMX to VTL__, i.e. when parts of a SDMX Dataflow (e.g. DF1(1.0.0)) need to be mapped to distinct VTL Data Sets that are operand of some VTL Transformations. 420 420 ... ... @@ -422,7 +422,7 @@ 422 422 423 423 SDMX Dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=// COUNTRYvalue//. For example, the VTL dataset ‘DF1(1.0.0)/POPULATION.USA’ would contain all the observations of DF1(1.0.0) having INDICATOR = POPULATION and COUNTRY = USA. 424 424 425 -In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets {{footnote}}Ifthese DimensionComponents wouldnotbedropped, the variousVTL Data Setsresultingfrom thiskind of mappingwould havenon-matching values for the Identifiers correspondingto themappingDimensions (e.g. POPULATIONandCOUNTRY). As a consequence, takingintoaccountthat thetypicalbinaryVTL operationsatdatasetlevel(+, -, *, / andso on) are executed on theobservationshaving matching valuesfortheidentifiers,itwouldnotbepossibleto composetheresultingVTL datasets oneanother(e.g.itwouldnotbepossibleto calculatethepopulationratiobetweenUSAandCANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.427 +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="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" %)^^31^^>>path:#sdfootnote31sym||name="sdfootnote31anc"]](%%)^^. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. 426 426 427 427 basic, pivot …). 428 428 ... ... @@ -442,7 +442,7 @@ 442 442 443 443 … … … 444 444 445 -In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow. {{footnote}}Incasetheordered concatenation notation is used,theVTL Transformationdescribedabove, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”],isimplicitlyexecuted. Inorder to testtheoverallcomplianceoftheVTL programto theVTL consistencyrules,ithasto beconsideredaspartof theVTL programevenifitisnotexplicitlycoded.{{/footnote}}447 +In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow. ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^32^^>>path:#sdfootnote32sym||name="sdfootnote32anc"]](%%)^^ 446 446 447 447 In the direction from SDMX to VTL it is allowed to omit the value of one or more 448 448 ... ... @@ -470,12 +470,12 @@ 470 470 471 471 Dataflow DF2(1.0.0) having the Dimensions TIME_PERIOD, INDICATOR, and COUNTRY and that such a programmer finds it convenient to calculate separately the parts of DF2(1.0.0) that have different combinations of values for INDICATOR and COUNTRY: 472 472 473 -* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation; {{footnote}}Ifthe wholeDF2(1.0)iscalculatedby meansof justoneVTL Transformation,then themappingbetween theSDMX DataflowandthecorrespondingVTL datasetisone-to-oneandthiskind of mapping(oneSDMX Dataflow tomanyVTL datasets)doesnotapply.{{/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}}Thisispossible aseachVTL datasetcorrespondstooneparticularcombinationof valuesof INDICATORandCOUNTRY.{{/footnote}}475 +* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation; ^^[[(% 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" %)^^33^^>>path:#sdfootnote33sym||name="sdfootnote33anc"]](%%)^^ 476 +* 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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^34^^>>path:#sdfootnote34sym||name="sdfootnote34anc"]](%%)^^ 475 475 476 -Under these hypothesis, such derived VTL Data Sets can be mapped to DF2(1.0.0) by declaring the DimensionComponents INDICATOR and COUNTRY as mapping dimensions {{footnote}}The mappingdimensionsaredefinedasFromVtlSpaceKeysoftheFromVtlSuperSpaceoftheVtlDataflowMappingrelevant toDF2(1.0).{{/footnote}}.478 +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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^35^^>>path:#sdfootnote35sym||name="sdfootnote35anc"]](%%)^^. 477 477 478 -The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind: {{footnote}}thesymboloftheVTLpersistent assignment isused(<-){{/footnote}}480 +The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:^^ [[(% 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" %)^^36^^>>path:#sdfootnote36sym||name="sdfootnote36anc"]](%%)^^ 479 479 480 480 ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression 481 481 ... ... @@ -531,9 +531,9 @@ 531 531 532 532 In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example 533 533 534 -DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0) {{footnote}}The result ispersistent in thisexamplebut itcanbe alsononpersistent ifneeded.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.536 +DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0)^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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. 535 535 536 -Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. {{footnote}}Incase theordered concatenation notationfromVTLto SDMXisused,thesetof Transformationsdescribedaboveisimplicitlyperformed;therefore,inorder totesttheoverallcomplianceoftheVTL programtothe VTL consistencyrules,theseimplicitTransformationshave to beconsideredaspartoftheVTL programevenifthey arenotexplicitlycoded.{{/footnote}}{{footnote}}ThroughSDMX Constraints,itispossible to specifythevaluesthataComponent ofaDataflowcan assume.{{/footnote}}538 +Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]](%%)[[(% 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" %)^^39^^>>path:#sdfootnote39sym||name="sdfootnote39anc"]](%%)^^ 537 537 538 538 It is worth noting that in the direction from VTL to SDMX it is mandatory to specify the value for every Dimension on which the mapping is based (in other word, in the name of the calculated VTL dataset is __not__ possible to omit the value of some of the Dimensions). 539 539 ... ... @@ -541,42 +541,43 @@ 541 541 542 542 With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered: 543 543 544 -(% style="width:1170.29px" %) 545 -|**VTL**|(% style="width:754px" %)**SDMX** 546 -|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow 547 -|**Represented Variable**|(% style="width:754px" %)((( 546 +|VTL|SDMX 547 +|**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^^ 548 +|**Represented Variable**|((( 548 548 **Concept** with a definite 549 549 550 550 Representation 551 551 ))) 552 -|**Value Domain**|( % style="width:754px" %)(((553 +|**Value Domain**|((( 553 553 **Representation** (see the Structure 554 554 555 555 Pattern in the Base Package) 556 556 ))) 557 -|**Enumerated Value Domain / Code List**| (% style="width:754px" %)**Codelist**558 -|**Code**|( % style="width:754px" %)(((558 +|**Enumerated Value Domain / Code List**|**Codelist** 559 +|**Code**|((( 559 559 **Code** (for enumerated 560 560 561 561 DimensionComponent, Measure, DataAttribute) 562 562 ))) 563 -|**Described Value Domain**|( % style="width:754px" %)(((564 -non-enumerated** Representation** 564 +|**Described Value Domain**|((( 565 +non-enumerated** Representation** 565 565 566 566 (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package) 567 567 ))) 568 -|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or 569 -| |(% style="width:754px" %)((( 570 -to a valid **value **(for non-enumerated** **Representations) 569 +|**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 570 +| |((( 571 +to a valid **value **(for non-enumerated** ** 572 + 573 +Representations) 571 571 ))) 572 -|**Value Domain Subset / Set**| (% style="width:754px" %)This abstraction does not exist in SDMX573 -|**Enumerated Value Domain Subset / Enumerated Set**| (% style="width:754px" %)This abstraction does not exist in SDMX574 -|**Described Value Domain Subset / Described Set**| (% style="width:754px" %)This abstraction does not exist in SDMX575 -|**Set list**| (% style="width:754px" %)This abstraction does not exist in SDMX575 +|**Value Domain Subset / Set**|This abstraction does not exist in SDMX 576 +|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX 577 +|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX 578 +|**Set list**|This abstraction does not exist in SDMX 576 576 577 577 The main difference between VTL and SDMX relies on the fact that the VTL artefacts for defining subsets of Value Domains do not exist in SDMX, therefore the VTL features for referring to predefined subsets are not available in SDMX. These artefacts are the Value Domain Subset (or Set), either enumerated or described, the Set List (list of values belonging to enumerated subsets) and the Data Set Component (aimed at defining the set of values that the Component of a Data Set can take, possibly a subset of the codes of Value Domain). 578 578 579 -Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear^^[[(% 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" %)^^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 wikiinternallinkwikiinternallink 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.582 +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" %)^^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" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has. 580 580 581 581 Therefore, it is important to be aware that some VTL operations (for example the binary operations at data set level) are consistent only if the components having the same names in the operated VTL Data Sets have also the same representation (i.e. the same Value Domain as for VTL). For example, it is possible to obtain correct results from the VTL expression 582 582 ... ... @@ -1045,7 +1045,7 @@ 1045 1045 |N|fixed number of digits used in the preceding textual representation of the month or the day 1046 1046 | | 1047 1047 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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.1051 +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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^. 1049 1049 1050 1050 === 12.4.5 Null Values === 1051 1051