Changes for page 12 Validation and Transformation Language (VTL)
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... ... @@ -249,19 +249,16 @@ 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 -|**SDMX**|**VTL** 253 -|Dimension|(Simple) Identifier 254 -|TimeDimension|(Time) Identifier 255 -|MeasureDimension & one Measure|((( 256 -One Measure for each Code of the 257 - 258 -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 259 259 ))) 260 -|DataAttribute not depending on the MeasureDimension|Attribute 261 -|DataAttribute depending on the MeasureDimension|((( 262 -One Attribute for each Code of the 263 - 264 -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 265 265 ))) 266 266 267 267 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. ... ... @@ -276,7 +276,7 @@ 276 276 * 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 277 277 * 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 278 278 279 - **12.3.3.3 From SDMX DataAttributes to VTL Measures**276 +==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ==== 280 280 281 281 * 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 282 282 ... ... @@ -288,7 +288,7 @@ 288 288 289 289 === 12.3.4 Mapping from VTL to SDMX data structures === 290 290 291 - **12.3.4.1 Basic Mapping**288 +==== 12.3.4.1 Basic Mapping ==== 292 292 293 293 The main mapping method **from VTL to SDMX** is called **Basic **mapping as well. 294 294 ... ... @@ -298,11 +298,12 @@ 298 298 299 299 Mapping table: 300 300 301 -|**VTL**|**SDMX** 302 -|(Simple) Identifier|Dimension 303 -|(Time) Identifier|TimeDimension 304 -|Measure|Measure 305 -|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 306 306 307 307 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. 308 308 ... ... @@ -312,7 +312,7 @@ 312 312 313 313 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. 314 314 315 - **12.3.4.2 Unpivot Mapping**313 +==== 12.3.4.2 Unpivot Mapping ==== 316 316 317 317 An alternative mapping method from VTL to SDMX is the **Unpivot **mapping. 318 318 ... ... @@ -336,11 +336,12 @@ 336 336 337 337 The summary mapping table of the **unpivot** mapping method is the following: 338 338 339 -|**VTL**|**SDMX** 340 -|(Simple) Identifier|Dimension 341 -|(Time) Identifier|TimeDimension 342 -|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure 343 -|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 344 344 345 345 At observation / data point level: 346 346 ... ... @@ -354,7 +354,7 @@ 354 354 355 355 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. 356 356 357 - **12.3.4.3 From VTL Measures to SDMX Data Attributes**356 +==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ==== 358 358 359 359 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”). 360 360 ... ... @@ -362,12 +362,13 @@ 362 362 363 363 The mapping table is the following: 364 364 365 -|VTL|SDMX 366 -|(Simple) Identifier|Dimension 367 -|(Time) Identifier|TimeDimension 368 -|Some Measures|Measure 369 -|Other Measures|DataAttribute 370 -|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 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. ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^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}} 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. ^^[[(% class="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink"%)^^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}} 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. ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^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. 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; ^^[[(% class="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink" %)^^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}} 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 ^^[[(% class="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^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. 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 ^^[[(% class="wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink" %)^^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. 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 ^^[[(%class="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink 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. 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. ^^[[(% class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink"%)^^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}} 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; ^^[[(% class="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^33^^>>path:#sdfootnote33sym||name="sdfootnote33anc"]](%%)^^474 -* 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 wikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallink" %)^^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}} 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 ^^[[(% class="wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallink 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}}. 477 477 478 -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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}} 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) ^^[[(% class="wikiinternallink wikiinternallink wikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallink 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.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. 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. ^^[[(% class="wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]](%%)[[(%class="wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink"%)^^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}} 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 ... ... @@ -577,7 +577,7 @@ 577 577 578 578 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). 579 579 580 -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" %)^^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" %)^^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 +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 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. 581 581 582 582 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 583 583 ... ... @@ -1046,7 +1046,7 @@ 1046 1046 |N|fixed number of digits used in the preceding textual representation of the month or the day 1047 1047 | | 1048 1048 1049 -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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^. 1049 +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"]](%%)^^. 1050 1050 1051 1051 === 12.4.5 Null Values === 1052 1052