Changes for page 12 Validation and Transformation Language (VTL)

Last modified by Artur on 2025/09/10 11:19

From 1.23 to 1.22 From 1.25 to 1.24

From version 1.24

edited by Helena
on 2025/06/16 13:29

Change comment: There is no comment for this version

To version 1.23

edited by Helena
on 2025/06/16 13:27

Change comment: There is no comment for this version

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@@ -313,12 +313,11 @@
  The summary mapping table of the **unpivot** mapping method is the following:
--(% style="width:638.294px" %)
--|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX**
--|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension
--|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension
--|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
--|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
++|**VTL**|**SDMX**
++|(Simple) Identifier|Dimension
++|(Time) Identifier|TimeDimension
++|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
++|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
  At observation / data point level:
@@ -340,13 +340,12 @@
  The mapping table is the following:
--(% style="width:467.294px" %)
--|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
--|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
--|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
--|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
--|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
--|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
++|VTL|SDMX
++|(Simple) Identifier|Dimension
++|(Time) Identifier|TimeDimension
++|Some Measures|Measure
++|Other Measures|DataAttribute
++|Attribute|DataAttribute
  Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the attributeRelationship for the DataAttributes, which does not exist in VTL.
@@ -384,11 +384,11 @@
  Therefore, the generic name of this kind of VTL datasets would be:
--> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
++'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
  Where DF(1.0.0) is the Dataflow and //INDICATORvalue// and //COUNTRYvalue //are placeholders for one value of the INDICATOR and COUNTRY dimensions. Instead the specific name of one of these VTL datasets would be:
--> ‘DF(1.0.0)/POPULATION.USA’
++‘DF(1.0.0)/POPULATION.USA’
  In particular, this is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA.
@@ -402,11 +402,13 @@
  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.
--In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
++In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
++basic, pivot …).
++
  In the example above, for all the datasets of the kind
--> ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
++‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
  It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression: