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edited by Helena K.
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1 -Artefact|Attribute|Code|Code list|Component|Concept scheme|Currency|Data set|Data structure definition|Dataflow|Dimension|Facet|Maintainable artefact|Measure|Nameable artefact|Representation|SDMX Information Model|Statistical data and metadata exchange|Structural metadata|Validation and transformation language
Content
... ... @@ -18,7 +18,7 @@
18 18  
19 19  This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts.
20 20  
21 -== 12.2 References to SDMX artefacts from VTL statements ==
21 +== 12.2 References to SDMX artefacts from VTL statements ==
22 22  
23 23  === 12.2.1 Introduction ===
24 24  
... ... @@ -78,12 +78,8 @@
78 78  * if the artefact is a Dimension, TimeDimension, Measure or DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components)
79 79  * if the artefact is a Concept (the object-id is the name of the Concept)
80 80  
81 +For example, by using the URN, the VTL Transformation that sums two SDMX Dataflows DF1 and DF2 and assigns the result to a third persistent Dataflow DFR, assuming that DF1, DF2 and DFR are the maintainedobject-id of the three Dataflows, that their version is 1.0.0 and their Agency is AG, would be written as{{footnote}}Since these references to SDMX objects include non-permitted characters as per the VTL ID notation, they need to be included between single quotes, according to the VTL rules for irregular names.{{/footnote}}:
81 81  
82 -
83 -For example, by using the URN, the VTL Transformation that sums two SDMX Dataflows DF1 and DF2 and assigns the result to a third persistent Dataflow DFR, assuming that DF1, DF2 and DFR are the maintainedobject-id of the three Dataflows, that their version is 1.0.0 and their Agency is AG, would be written as
84 -
85 -{{footnote}}Since these references to SDMX objects include non-permitted characters as per the VTL ID notation, they need to be included between single quotes, according to the VTL rules for irregular names.{{/footnote}}:
86 -
87 87  > 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
88 88  > 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
89 89  > 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
... ... @@ -110,8 +110,6 @@
110 110  * As said, the container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN
111 111  * The object-id does not exist for the artefacts belonging to the Dataflow, and Codelist classes, while it exists and cannot be omitted for the artefacts belonging to the classes Dimension, TimeDimension, Measure, DataAttribute and Concept, as for them the object-id is the main identifier of the artefact
112 112  
113 -
114 -
115 115  The simplified object identifier is obtained by omitting all the first part of the URN, including the special characters, till the first part not omitted.
116 116  
117 117  For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
... ... @@ -122,7 +122,7 @@
122 122  
123 123  by omitting all the non-essential parts would become simply:
124 124  
125 -> DFR : = DF1 + DF2
119 +> DFR  : =  DF1 + DF2
126 126  
127 127  The references to the Codelists can be simplified similarly. For example, given the non-abbreviated reference to the Codelist AG:CL_FREQ(1.0.0), which is{{footnote}}Single quotes are needed because this reference is not a VTL regular name. 19 Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}:
128 128  
... ... @@ -168,16 +168,14 @@
168 168  
169 169  === 12.2.5 References to SDMX artefacts from VTL Rulesets ===
170 170  
171 -The VTL Rulesets allow defining sets of reusable Rules that can be applied by some VTL operators, like the ones for validation and hierarchical roll-up. A "Rule" consists in a relationship between Values belonging to some Value Domains or taken by some Variables, for example: when the Country is USA then the Currency is USD; (ii) the Benelux is composed by Belgium, Luxembourg, Netherlands.
165 +The VTL Rulesets allow defining sets of reusable Rules that can be applied by some VTL operators, like the ones for validation and hierarchical roll-up. A "Rule" consists in a relationship between Values belonging to some Value Domains or taken by some Variables, for example: (i) when the Country is USA then the Currency is USD; (ii) the Benelux is composed by Belgium, Luxembourg, Netherlands.
172 172  
173 173  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.
174 174  
175 175  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}}.
176 176  
177 -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).
171 +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}}
178 178  
179 -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}}
180 -
181 181  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.
182 182  
183 183  == 12.3 Mapping between SDMX and VTL artefacts ==
... ... @@ -206,7 +206,7 @@
206 206  
207 207  The possible mapping options are described in more detail in the following sections.
208 208  
209 -=== 12.3.3 Mapping from SDMX to VTL data structures ===
201 +=== 12.3.2 Mapping from SDMX to VTL data structures ===
210 210  
211 211  ==== 12.3.3.1 Basic Mapping ====
212 212  
... ... @@ -229,8 +229,10 @@
229 229  
230 230  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.
231 231  
232 -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
233 233  
226 +MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.
227 +
234 234  Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
235 235  
236 236  If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
... ... @@ -243,18 +243,16 @@
243 243  * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
244 244  * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
245 245  ** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension;
246 -** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators).
247 -** Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship.
240 +** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators). o Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship.
248 248  
249 249  The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
250 250  
251 -(% style="width:739.294px" %)
252 -|(% style="width:335px" %)**SDMX**|(% style="width:400px" %)**VTL**
253 -|(% style="width:335px" %)Dimension|(% style="width:400px" %)(Simple) Identifier
254 -|(% style="width:335px" %)TimeDimension|(% style="width:400px" %)(Time) Identifier
255 -|(% style="width:335px" %)MeasureDimension & one Measure|(% style="width:400px" %)One Measure for each Code of the SDMX MeasureDimension
256 -|(% style="width:335px" %)DataAttribute not depending on the MeasureDimension|(% style="width:400px" %)Attribute
257 -|(% style="width:335px" %)DataAttribute depending on the MeasureDimension|(% style="width:400px" %)(((
244 +|**SDMX**|**VTL**
245 +|Dimension|(Simple) Identifier
246 +|TimeDimension|(Time) Identifier
247 +|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension
248 +|DataAttribute not depending on the MeasureDimension|Attribute
249 +|DataAttribute depending on the MeasureDimension|(((
258 258  One Attribute for each Code of the
259 259  SDMX MeasureDimension
260 260  )))
... ... @@ -264,14 +264,19 @@
264 264  At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
265 265  
266 266  * The set of SDMX observations having the same values for all the Dimensions except than the MeasureDimension become one multi-measure VTL Data Point, having one Measure for each Code Cj of the SDMX MeasureDimension;
267 -* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
259 +* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple)
260 +
261 +Identifiers, (time) Identifier and Attributes.
262 +
268 268  * 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
269 269  * 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
270 270  
271 271  ==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
272 272  
273 -* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain Attributes.
268 +* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain
274 274  
270 +Attributes.
271 +
275 275  The Basic_A2M and Pivot_A2M behaves respectively like the Basic and Pivot methods, except that the final VTL components, which according to the Basic and Pivot methods would have had the role of Attribute, assume instead the role of Measure.
276 276  
277 277  Proper VTL features allow changing the role of specific attributes even after the SDMX to VTL mapping: they can be useful when only some of the DataAttributes need to be managed as VTL Measures.
... ... @@ -288,12 +288,11 @@
288 288  
289 289  Mapping table:
290 290  
291 -(% style="width:470.294px" %)
292 -|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX**
293 -|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension
294 -|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension
295 -|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure
296 -|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute
288 +|**VTL**|**SDMX**
289 +|(Simple) Identifier|Dimension
290 +|(Time) Identifier|TimeDimension
291 +|Measure|Measure
292 +|Attribute|DataAttribute
297 297  
298 298  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.
299 299  
... ... @@ -321,12 +321,11 @@
321 321  
322 322  The summary mapping table of the **unpivot** mapping method is the following:
323 323  
324 -(% style="width:638.294px" %)
325 -|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX**
326 -|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension
327 -|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension
328 -|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
329 -|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
320 +|**VTL**|**SDMX**
321 +|(Simple) Identifier|Dimension
322 +|(Time) Identifier|TimeDimension
323 +|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
324 +|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
330 330  
331 331  At observation / data point level:
332 332  
... ... @@ -348,13 +348,12 @@
348 348  
349 349  The mapping table is the following:
350 350  
351 -(% style="width:467.294px" %)
352 -|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
353 -|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
354 -|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
355 -|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
356 -|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
357 -|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
346 +|VTL|SDMX
347 +|(Simple) Identifier|Dimension
348 +|(Time) Identifier|TimeDimension
349 +|Some Measures|Measure
350 +|Other Measures|DataAttribute
351 +|Attribute|DataAttribute
358 358  
359 359  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.
360 360  
... ... @@ -392,11 +392,11 @@
392 392  
393 393  Therefore, the generic name of this kind of VTL datasets would be:
394 394  
395 -> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
389 +'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
396 396  
397 397  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:
398 398  
399 -> ‘DF(1.0.0)/POPULATION.USA’
393 +‘DF(1.0.0)/POPULATION.USA’
400 400  
401 401  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.
402 402  
... ... @@ -410,22 +410,26 @@
410 410  
411 411  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.
412 412  
413 -In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
407 +In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
414 414  
409 +basic, pivot …).
410 +
415 415  In the example above, for all the datasets of the kind
416 416  
417 -> ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
413 +‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
418 418  
419 419  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:
420 420  
421 -> ‘DF1(1.0.0)/POPULATION.USA’ :=
422 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
423 ->
424 -> ‘DF1(1.0.0)/POPULATION.CANADA’ :=
425 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
426 ->
427 -> … … …
417 +‘DF1(1.0.0)/POPULATION.USA’ :=
428 428  
419 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
420 +
421 +‘DF1(1.0.0)/POPULATION.CANADA’ :=
422 +
423 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
424 +
425 +… … …
426 +
429 429  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}}
430 430  
431 431  In the direction from SDMX to VTL it is allowed to omit the value of one or more DimensionComponents on which the mapping is based, but maintaining all the separating dots (therefore it may happen to find two or more consecutive dots and dots in the beginning or in the end). The absence of value means that for the corresponding Dimension all the values are kept and the Dimension is not dropped.
... ... @@ -434,9 +434,10 @@
434 434  
435 435  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
436 436  
437 -> ‘DF1(1.0.0)/POPULATION.’ :=
438 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
435 +‘DF1(1.0.0)/POPULATION.’ :=
439 439  
437 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
438 +
440 440  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
441 441  
442 442  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
... ... @@ -454,33 +454,41 @@
454 454  
455 455  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}}
456 456  
457 -> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
456 +‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
458 458  
459 459  Some examples follow, for some specific values of INDICATOR and COUNTRY:
460 460  
461 -> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
462 -> … … …
463 -> ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
464 -> ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
465 -> … … …
460 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
461 +… … …
466 466  
463 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
464 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
465 +… … …
466 +
467 467  As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively:
468 468  
469 -> VTL dataset INDICATOR value COUNTRY value
470 ->
471 -> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
472 -> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
473 ->
474 -> ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
475 -> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
476 -> … … …
469 +VTL dataset   INDICATOR value COUNTRY value
477 477  
471 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
472 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
473 +‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
474 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
475 +
476 +… … …
477 +
478 478  It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be:
479 479  
480 -> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”];… … … DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”];… … … DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’, DF2bis_GDPPERCAPITA_CANADA’,
481 -> … ,
482 -> DF2bis_POPGROWTH_USA’, DF2bis_POPGROWTH_CANADA’
483 -> …);
480 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
481 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
482 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
483 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
484 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
485 +DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
486 +DF2bis_GDPPERCAPITA_CANADA’,
487 +… ,
488 +DF2bis_POPGROWTH_USA’,
489 +DF2bis_POPGROWTH_CANADA’
490 +…);
484 484  
485 485  In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
486 486  
... ... @@ -492,26 +492,25 @@
492 492  
493 493  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
494 494  
495 -(% style="width:706.294px" %)
496 -|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX
497 -|(% style="width:257px" %)**Data Set Component**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
498 -|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation
499 -|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)(((
502 +|VTL|SDMX
503 +|**Data Set Component**|Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
504 +|**Represented Variable**|**Concept** with a definite Representation
505 +|**Value Domain**|(((
500 500  **Representation** (see the Structure
501 501  Pattern in the Base Package)
502 502  )))
503 -|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
504 -|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
505 -|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
509 +|**Enumerated Value Domain / Code List**|**Codelist**
510 +|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
511 +|**Described Value Domain**|(((
506 506  non-enumerated** Representation**
507 507  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
508 508  )))
509 -|(% style="width:257px" %)**Value**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
510 -|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)
511 -|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
512 -|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
513 -|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
514 -|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX
515 +|**Value**|Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
516 +| |to a valid **value **(for non-enumerated** **Representations)
517 +|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
518 +|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
519 +|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
520 +|**Set list**|This abstraction does not exist in SDMX
515 515  
516 516  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).
517 517  
... ... @@ -519,10 +519,8 @@
519 519  
520 520  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
521 521  
522 -> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
528 +DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
523 523  
524 -if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
525 -
526 526  As mentioned, the property above is not enforced by construction in SDMX, and different representations of the same Concept can be not compatible one another (for example, it may happen that geo_area is represented by ISO-alpha-3 codes in DS_a and by ISO alpha-2 codes in DS_b). Therefore, it will be up to the definer of VTL
527 527  
528 528  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
... ... @@ -537,7 +537,7 @@
537 537  
538 538  The VTL data types are sub-divided in scalar types (like integers, strings, etc.), which are the types of the scalar values, and compound types (like Data Sets, Components, Rulesets, etc.), which are the types of the compound structures. See below the diagram of the VTL data types, taken from the VTL User Manual:
539 539  
540 -[[image:1750070288958-132.png]]
544 +[[image:1750067055028-964.png]]
541 541  
542 542  **Figure 22 – VTL Data Types**
543 543  
... ... @@ -545,8 +545,6 @@
545 545  
546 546  The VTL basic scalar types are listed below and follow a hierarchical structure in terms of supersets/subsets (e.g. "scalar" is the superset of all the basic scalar types):
547 547  
548 -[[image:1750070310572-584.png]]
549 -
550 550  **Figure 23 – VTL Basic Scalar Types**
551 551  
552 552  === 12.4.2 VTL basic scalar types and SDMX data types ===
... ... @@ -571,159 +571,158 @@
571 571  
572 572  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
573 573  
574 -(% style="width:583.294px" %)
575 -|(% style="width:360px" %)SDMX data type
576 -(BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type
577 -|(% style="width:360px" %)(((
576 +|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
577 +|(((
578 578  String
579 579  (string allowing any character)
580 -)))|(% style="width:221px" %)string
581 -|(% style="width:360px" %)(((
582 -Alpha
580 +)))|string
581 +|(((
582 +Alpha 
583 +
583 583  (string which only allows A-z)
584 -)))|(% style="width:221px" %)string
585 -|(% style="width:360px" %)(((
585 +)))|string
586 +|(((
586 586  AlphaNumeric
587 587  (string which only allows A-z and 0-9)
588 -)))|(% style="width:221px" %)string
589 -|(% style="width:360px" %)(((
589 +)))|string
590 +|(((
590 590  Numeric
592 +
591 591  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
592 -)))|(% style="width:221px" %)string
593 -|(% style="width:360px" %)(((
594 +)))|string
595 +|(((
594 594  BigInteger
595 595  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
596 -)))|(% style="width:221px" %)integer
597 -|(% style="width:360px" %)(((
598 +)))|integer
599 +|(((
598 598  Integer
599 599  (corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
600 600  (inclusive))
601 -)))|(% style="width:221px" %)integer
602 -|(% style="width:360px" %)(((
603 +)))|integer
604 +|(((
603 603  Long
604 604  (corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
605 605  +9223372036854775807 (inclusive))
606 -)))|(% style="width:221px" %)integer
607 -|(% style="width:360px" %)(((
608 +)))|integer
609 +|(((
608 608  Short
609 609  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
610 -)))|(% style="width:221px" %)integer
611 -|(% style="width:360px" %)Decimal
612 -(corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:221px" %)number
613 -|(% style="width:360px" %)(((
612 +)))|integer
613 +|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
614 +|(((
614 614  Float
615 615  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
616 -)))|(% style="width:221px" %)number
617 -|(% style="width:360px" %)(((
617 +)))|number
618 +|(((
618 618  Double
619 619  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
620 -)))|(% style="width:221px" %)number
621 -|(% style="width:360px" %)(((
621 +)))|number
622 +|(((
622 622  Boolean
623 623  (corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
624 624  binary-valued logic: {true, false})
625 -)))|(% style="width:221px" %)boolean
626 -|(% style="width:360px" %)(((
626 +)))|boolean
627 +|(((
627 627  URI
628 628  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
629 -)))|(% style="width:221px" %)string
630 -|(% style="width:360px" %)(((
630 +)))|string
631 +|(((
631 631  Count
632 632  (an integer following a sequential pattern, increasing by 1 for each occurrence)
633 -)))|(% style="width:221px" %)integer
634 -|(% style="width:360px" %)(((
634 +)))|integer
635 +|(((
635 635  InclusiveValueRange
636 636  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
637 -)))|(% style="width:221px" %)number
638 -|(% style="width:360px" %)(((
638 +)))|number
639 +|(((
639 639  ExclusiveValueRange
640 640  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
641 -)))|(% style="width:221px" %)number
642 -|(% style="width:360px" %)(((
642 +)))|number
643 +|(((
643 643  Incremental
644 644  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
645 -)))|(% style="width:221px" %)number
646 -|(% style="width:360px" %)(((
646 +)))|number
647 +|(((
647 647  ObservationalTimePeriod
648 648  (superset of StandardTimePeriod and TimeRange)
649 -)))|(% style="width:221px" %)time
650 -|(% style="width:360px" %)(((
650 +)))|time
651 +|(((
651 651  StandardTimePeriod
652 652  (superset of BasicTimePeriod and ReportingTimePeriod)
653 -)))|(% style="width:221px" %)time
654 -|(% style="width:360px" %)(((
654 +)))|time
655 +|(((
655 655  BasicTimePeriod
656 656  (superset of GregorianTimePeriod and DateTime)
657 -)))|(% style="width:221px" %)date
658 -|(% style="width:360px" %)(((
658 +)))|date
659 +|(((
659 659  GregorianTimePeriod
660 660  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
661 -)))|(% style="width:221px" %)date
662 -|(% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date
663 -|(% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date
664 -|(% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date
665 -|(% style="width:360px" %)(((
662 +)))|date
663 +|GregorianYear (YYYY)|date
664 +|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
665 +|GregorianDay (YYYY-MM-DD)|date
666 +|(((
666 666  ReportingTimePeriod
667 667  (superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
668 -)))|(% style="width:221px" %)time_period
669 -|(% style="width:360px" %)(((
669 +)))|time_period
670 +|(((
670 670  ReportingYear
671 671  (YYYY-A1 – 1 year period)
672 -)))|(% style="width:221px" %)time_period
673 -|(% style="width:360px" %)(((
673 +)))|time_period
674 +|(((
674 674  ReportingSemester
675 675  (YYYY-Ss – 6 month period)
676 -)))|(% style="width:221px" %)time_period
677 -|(% style="width:360px" %)(((
677 +)))|time_period
678 +|(((
678 678  ReportingTrimester
679 679  (YYYY-Tt – 4 month period)
680 -)))|(% style="width:221px" %)time_period
681 -|(% style="width:360px" %)(((
681 +)))|time_period
682 +|(((
682 682  ReportingQuarter
683 683  (YYYY-Qq – 3 month period)
684 -)))|(% style="width:221px" %)time_period
685 -|(% style="width:360px" %)(((
685 +)))|time_period
686 +|(((
686 686  ReportingMonth
687 687  (YYYY-Mmm – 1 month period)
688 -)))|(% style="width:221px" %)time_period
689 -|(% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period
690 -|(% style="width:360px" %) (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% style="width:221px" %)
691 -|(% style="width:360px" %)(((
689 +)))|time_period
690 +|ReportingWeek|time_period
691 +| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
692 +|(((
692 692  ReportingDay
693 693  (YYYY-Dddd – 1 day period)
694 -)))|(% style="width:221px" %)time_period
695 -|(% style="width:360px" %)(((
695 +)))|time_period
696 +|(((
696 696  DateTime
697 697  (YYYY-MM-DDThh:mm:ss)
698 -)))|(% style="width:221px" %)date
699 -|(% style="width:360px" %)(((
699 +)))|date
700 +|(((
700 700  TimeRange
701 -(YYYY-MM-DD(Thh:mm:ss)?/)
702 -)))|(% style="width:221px" %)time
703 -|(% style="width:360px" %)(((
702 +(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
703 +)))|time
704 +|(((
704 704  Month
705 -(MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
706 -)))|(% style="width:221px" %)string
707 -|(% style="width:360px" %)(((
706 +(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
707 +)))|string
708 +|(((
708 708  MonthDay
709 -(MM-DD; specifies a day within a month independent of a year; e.g. Christmas is December 25^^th^^; used to specify reporting year start day)
710 -)))|(% style="width:221px" %)string
711 -|(% style="width:360px" %)(((
710 +(~-~-MM-DD; specifies a day within a month independent of a year; e.g. Christmas is December 25^^th^^; used to specify reporting year start day)
711 +)))|string
712 +|(((
712 712  Day
713 -(-DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
714 -)))|(% style="width:221px" %)string
715 -|(% style="width:360px" %)(((
714 +(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
715 +)))|string
716 +|(((
716 716  Time
717 717  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
718 -)))|(% style="width:221px" %)string
719 -|(% style="width:360px" %)(((
719 +)))|string
720 +|(((
720 720  Duration
721 721  (corresponds to XML Schema xs:duration datatype)
722 -)))|(% style="width:221px" %)duration
723 -|(% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable
724 -|(% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable
725 -|(% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable
726 -|(% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable
723 +)))|duration
724 +|XHTML|Metadata type – not applicable
725 +|KeyValues|Metadata type – not applicable
726 +|IdentifiableReference|Metadata type – not applicable
727 +|DataSetReference|Metadata type – not applicable
727 727  
728 728  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
729 729  
... ... @@ -733,82 +733,84 @@
733 733  
734 734  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
735 735  
736 -(% style="width:748.294px" %)
737 -|(% style="width:164px" %)(((
738 -VTL basic scalar type
739 -)))|(% style="width:304px" %)(((
737 +|(((
738 +VTL basic
739 +scalar type
740 +)))|(((
740 740  Default SDMX data type
741 -(BasicComponentDataType)
742 -)))|(% style="width:277px" %)Default output format
743 -|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string)
744 -|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float)
745 -|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int)
746 -|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z
747 -|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above)
748 -|(% style="width:164px" %)time_period|(% style="width:304px" %)(((
742 +(BasicComponentDataType
743 +)
744 +)))|Default output format
745 +|String|String|Like XML (xs:string)
746 +|Number|Float|Like XML (xs:float)
747 +|Integer|Integer|Like XML (xs:int)
748 +|Date|DateTime|YYYY-MM-DDT00:00:00Z
749 +|Time|StandardTimePeriod|<date>/<date> (as defined above)
750 +|time_period|(((
749 749  ReportingTimePeriod
750 750  (StandardReportingPeriod)
751 -)))|(% style="width:277px" %)(((
753 +)))|(((
752 752   YYYY-Pppp
753 753  (according to SDMX )
754 754  )))
755 -|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS
756 -|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"
757 +|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
758 +|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
757 757  
758 758  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
759 759  
760 -In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
762 +In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
761 761  
764 +Transformations and Expressions of the SDMX information model).
765 +
762 762  The custom output formats can be specified by means of the VTL formatting mask described in the section "Type Conversion and Formatting Mask" of the VTL Reference Manual. Such a section describes the masks for the VTL basic scalar types "number", "integer", "date", "time", "time_period" and "duration" and gives examples. As for the types "string" and "boolean" the VTL conventions are extended with some other special characters as described in the following table.
763 763  
764 -(% style="width:717.294px" %)
765 -|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks
766 -|(% colspan="2" style="width:714px" %)
767 -|(% colspan="2" style="width:714px" %)Number
768 -|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
769 -|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation)
770 -|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
771 -|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
772 -|(% style="width:122px" %) |(% style="width:591px" %)
773 -|(% colspan="2" style="width:714px" %)Time and duration
774 -|(% style="width:122px" %)C|(% style="width:591px" %)century
775 -|(% style="width:122px" %)Y|(% style="width:591px" %)year
776 -|(% style="width:122px" %)S|(% style="width:591px" %)semester
777 -|(% style="width:122px" %)Q|(% style="width:591px" %)quarter
778 -|(% style="width:122px" %)M|(% style="width:591px" %)month
779 -|(% style="width:122px" %)W|(% style="width:591px" %)week
780 -|(% style="width:122px" %)D|(% style="width:591px" %)day
781 -|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours)
782 -|(% style="width:122px" %)M|(% style="width:591px" %)minute
783 -|(% style="width:122px" %)S|(% style="width:591px" %)second
784 -|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second
785 -|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration)
786 -|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator
787 -|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
788 -|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January)
789 -|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
790 -|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january)
791 -|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday)
792 -|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
793 -|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
794 -|(% style="width:122px" %) |(% style="width:591px" %)
795 -|(% colspan="2" style="width:714px" %)String
796 -|(% style="width:122px" %)X|(% style="width:591px" %)any string character
797 -|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z"
798 -|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9"
799 -|(% style="width:122px" %) |(% style="width:591px" %)
800 -|(% colspan="2" style="width:714px" %)Boolean
801 -|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False
802 -|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False
803 -|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False
804 -|(% style="width:122px" %) |(% style="width:591px" %)
805 -|(% colspan="2" style="width:714px" %)Other qualifiers
806 -|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type)
807 -|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type)
808 -|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets)
809 -|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask
810 -|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day
811 -|(% style="width:122px" %) |(% style="width:591px" %)
768 +|(% colspan="2" %)VTL special characters for the formatting masks
769 +|(% colspan="2" %)
770 +|(% colspan="2" %)Number
771 +|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
772 +|E|one numeric digit (for the exponent of the scientific notation)
773 +|. (dot)|possible separator between the integer and the decimal parts.
774 +|, (comma)|possible separator between the integer and the decimal parts.
775 +| |
776 +|(% colspan="2" %)Time and duration
777 +|C|century
778 +|Y|year
779 +|S|semester
780 +|Q|quarter
781 +|M|month
782 +|W|week
783 +|D|day
784 +|h|hour digit (by default on 24 hours)
785 +|M|minute
786 +|S|second
787 +|D|decimal of second
788 +|P|period indicator (representation in one digit for the duration)
789 +|P|number of the periods specified in the period indicator
790 +|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
791 +|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
792 +|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
793 +|Month|lowercase textual representation of the month (e.g., january)
794 +|Day|lowercase textual representation of the month (e.g., monday)
795 +|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
796 +|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
797 +| |
798 +|(% colspan="2" %)String
799 +|X|any string character
800 +|Z|any string character from "A" to "z"
801 +|9|any string character from "0" to "9"
802 +| |
803 +|(% colspan="2" %)Boolean
804 +|B|Boolean using "true" for True and "false" for False
805 +|1|Boolean using "1" for True and "0" for False
806 +|0|Boolean using "0" for True and "1" for False
807 +| |
808 +|(% colspan="2" %)Other qualifiers
809 +|*|an arbitrary number of digits (of the preceding type)
810 +|+|at least one digit (of the preceding type)
811 +|( )|optional digits (specified within the brackets)
812 +|\|prefix for the special characters that must appear in the mask
813 +|N|fixed number of digits used in the preceding textual representation of the month or the day
814 +| |
812 812  
813 813  The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion{{footnote}}The representation given in the DSD should obviously be compatible with the VTL data type.{{/footnote}}.
814 814  
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SKMS.Methodology.Code.MethodologyClass[0]
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SUZ.Methodology.Code.MethodologyClass[0]
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