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... ... @@ -82,9 +82,7 @@
82 82  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}}:
83 83  
84 84  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
85 -
86 86  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
87 -
88 88  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
89 89  
90 90  === 12.2.3 Abbreviation of the URN ===
... ... @@ -109,9 +109,7 @@
109 109  For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
110 110  
111 111  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
112 -
113 113  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
114 -
115 115  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
116 116  
117 117  by omitting all the non-essential parts would become simply:
... ... @@ -118,11 +118,11 @@
118 118  
119 119  DFR := DF1 + DF2
120 120  
121 -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^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^16^^>>path:#sdfootnote16sym||name="sdfootnote16anc"]](%%)^^:
117 +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.{{/footnote}}:
122 122  
123 123  'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
124 124  
125 -if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply^^19^^:
121 +if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply{{footnote}}Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}:
126 126  
127 127  CL_FREQ
128 128  
... ... @@ -136,7 +136,7 @@
136 136  
137 137  SECTOR
138 138  
139 -For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^17^^>>path:#sdfootnote17sym||name="sdfootnote17anc"]](%%)^^:
135 +For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as{{footnote}}The result DFR(1.0.0) is be equal to DF1(1.0.0) save that the component SECTOR is called SEC{{/footnote}}:
140 140  
141 141  'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
142 142  
... ... @@ -168,9 +168,9 @@
168 168  
169 169  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.
170 170  
171 -In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist, while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^18^^>>path:#sdfootnote18sym||name="sdfootnote18anc"]](%%)^^.
167 +In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist, while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation{{footnote}}Rulesets of this kind cannot be reused when the referenced Concept has a different representation.{{/footnote}}.
172 172  
173 -In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called "valueDomain" and "variable" for the Datapoint Rulesets and "ruleValueDomain", "ruleVariable", "condValueDomain" "condVariable" for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific Ruleset definition statement and cannot be mapped to SDMX.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^19^^>>path:#sdfootnote19sym||name="sdfootnote19anc"]](%%)^^
169 +In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called "valueDomain" and "variable" for the Datapoint Rulesets and "ruleValueDomain", "ruleVariable", "condValueDomain" "condVariable" for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific Ruleset definition statement and cannot be mapped to SDMX.{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}}
174 174  
175 175  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.
176 176  
... ... @@ -182,15 +182,15 @@
182 182  
183 183  Every time a SDMX object is referenced in a VTL Transformation as an input operand, there is the need to generate a VTL definition of the object, so that the VTL operations can take place. This can be made starting from the SDMX definition and applying a SDMX-VTL mapping method in the direction from SDMX to VTL. The possible mapping methods from SDMX to VTL are described in the following paragraphs and are conceived to allow the automatic deduction of the VTL definition of the object from the knowledge of the SDMX definition.
184 184  
185 -In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^20^^>>path:#sdfootnote20sym||name="sdfootnote20anc"]](%%)^^.
181 +In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged{{footnote}}If a calculated artefact is persistent, it needs a persistent definition, i.e. a SDMX definition in a SDMX environment. In addition, possible calculated artefact that are not persistent may require a SDMX definition, for example when the result of a non-persistent calculation is disseminated through SDMX tools (like an inquiry tool).{{/footnote}}.
186 186  
187 187  The mapping methods from VTL to SDMX are described in the following paragraphs as well, however they do not allow the complete SDMX definition to be automatically deduced from the VTL definition, more than all because the former typically contains additional information in respect to the latter. For example, the definition of a SDMX DSD includes also some mandatory information not available in VTL (like the concept scheme to which the SDMX components refer, the ‘usage’ and ‘attributeRelationship’ for the DataAttributes and so on). Therefore the mapping methods from VTL to SDMX provide only a general guidance for generating SDMX definitions properly starting from the information available in VTL, independently of how the SDMX definition it is actually generated (manually, automatically or part and part).
188 188  
189 189  === 12.3.2 General mapping of VTL and SDMX data structures ===
190 190  
191 -This section makes reference to the VTL "Model for data and their structure"^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^21^^>>path:#sdfootnote21sym||name="sdfootnote21anc"]](%%)^^ and the correspondent SDMX "Data Structure Definition"^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^22^^>>path:#sdfootnote22sym||name="sdfootnote22anc"]](%%)^^.
187 +This section makes reference to the VTL "Model for data and their structure"{{footnote}}See the VTL 2.0 User Manual{{/footnote}} and the correspondent SDMX "Data Structure Definition"{{footnote}}See the SDMX Standards Section 2 – Information Model{{/footnote}}.
192 192  
193 -The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^23^^>>path:#sdfootnote23sym||name="sdfootnote23anc"]](%%)^^
189 +The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).{{footnote}}Besides the mapping between one SDMX Dataflow and one VTL Data Set, it is also possible to map distinct parts of a SDMX Dataflow to different VTL Data Set, as explained in a following paragraph.{{/footnote}}
194 194  
195 195  While the VTL Transformations are defined in term of Dataflow definitions, they are assumed to be executed on instances of such Dataflows, provided at runtime to the VTL engine (the mechanism for identifying the instances to be processed are not part of the VTL specifications and depend on the implementation of the VTL-based systems). As already said, the SDMX Datasets are instances of SDMX Dataflows, therefore a VTL Transformation defined on some SDMX Dataflows can be applied on some corresponding SDMX Datasets.
196 196  
... ... @@ -210,32 +210,28 @@
210 210  
211 211  The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes. When transforming **from SDMX to VTL**, this method consists in leaving the components unchanged and maintaining their names and roles, according to the following table:
212 212  
213 -|**SDMX**|**VTL**
214 -|Dimension|(Simple) Identifier
215 -|TimeDimension|(Time) Identifier
209 +(% style="width:529.294px" %)
210 +|(% style="width:151px" %)**SDMX**|(% style="width:375px" %)**VTL**
211 +|(% style="width:151px" %)Dimension|(% style="width:375px" %)(Simple) Identifier
212 +|(% style="width:151px" %)TimeDimension|(% style="width:375px" %)(Time) Identifier
213 +|(% style="width:151px" %)Measure|(% style="width:375px" %)Measure
214 +|(% style="width:151px" %)DataAttribute|(% style="width:375px" %)Attribute
216 216  
217 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape4" height="1" width="192"]]
218 -
219 -|Measure|Measure
220 -|DataAttribute|Attribute
221 -
222 222  The SDMX DataAttributes, in VTL they are all considered "at data point / observation level" (i.e. dependent on all the VTL Identifiers), because VTL does not have the SDMX AttributeRelationships, which defines the construct to which the DataAttribute is related (e.g. observation, dimension or set or group of dimensions, whole data set).
223 223  
224 -With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point.
218 +With the Basic mapping, one SDMX observation{{footnote}}Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.{{/footnote}} generates one VTL data point.
225 225  
226 -**12.3.3.2 Pivot Mapping**
220 +==== 12.3.3.2 Pivot Mapping ====
227 227  
228 228  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.
229 229  
230 -In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the
224 +In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.
231 231  
232 -MeasureDimensions considered as a joint variable^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^24^^>>path:#sdfootnote24sym||name="sdfootnote24anc"]](%%)^^.
233 -
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).
237 237  
238 -^^27^^ Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
230 +Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
239 239  
240 240  The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation):
241 241  
... ... @@ -251,25 +251,22 @@
251 251  
252 252  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;
253 253  
254 -*
246 +*
255 255  ** 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).
256 256  ** 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.
257 257  
258 258  The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
259 259  
260 -|**SDMX**|**VTL**
261 -|Dimension|(Simple) Identifier
262 -|TimeDimension|(Time) Identifier
263 -|MeasureDimension & one Measure|(((
264 -One Measure for each Code of the
265 -
266 -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
267 267  )))
268 -|DataAttribute not depending on the MeasureDimension|Attribute
269 -|DataAttribute depending on the MeasureDimension|(((
270 -One Attribute for each Code of the
271 -
272 -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
273 273  )))
274 274  
275 275  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.
... ... @@ -284,7 +284,7 @@
284 284  * 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
285 285  * 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
286 286  
287 -**12.3.3.3 From SDMX DataAttributes to VTL Measures**
276 +==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
288 288  
289 289  * 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
290 290  
... ... @@ -296,7 +296,7 @@
296 296  
297 297  === 12.3.4 Mapping from VTL to SDMX data structures ===
298 298  
299 -**12.3.4.1 Basic Mapping**
288 +==== 12.3.4.1 Basic Mapping ====
300 300  
301 301  The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
302 302  
... ... @@ -306,11 +306,12 @@
306 306  
307 307  Mapping table:
308 308  
309 -|**VTL**|**SDMX**
310 -|(Simple) Identifier|Dimension
311 -|(Time) Identifier|TimeDimension
312 -|Measure|Measure
313 -|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
314 314  
315 315  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.
316 316  
... ... @@ -320,7 +320,7 @@
320 320  
321 321  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.
322 322  
323 -**12.3.4.2 Unpivot Mapping**
313 +==== 12.3.4.2 Unpivot Mapping ====
324 324  
325 325  An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
326 326  
... ... @@ -344,11 +344,12 @@
344 344  
345 345  The summary mapping table of the **unpivot** mapping method is the following:
346 346  
347 -|**VTL**|**SDMX**
348 -|(Simple) Identifier|Dimension
349 -|(Time) Identifier|TimeDimension
350 -|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
351 -|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
352 352  
353 353  At observation / data point level:
354 354  
... ... @@ -362,7 +362,7 @@
362 362  
363 363  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.
364 364  
365 -**12.3.4.3 From VTL Measures to SDMX Data Attributes**
356 +==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ====
366 366  
367 367  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”).
368 368  
... ... @@ -370,12 +370,13 @@
370 370  
371 371  The mapping table is the following:
372 372  
373 -|VTL|SDMX
374 -|(Simple) Identifier|Dimension
375 -|(Time) Identifier|TimeDimension
376 -|Some Measures|Measure
377 -|Other Measures|DataAttribute
378 -|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
379 379  
380 380  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.
381 381  
... ... @@ -393,20 +393,20 @@
393 393  
394 394  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).
395 395  
396 -As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}
397 397  
398 -Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL Data Sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}
399 399  
400 400  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.
401 401  
402 402  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:
403 403  
404 -* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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.
405 405  * The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts:
406 406  ** 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);
407 -** a slash (“/”) as a separator; ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}
408 408  
409 -The reference to a specific part of the SDMX Dataflow above, expressed as the concatenation of the values that the SDMX DimensionComponents declared above must have, separated by dots (“.”) and written in the order in which these DimensionComponents are defined^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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.
410 410  
411 411  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.
412 412  
... ... @@ -422,7 +422,7 @@
422 422  
423 423  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.
424 424  
425 -As already said, the mapping from SDMX to VTL happens when the SDMX dataflows are operand of VTL Transformations, instead the mapping from VTL to SDMX happens when the VTL Data Sets that is result of Transformations^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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.
426 426  
427 427  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.
428 428  
... ... @@ -430,7 +430,7 @@
430 430  
431 431  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.
432 432  
433 -In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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.
434 434  
435 435  basic, pivot …).
436 436  
... ... @@ -450,7 +450,7 @@
450 450  
451 451  … … …
452 452  
453 -In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow. ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}
454 454  
455 455  In the direction from SDMX to VTL it is allowed to omit the value of one or more
456 456  
... ... @@ -478,12 +478,12 @@
478 478  
479 479  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:
480 480  
481 -* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation; ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^33^^>>path:#sdfootnote33sym||name="sdfootnote33anc"]](%%)^^
482 -* the data structure of all these VTL Data Sets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}
483 483  
484 -Under these hypothesis, such derived VTL Data Sets can be mapped to DF2(1.0.0) by declaring the DimensionComponents INDICATOR and COUNTRY as mapping dimensions^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}.
485 485  
486 -The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:^^ [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}
487 487  
488 488  ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
489 489  
... ... @@ -539,9 +539,9 @@
539 539  
540 540  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
541 541  
542 -DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0)^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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.
543 543  
544 -Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^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}}
545 545  
546 546  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).
547 547  
... ... @@ -549,52 +549,51 @@
549 549  
550 550  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
551 551  
552 -|VTL|SDMX
553 -|**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^^
554 -|**Represented Variable**|(((
544 +(% style="width:1170.29px" %)
545 +|**VTL**|(% style="width:754px" %)**SDMX**
546 +|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
547 +|**Represented Variable**|(% style="width:754px" %)(((
555 555  **Concept** with a definite
556 556  
557 557  Representation
558 558  )))
559 -|**Value Domain**|(((
552 +|**Value Domain**|(% style="width:754px" %)(((
560 560  **Representation** (see the Structure
561 561  
562 562  Pattern in the Base Package)
563 563  )))
564 -|**Enumerated Value Domain / Code List**|**Codelist**
565 -|**Code**|(((
557 +|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
558 +|**Code**|(% style="width:754px" %)(((
566 566  **Code** (for enumerated
567 567  
568 568  DimensionComponent, Measure, DataAttribute)
569 569  )))
570 -|**Described Value Domain**|(((
571 -non-enumerated** &nbsp;&nbsp;&nbsp;Representation**
563 +|**Described Value Domain**|(% style="width:754px" %)(((
564 +non-enumerated** Representation**
572 572  
573 573  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
574 574  )))
575 -|**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
576 -| |(((
577 -to a valid **value &nbsp;&nbsp;&nbsp;**(for non-enumerated** &nbsp;&nbsp;&nbsp;**
578 -
579 -Representations)
568 +|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
569 +| |(% style="width:754px" %)(((
570 +to a valid **value **(for non-enumerated** **Representations)
580 580  )))
581 -|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
582 -|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
583 -|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
584 -|**Set list**|This abstraction does not exist in SDMX
572 +|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
573 +|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
574 +|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
575 +|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
585 585  
586 586  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).
587 587  
588 -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" %)^^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" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
579 +Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear{{footnote}}By using represented variables, VTL can assume that data structures having the same variables as identifiers can be composed one another because the correspondent values can match.{{/footnote}}, while the SDMX Concepts can have different Representations in different DataStructures.{{footnote}}A Concept becomes a Component in a DataStructureDefinition, and Components can have different LocalRepresentations in different DataStructureDefinitions, also overriding the (possible) base representation of the Concept.{{/footnote}} This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
589 589  
590 590  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
591 591  
592 -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.
583 +DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
593 593  
585 +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.
586 +
594 594  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
595 595  
596 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape5" height="1" width="192"]]
597 -
598 598  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
599 599  
600 600  It remains up to the SDMX-VTL definer also the assurance of the consistency between a VTL Ruleset defined on Variables and the SDMX Components on which the Ruleset is applied. In fact, a VTL Ruleset is expressed by means of the values of the Variables (i.e. SDMX Concepts), i.e. assuming definite representations for them (e.g. ISOalpha-3 for country). If the Ruleset is applied to SDMX Components that have the same name of the Concept they refer to but different representations (e.g. ISO-alpha-2 for country), the Ruleset cannot work properly.
... ... @@ -609,7 +609,8 @@
609 609  
610 610  [[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
611 611  
612 -==== Figure 22 – VTL Data Types ====
603 +(% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
604 +**Figure 22 – VTL Data Types**
613 613  
614 614  The VTL scalar types are in turn subdivided in basic scalar types, which are elementary (not defined in term of other data types) and Value Domain and Set scalar types, which are defined in terms of the basic scalar types.
615 615  
... ... @@ -616,131 +616,12 @@
616 616  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):
617 617  
618 618  
611 +**Figure 23 – VTL Basic Scalar Types**
619 619  
620 620  (((
621 -//n//
622 -
623 -//a//
624 -
625 -//e//
626 -
627 -//l//
628 -
629 -//o//
630 -
631 -//o//
632 -
633 -//B//
634 -
635 -//n//
636 -
637 -//o//
638 -
639 -//i//
640 -
641 -//t//
642 -
643 -//a//
644 -
645 -//r//
646 -
647 -//u//
648 -
649 -//D//
650 -
651 -//d//
652 -
653 -//o//
654 -
655 -//i//
656 -
657 -//r//
658 -
659 -//e//
660 -
661 -//p//
662 -
663 -//_//
664 -
665 -//e//
666 -
667 -//m//
668 -
669 -//i//
670 -
671 -//T//
672 -
673 -//e//
674 -
675 -//t//
676 -
677 -//a//
678 -
679 -//D//
680 -
681 -//e//
682 -
683 -//m//
684 -
685 -//i//
686 -
687 -//T//
688 -
689 -//r//
690 -
691 -//e//
692 -
693 -//g//
694 -
695 -//e//
696 -
697 -//t//
698 -
699 -//n//
700 -
701 -//I//
702 -
703 -//r//
704 -
705 -//e//
706 -
707 -//b//
708 -
709 -//m//
710 -
711 -//u//
712 -
713 -//N//
714 -
715 -//g//
716 -
717 -//n//
718 -
719 -//i//
720 -
721 -//r//
722 -
723 -//t//
724 -
725 -//S//
726 -
727 -//r//
728 -
729 -//a//
730 -
731 -//l//
732 -
733 -//a//
734 -
735 -//c//
736 -
737 -//S//
738 -
739 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_82d45833.gif||alt="Shape6" height="231" width="184"]]
614 +
740 740  )))
741 741  
742 -==== Figure 23 – VTL Basic Scalar Types ====
743 -
744 744  === 12.4.2 VTL basic scalar types and SDMX data types ===
745 745  
746 746  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
... ... @@ -763,204 +763,159 @@
763 763  
764 764  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
765 765  
766 -|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
767 -|(((
639 +(% style="width:823.294px" %)
640 +|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type**
641 +|(% style="width:509px" %)(((
768 768  String
769 -
770 770  (string allowing any character)
771 -)))|string
772 -|(((
644 +)))|(% style="width:312px" %)string
645 +|(% style="width:509px" %)(((
773 773  Alpha
774 -
775 775  (string which only allows A-z)
776 -)))|string
777 -|(((
648 +)))|(% style="width:312px" %)string
649 +|(% style="width:509px" %)(((
778 778  AlphaNumeric
779 -
780 780  (string which only allows A-z and 0-9)
781 -)))|string
782 -|(((
652 +)))|(% style="width:312px" %)string
653 +|(% style="width:509px" %)(((
783 783  Numeric
784 -
785 785  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
786 -)))|string
787 -|(((
656 +)))|(% style="width:312px" %)string
657 +|(% style="width:509px" %)(((
788 788  BigInteger
789 -
790 790  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
791 -)))|integer
792 -|(((
660 +)))|(% style="width:312px" %)integer
661 +|(% style="width:509px" %)(((
793 793  Integer
794 -
795 -(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
796 -
797 -(inclusive))
798 -)))|integer
799 -|(((
663 +(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
664 +)))|(% style="width:312px" %)integer
665 +|(% style="width:509px" %)(((
800 800  Long
801 -
802 -(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
803 -
804 -+9223372036854775807 (inclusive))
805 -)))|integer
806 -|(((
667 +(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
668 +)))|(% style="width:312px" %)integer
669 +|(% style="width:509px" %)(((
807 807  Short
808 -
809 809  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
810 -)))|integer
811 -|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
812 -|(((
672 +)))|(% style="width:312px" %)integer
673 +|(% style="width:509px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:312px" %)number
674 +|(% style="width:509px" %)(((
813 813  Float
814 -
815 815  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
816 -)))|number
817 -|(((
677 +)))|(% style="width:312px" %)number
678 +|(% style="width:509px" %)(((
818 818  Double
819 -
820 820  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
821 -)))|number
822 -|(((
681 +)))|(% style="width:312px" %)number
682 +|(% style="width:509px" %)(((
823 823  Boolean
684 +(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
685 +)))|(% style="width:312px" %)boolean
824 824  
825 -(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
826 -
827 -binary-valued logic: {true, false})
828 -)))|boolean
829 -
830 -| |(% colspan="2" %)(((
687 +(% style="width:822.294px" %)
688 +|(% colspan="2" style="width:507px" %)(((
831 831  URI
832 -
833 833  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
834 -)))|(% colspan="2" %)string
835 -| |(% colspan="2" %)(((
691 +)))|(% colspan="1" style="width:311px" %)string
692 +|(% colspan="2" style="width:507px" %)(((
836 836  Count
837 -
838 838  (an integer following a sequential pattern, increasing by 1 for each occurrence)
839 -)))|(% colspan="2" %)integer
840 -| |(% colspan="2" %)(((
695 +)))|(% colspan="1" style="width:311px" %)integer
696 +|(% colspan="2" style="width:507px" %)(((
841 841  InclusiveValueRange
842 -
843 843  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
844 -)))|(% colspan="2" %)number
845 -| |(% colspan="2" %)(((
699 +)))|(% colspan="1" style="width:311px" %)number
700 +|(% colspan="2" style="width:507px" %)(((
846 846  ExclusiveValueRange
847 -
848 848  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
849 -)))|(% colspan="2" %)number
850 -| |(% colspan="2" %)(((
703 +)))|(% colspan="1" style="width:311px" %)number
704 +|(% colspan="2" style="width:507px" %)(((
851 851  Incremental
852 -
853 853  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
854 -)))|(% colspan="2" %)number
855 -| |(% colspan="2" %)(((
707 +)))|(% colspan="1" style="width:311px" %)number
708 +|(% colspan="2" style="width:507px" %)(((
856 856  ObservationalTimePeriod
857 -
858 858  (superset of StandardTimePeriod and TimeRange)
859 -)))|(% colspan="2" %)time
860 -| |(% colspan="2" %)(((
711 +)))|(% colspan="1" style="width:311px" %)time
712 +|(% colspan="2" style="width:507px" %)(((
861 861  StandardTimePeriod
862 -
863 -(superset of BasicTimePeriod and
864 -
865 -ReportingTimePeriod)
866 -)))|(% colspan="2" %)time
867 -| |(% colspan="2" %)(((
714 +(superset of BasicTimePeriod and ReportingTimePeriod)
715 +)))|(% colspan="1" style="width:311px" %)time
716 +|(% colspan="2" style="width:507px" %)(((
868 868  BasicTimePeriod
869 -
870 870  (superset of GregorianTimePeriod and DateTime)
871 -)))|(% colspan="2" %)date
872 -| |(% colspan="2" %)(((
719 +)))|(% colspan="1" style="width:311px" %)date
720 +|(% colspan="2" style="width:507px" %)(((
873 873  GregorianTimePeriod
874 -
875 875  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
876 -)))|(% colspan="2" %)date
877 -| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
878 -| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
879 -| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
880 -| |(% colspan="2" %)(((
723 +)))|(% colspan="1" style="width:311px" %)date
724 +|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date
725 +|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date
726 +|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date
727 +|(% colspan="2" style="width:507px" %)(((
881 881  ReportingTimePeriod
882 -
883 -(superset of RepostingYear, ReportingSemester,
884 -
885 -ReportingTrimester, ReportingQuarter,
886 -
887 -ReportingMonth, ReportingWeek, ReportingDay)
888 -)))|(% colspan="2" %)time_period
889 -| |(% colspan="2" %)(((
729 +(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
730 +)))|(% colspan="1" style="width:311px" %)time_period
731 +|(% colspan="2" style="width:507px" %)(((
890 890  ReportingYear
891 -
892 892  (YYYY-A1 – 1 year period)
893 -)))|(% colspan="2" %)time_period
894 -| |(% colspan="2" %)(((
734 +)))|(% colspan="1" style="width:311px" %)time_period
735 +|(% colspan="2" style="width:507px" %)(((
895 895  ReportingSemester
896 -
897 897  (YYYY-Ss – 6 month period)
898 -)))|(% colspan="2" %)time_period
899 -| |(% colspan="2" %)(((
738 +)))|(% colspan="1" style="width:311px" %)time_period
739 +|(% colspan="2" style="width:507px" %)(((
900 900  ReportingTrimester
901 -
902 902  (YYYY-Tt – 4 month period)
903 -)))|(% colspan="2" %)time_period
904 -| |(% colspan="2" %)(((
742 +)))|(% colspan="1" style="width:311px" %)time_period
743 +|(% colspan="2" style="width:507px" %)(((
905 905  ReportingQuarter
906 -
907 907  (YYYY-Qq – 3 month period)
908 -)))|(% colspan="2" %)time_period
909 -| |(% colspan="2" %)(((
746 +)))|(% colspan="1" style="width:311px" %)time_period
747 +|(% colspan="2" style="width:507px" %)(((
910 910  ReportingMonth
911 -
912 912  (YYYY-Mmm – 1 month period)
913 -)))|(% colspan="2" %)time_period
914 -| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
915 -| |(% colspan="2" %) |(% colspan="2" %)
916 -| |(% colspan="2" %) |(% colspan="2" %)
917 -|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) |
918 -|(% colspan="2" %)(((
750 +)))|(% colspan="1" style="width:311px" %)time_period
751 +|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period
752 +|(% colspan="1" style="width:507px" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" style="width:312px" %)
753 +|(% colspan="1" style="width:507px" %)(((
919 919  ReportingDay
920 -
921 921  (YYYY-Dddd – 1 day period)
922 -)))|(% colspan="2" %)time_period|
923 -|(% colspan="2" %)(((
756 +)))|(% colspan="2" style="width:312px" %)time_period
757 +|(% colspan="1" style="width:507px" %)(((
924 924  DateTime
925 -
926 926  (YYYY-MM-DDThh:mm:ss)
927 -)))|(% colspan="2" %)date|
928 -|(% colspan="2" %)(((
760 +)))|(% colspan="2" style="width:312px" %)date
761 +|(% colspan="1" style="width:507px" %)(((
929 929  TimeRange
930 -
931 931  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
932 -)))|(% colspan="2" %)time|
933 -|(% colspan="2" %)(((
764 +)))|(% colspan="2" style="width:312px" %)time
765 +|(% colspan="1" style="width:507px" %)(((
934 934  Month
935 -
936 936  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
937 -)))|(% colspan="2" %)string|
938 -|(% colspan="2" %)(((
768 +)))|(% colspan="2" style="width:312px" %)string
769 +|(% colspan="1" style="width:507px" %)(((
939 939  MonthDay
940 -
941 941  (~-~-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)
942 -)))|(% colspan="2" %)string|
943 -|(% colspan="2" %)(((
772 +)))|(% colspan="2" style="width:312px" %)string
773 +|(% colspan="1" style="width:507px" %)(((
944 944  Day
945 -
946 946  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
947 -)))|(% colspan="2" %)string|
948 -|(% colspan="2" %)(((
776 +)))|(% colspan="2" style="width:312px" %)string
777 +|(% colspan="1" style="width:507px" %)(((
949 949  Time
950 -
951 951  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
952 -)))|(% colspan="2" %)string|
953 -|(% colspan="2" %)(((
780 +)))|(% colspan="2" style="width:312px" %)string
781 +|(% colspan="1" style="width:507px" %)(((
954 954  Duration
955 -
956 956  (corresponds to XML Schema xs:duration datatype)
957 -)))|(% colspan="2" %)duration|
958 -|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
959 -|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
960 -|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
961 -|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
784 +)))|(% colspan="2" style="width:312px" %)duration
785 +|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable
786 +|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable
787 +|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
788 +|(% colspan="1" style="width:507px" %)DataSetReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
962 962  
963 -==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
790 +(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %)
791 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
964 964  
965 965  When VTL takes in input SDMX artefacts, it is assumed that a type conversion according to the table above always happens. In case a different VTL basic scalar type is desired, it can be achieved in the VTL program taking in input the default VTL basic scalar type above and applying to it the VTL type conversion features (see the implicit and explicit type conversion and the "cast" operator in the VTL Reference Manual).
966 966  
... ... @@ -968,37 +968,29 @@
968 968  
969 969  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
970 970  
971 -|(((
972 -VTL basic
973 -
974 -scalar type
975 -)))|(((
976 -Default SDMX data type
977 -
978 -(BasicComponentDataType
979 -
980 -)
981 -)))|Default output format
982 -|String|String|Like XML (xs:string)
983 -|Number|Float|Like XML (xs:float)
984 -|Integer|Integer|Like XML (xs:int)
985 -|Date|DateTime|YYYY-MM-DDT00:00:00Z
986 -|Time|StandardTimePeriod|<date>/<date> (as defined above)
987 -|time_period|(((
799 +(% style="width:1073.29px" %)
800 +|(% style="width:207px" %)(((
801 +**VTL basic scalar type**
802 +)))|(% style="width:462px" %)(((
803 +**Default SDMX data type (BasicComponentDataType)**
804 +)))|(% style="width:402px" %)**Default output format**
805 +|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string)
806 +|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float)
807 +|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int)
808 +|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z
809 +|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above)
810 +|(% style="width:207px" %)time_period|(% style="width:462px" %)(((
988 988  ReportingTimePeriod
989 -
990 990  (StandardReportingPeriod)
991 -)))|(((
813 +)))|(% style="width:402px" %)(((
992 992  YYYY-Pppp
993 -
994 994  (according to SDMX )
995 995  )))
996 -|Duration|Duration|(((
817 +|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)(((
997 997  Like XML (xs:duration)
998 -
999 999  PnYnMnDTnHnMnS
1000 1000  )))
1001 -|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
821 +|(% style="width:207px" %)Boolean|(% style="width:462px" %)Boolean|(% style="width:402px" %)Like XML (xs:boolean) with the values "true" or "false"
1002 1002  
1003 1003  ==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
1004 1004  
... ... @@ -1054,7 +1054,7 @@
1054 1054  |N|fixed number of digits used in the preceding textual representation of the month or the day
1055 1055  | |
1056 1056  
1057 -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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
877 +The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL Transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
1058 1058  
1059 1059  === 12.4.5 Null Values ===
1060 1060