Changes for page 12 Validation and Transformation Language (VTL)
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... ... @@ -2,8 +2,7 @@ 2 2 {{toc/}} 3 3 {{/box}} 4 4 5 -1. 6 -11. Introduction 5 +== 12.1 Introduction == 7 7 8 8 The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones{{footnote}}The Validation and Transformation Language is a standard language designed and published under the SDMX initiative. VTL is described in the VTL User and Reference Guides available on the SDMX website https://sdmx.org.{{/footnote}}. The purpose of the VTL in the SDMX context is to enable the: 9 9 ... ... @@ -19,10 +19,10 @@ 19 19 20 20 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. 21 21 22 -1. 23 -11. References to SDMX artefacts from VTL statements 24 -111. Introduction 21 +== 12.2 References to SDMX artefacts from VTL statements == 25 25 23 +=== 12.2.1 Introduction === 24 + 26 26 The VTL can manipulate SDMX artefacts (or objects) by referencing them through predefined conventional names (aliases). 27 27 28 28 The alias of an SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name. ... ... @@ -33,9 +33,7 @@ 33 33 34 34 The references through the URN and the abbreviated URN are described in the following paragraphs. 35 35 36 -1. 37 -11. 38 -111. References through the URN 35 +=== 12.2.2 References through the URN === 39 39 40 40 This approach has the advantage that in the VTL code the URN of the referenced artefacts is directly intelligible by a human reader but has the drawback that the references are verbose. 41 41 ... ... @@ -52,10 +52,8 @@ 52 52 53 53 The generic structure of the URN is the following: 54 54 55 -SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id 52 +SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id (maintainedobject-version).*container-object-id.object-id 56 56 57 -(maintainedobject-version).*container-object-id.object-id 58 - 59 59 The **SDMXprefix** is "urn:sdmx:org", always the same for all SDMX artefacts. 60 60 61 61 The SDMX-IM-package-name** **is the concatenation of the string** **"sdmx.infomodel." with the package-name, which the artefact belongs to. For example, for referencing a Dataflow the SDMX-IM-package-name is "sdmx.infomodel.datastructure", because the class Dataflow belongs to the package "datastructure". ... ... @@ -76,28 +76,21 @@ 76 76 77 77 The maintainedobject-version is the version, according to the SDMX versioning rules, of the maintained object which the artefact belongs to (for example, possible versions might be 1.0, 2.3, 1.0.0, 2.1.0 or 3.1.2). 78 78 79 -The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN 74 +The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN. 80 80 81 81 The object-id is the name of the non-maintainable artefact (when the artefact is maintainable its name is already specified as the maintainedobject-id, see above), in particular it has to be specified: 82 82 83 -* if the artefact is a Dimension, TimeDimension, Measure or 84 - 85 -DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components) 86 - 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) 87 87 * if the artefact is a Concept (the object-id is the name of the Concept) 88 88 89 89 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}}: 90 90 91 -'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <- 83 +>(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <- 84 +>(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' + 85 +>(% style="font-size:16px" %) 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 92 92 93 - 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)'+87 +=== 12.2.3 Abbreviation of the URN === 94 94 95 -'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)' 96 - 97 -1. 98 -11. 99 -111. Abbreviation of the URN 100 - 101 101 The complete formulation of the URN described above is exhaustive but verbose, even for very simple statements. In order to reduce the verbosity through a simplified identifier and make the work of transformation definers easier, proper abbreviations of the URN are possible. Using this approach, the referenced artefacts remain intelligible in the VTL code by a human reader. 102 102 103 103 The URN can be abbreviated by omitting the parts that are not essential for the identification of the artefact or that can be deduced from other available information, including the context in which the invocation is made. The possible abbreviations are described below. ... ... @@ -108,11 +108,7 @@ 108 108 * The class-name can be omitted as it can be deduced from the VTL invocation. In particular, starting from the VTL class of the invoked artefact (e.g. dataset, component, identifier, measure, attribute, variable, valuedomain), which is known given the syntax of the invoking VTL operator{{footnote}}For the syntax of the VTL operators see the VTL Reference Manual{{/footnote}}, the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section "Mapping between VTL and SDMX" hereinafter){{footnote}}In case the invoked artefact is a VTL component, which can be invoked only within the invocation of a VTL data set (SDMX Dataflow), the specific SDMX class-name (e.g. Dimension, TimeDimension, Measure or DataAttribute) can be deduced from the data structure of the SDMX Dataflow, which the component belongs to.{{/footnote}}. 109 109 * If the agency-id is not specified, it is assumed by default equal to the agency-id of the TransformationScheme, UserDefinedOperatorScheme or RulesetScheme from which the artefact is invoked. For example, the agencyid can be omitted if it is the same as the invoking TransformationScheme and cannot be omitted if the artefact comes from another agency{{footnote}}If the Agency is composite (for example AgencyA.Dept1.Unit2), the agency is considered different even if only part of the composite name is different (for example AgencyA.Dept1.Unit3 is a different Agency than the previous one). Moreover the agency-id cannot be omitted in part (i.e., if a TransformationScheme owned by AgencyA.Dept1.Unit2 references an artefact coming from AgencyA.Dept1.Unit3, the specification of the agency-id becomes mandatory and must be complete, without omitting the possibly equal parts like AgencyA.Dept1){{/footnote}}. Take also into account that, according to the VTL consistency rules, the agency of the result of a Transformation must be the same as its TransformationScheme, therefore the agency-id can be omitted for all the results (left part of Transformation statements). 110 110 * As for the maintainedobject-id, this is essential in some cases while in other cases it can be omitted: o if the referenced artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the dataflow-id and obviously cannot be omitted; 111 -** if the referenced artefact is a Dimension, TimeDimension, Measure, 112 - 113 -DataAttribute, which are not maintainable and belong to the DataStructure maintainable class, the maintainedobject-id is the dataStructure-id and can be omitted, given that these components are always invoked within the invocation of a Dataflow, whose dataStructure-id can be deduced from the SDMX structural definitions; 114 - 115 -* 99 +** if the referenced artefact is a Dimension, TimeDimension, Measure, DataAttribute, which are not maintainable and belong to the DataStructure maintainable class, the maintainedobject-id is the dataStructure-id and can be omitted, given that these components are always invoked within the invocation of a Dataflow, whose dataStructure-id can be deduced from the SDMX structural definitions; 116 116 ** if the referenced artefact is a Concept, which is not maintainable and belong to the ConceptScheme maintainable class, the maintained object is the conceptScheme-id and cannot be omitted; 117 117 ** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted. 118 118 * When the maintainedobject-id is omitted, the maintainedobject-version is omitted too. When the maintainedobject-id is not omitted and the maintainedobject-version is omitted, the version 1.0 is assumed by default. ... ... @@ -171,17 +171,13 @@ 171 171 172 172 The artefact (Component, Concept, Codelist …) which the Values are referred to can be deduced from the context in which the reference is made, taking also into account the VTL syntax. In the Transformation above, for example, the values 0 and 2500 are compared to the values of the measures of DF1(1.0.0). 173 173 174 -1. 175 -11. 176 -111. User-defined alias 158 +=== 12.2.4 User-defined alias === 177 177 178 178 The third possibility for referencing SDMX artefacts from VTL statements is to use user-defined aliases not related to the SDMX URN of the artefact. 179 179 180 180 This approach gives preference to the use of symbolic names for the SDMX artefacts. As a consequence, in the VTL code the referenced artefacts may become not directly intelligible by a human reader. In any case, the VTL aliases are associated to the SDMX URN through the VtlMappingScheme and VtlMapping classes. These classes provide for structured references to SDMX artefacts whatever kind of reference is used in VTL statements (URN, abbreviated URN or user-defined aliases). 181 181 182 -1. 183 -11. 184 -111. References to SDMX artefacts from VTL Rulesets 164 +=== 12.2.5 References to SDMX artefacts from VTL Rulesets === 185 185 186 186 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. 187 187 ... ... @@ -193,10 +193,10 @@ 193 193 194 194 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. 195 195 196 -1. 197 -11. Mapping between SDMX and VTL artefacts 198 -111. When the mapping occurs 176 +== 12.3 Mapping between SDMX and VTL artefacts == 199 199 178 +=== 12.3.1. When the mapping occurs === 179 + 200 200 The mapping methods between the VTL and SDMX object classes allow transforming a SDMX definition in a VTL one and vice-versa for the artefacts to be manipulated. It should be remembered that VTL programs (i.e. Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformations (nameable artefacts). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result: the input operands of the expression and the result can be SDMX artefacts. 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. 201 201 202 202 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 nonpersistent calculation is disseminated through SDMX tools (like an inquiry tool).{{/footnote}}. ... ... @@ -203,9 +203,7 @@ 203 203 204 204 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). 205 205 206 -1. 207 -11. 208 -111. General mapping of VTL and SDMX data structures 186 +=== 12.3.2 General mapping of VTL and SDMX data structures === 209 209 210 210 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}}. 211 211 ... ... @@ -221,11 +221,9 @@ 221 221 222 222 The possible mapping options are described in more detail in the following sections. 223 223 224 -1. 225 -11. 226 -111. Mapping from SDMX to VTL data structures 202 +=== 12.3.2 Mapping from SDMX to VTL data structures === 227 227 228 - **12.3.3.1 Basic Mapping**204 +==== 12.3.3.1 Basic Mapping ==== 229 229 230 230 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. 231 231 ... ... @@ -241,7 +241,7 @@ 241 241 242 242 With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point. 243 243 244 - **12.3.3.2 Pivot Mapping**220 +==== 12.3.3.2 Pivot Mapping ==== 245 245 246 246 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. 247 247 ... ... @@ -272,7 +272,6 @@ 272 272 |DataAttribute not depending on the MeasureDimension|Attribute 273 273 |DataAttribute depending on the MeasureDimension|((( 274 274 One Attribute for each Code of the 275 - 276 276 SDMX MeasureDimension 277 277 ))) 278 278 ... ... @@ -285,13 +285,10 @@ 285 285 286 286 Identifiers, (time) Identifier and Attributes. 287 287 288 -* 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 289 - 290 -Cj 291 - 263 +* 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 292 292 * 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 293 293 294 - **12.3.3.3 From SDMX DataAttributes to VTL Measures**266 +==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ==== 295 295 296 296 * 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 297 297 ... ... @@ -301,11 +301,9 @@ 301 301 302 302 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. 303 303 304 -1. 305 -11. 306 -111. Mapping from VTL to SDMX data structures 276 +=== 12.3.4 Mapping from VTL to SDMX data structures === 307 307 308 - **12.3.4.1 Basic Mapping**278 +==== 12.3.4.1 Basic Mapping ==== 309 309 310 310 The main mapping method **from VTL to SDMX** is called **Basic **mapping as well. 311 311 ... ... @@ -329,7 +329,7 @@ 329 329 330 330 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. 331 331 332 - **12.3.4.2 Unpivot Mapping**302 +==== 12.3.4.2 Unpivot Mapping ==== 333 333 334 334 An alternative mapping method from VTL to SDMX is the **Unpivot **mapping. 335 335 ... ... @@ -365,7 +365,7 @@ 365 365 366 366 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. 367 367 368 - **12.3.4.3 From VTL Measures to SDMX Data Attributes**338 +==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ==== 369 369 370 370 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”). 371 371 ... ... @@ -382,9 +382,7 @@ 382 382 383 383 Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the attributeRelationship for the DataAttributes, which does not exist in VTL. 384 384 385 -1. 386 -11. 387 -111. Declaration of the mapping methods between data structures 355 +=== 12.3.5 Declaration of the mapping methods between data structures === 388 388 389 389 In order to define and understand properly VTL Transformations, the applied mapping methods must be specified in the SDMX structural metadata. If the default mapping method (Basic) is applied, no specification is needed. 390 390 ... ... @@ -394,14 +394,10 @@ 394 394 395 395 The VtlMappingScheme is a container for zero or more VtlDataflowMapping (it may contain also mappings towards artefacts other than dataflows). 396 396 397 -1. 398 -11. 399 -111. Mapping dataflow subsets to distinct VTL Data Sets 365 +=== 12.3.6 Mapping dataflow subsets to distinct VTL Data Sets === 400 400 401 -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 367 +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). 402 402 403 -(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). 404 - 405 405 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}} 406 406 407 407 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}} ... ... @@ -494,13 +494,10 @@ 494 494 Some examples follow, for some specific values of INDICATOR and COUNTRY: 495 495 496 496 ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12; 497 - 498 498 … … … 499 499 500 500 ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21; 501 - 502 502 ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22; 503 - 504 504 … … … 505 505 506 506 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: ... ... @@ -507,13 +507,9 @@ 507 507 508 508 VTL dataset INDICATOR value COUNTRY value 509 509 510 - 511 511 ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA 512 - 513 513 ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … … 514 - 515 515 ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA 516 - 517 517 ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA 518 518 519 519 … … … ... ... @@ -521,25 +521,15 @@ 521 521 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: 522 522 523 523 DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”]; 524 - 525 525 DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … … 526 - 527 527 DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’ 528 - 529 529 [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”]; 530 - 531 531 DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … … 532 - 533 533 DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’, 534 - 535 535 DF2bis_GDPPERCAPITA_CANADA’, 536 - 537 537 … , 538 - 539 539 DF2bis_POPGROWTH_USA’, 540 - 541 541 DF2bis_POPGROWTH_CANADA’ 542 - 543 543 …); 544 544 545 545 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. ... ... @@ -548,9 +548,7 @@ 548 548 549 549 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). 550 550 551 -1. 552 -11. 553 -111. Mapping variables and value domains between VTL and SDMX 498 +=== 12.3.7 Mapping variables and value domains between VTL and SDMX === 554 554 555 555 With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered: 556 556 ... ... @@ -559,7 +559,6 @@ 559 559 |**Represented Variable**|**Concept** with a definite Representation 560 560 |**Value Domain**|((( 561 561 **Representation** (see the Structure 562 - 563 563 Pattern in the Base Package) 564 564 ))) 565 565 |**Enumerated Value Domain / Code List**|**Codelist** ... ... @@ -566,7 +566,6 @@ 566 566 |**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute) 567 567 |**Described Value Domain**|((( 568 568 non-enumerated** Representation** 569 - 570 570 (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package) 571 571 ))) 572 572 |**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 ... ... @@ -590,10 +590,10 @@ 590 590 591 591 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. 592 592 593 -1. 594 -11. Mapping between SDMX and VTL Data Types 595 -111. VTL Data types 536 +== 12.4 Mapping between SDMX and VTL Data Types == 596 596 538 +=== 12.4.1 VTL Data types === 539 + 597 597 According to the VTL User Guide the possible operations in VTL depend on the data types of the artefacts. For example, numbers can be multiplied but text strings cannot. In the VTL Transformations, the compliance between the operators and the data types of their operands is statically checked, i.e., violations result in compile-time errors. 598 598 599 599 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: ... ... @@ -600,17 +600,15 @@ 600 600 601 601 [[image:1750067055028-964.png]] 602 602 603 - ====Figure 22 – VTL Data Types====546 +**Figure 22 – VTL Data Types** 604 604 605 605 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. 606 606 607 607 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): 608 608 609 - ====Figure 23 – VTL Basic Scalar Types====552 +**Figure 23 – VTL Basic Scalar Types** 610 610 611 -1. 612 -11. 613 -111. VTL basic scalar types and SDMX data types 554 +=== 12.4.2 VTL basic scalar types and SDMX data types === 614 614 615 615 The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations. 616 616 ... ... @@ -628,9 +628,7 @@ 628 628 629 629 The opposite conversion, i.e. from VTL to SDMX, happens when a VTL result, i.e. a VTL Data Set output of a Transformation, must become a SDMX artefact (or part of it). The values of the VTL result must be converted into the desired (SDMX) external representations (data types) of the SDMX artefact. 630 630 631 -1. 632 -11. 633 -111. Mapping SDMX data types to VTL basic scalar types 572 +=== 12.4.3 Mapping SDMX data types to VTL basic scalar types === 634 634 635 635 The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types. 636 636 ... ... @@ -637,7 +637,6 @@ 637 637 |SDMX data type (BasicComponentDataType)|Default VTL basic scalar type 638 638 |((( 639 639 String 640 - 641 641 (string allowing any character) 642 642 )))|string 643 643 |((( ... ... @@ -647,7 +647,6 @@ 647 647 )))|string 648 648 |((( 649 649 AlphaNumeric 650 - 651 651 (string which only allows A-z and 0-9) 652 652 )))|string 653 653 |((( ... ... @@ -657,89 +657,70 @@ 657 657 )))|string 658 658 |((( 659 659 BigInteger 660 - 661 661 (corresponds to XML Schema xs:integer datatype; infinite set of integer values) 662 662 )))|integer 663 663 |((( 664 664 Integer 665 - 666 666 (corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 667 - 668 668 (inclusive)) 669 669 )))|integer 670 670 |((( 671 671 Long 672 - 673 673 (corresponds to XML Schema xs:long datatype; between -9223372036854775808 and 674 - 675 675 +9223372036854775807 (inclusive)) 676 676 )))|integer 677 677 |((( 678 678 Short 679 - 680 680 (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive)) 681 681 )))|integer 682 682 |Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number 683 683 |((( 684 684 Float 685 - 686 686 (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type) 687 687 )))|number 688 688 |((( 689 689 Double 690 - 691 691 (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type) 692 692 )))|number 693 693 |((( 694 694 Boolean 695 - 696 696 (corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of 697 - 698 698 binary-valued logic: {true, false}) 699 699 )))|boolean 700 700 |((( 701 701 URI 702 - 703 703 (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference) 704 704 )))|string 705 705 |((( 706 706 Count 707 - 708 708 (an integer following a sequential pattern, increasing by 1 for each occurrence) 709 709 )))|integer 710 710 |((( 711 711 InclusiveValueRange 712 - 713 713 (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 714 714 )))|number 715 715 |((( 716 716 ExclusiveValueRange 717 - 718 718 (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 719 719 )))|number 720 720 |((( 721 721 Incremental 722 - 723 723 (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation) 724 724 )))|number 725 725 |((( 726 726 ObservationalTimePeriod 727 - 728 728 (superset of StandardTimePeriod and TimeRange) 729 729 )))|time 730 730 |((( 731 731 StandardTimePeriod 732 - 733 733 (superset of BasicTimePeriod and ReportingTimePeriod) 734 734 )))|time 735 735 |((( 736 736 BasicTimePeriod 737 - 738 738 (superset of GregorianTimePeriod and DateTime) 739 739 )))|date 740 740 |((( 741 741 GregorianTimePeriod 742 - 743 743 (superset of GregorianYear, GregorianYearMonth, and GregorianDay) 744 744 )))|date 745 745 |GregorianYear (YYYY)|date ... ... @@ -747,32 +747,26 @@ 747 747 |GregorianDay (YYYY-MM-DD)|date 748 748 |((( 749 749 ReportingTimePeriod 750 - 751 751 (superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay) 752 752 )))|time_period 753 753 |((( 754 754 ReportingYear 755 - 756 756 (YYYY-A1 – 1 year period) 757 757 )))|time_period 758 758 |((( 759 759 ReportingSemester 760 - 761 761 (YYYY-Ss – 6 month period) 762 762 )))|time_period 763 763 |((( 764 764 ReportingTrimester 765 - 766 766 (YYYY-Tt – 4 month period) 767 767 )))|time_period 768 768 |((( 769 769 ReportingQuarter 770 - 771 771 (YYYY-Qq – 3 month period) 772 772 )))|time_period 773 773 |((( 774 774 ReportingMonth 775 - 776 776 (YYYY-Mmm – 1 month period) 777 777 )))|time_period 778 778 |ReportingWeek|time_period ... ... @@ -779,42 +779,34 @@ 779 779 | (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)| 780 780 |((( 781 781 ReportingDay 782 - 783 783 (YYYY-Dddd – 1 day period) 784 784 )))|time_period 785 785 |((( 786 786 DateTime 787 - 788 788 (YYYY-MM-DDThh:mm:ss) 789 789 )))|date 790 790 |((( 791 791 TimeRange 792 - 793 793 (YYYY-MM-DD(Thh:mm:ss)?/<duration>) 794 794 )))|time 795 795 |((( 796 796 Month 797 - 798 798 (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States) 799 799 )))|string 800 800 |((( 801 801 MonthDay 802 - 803 803 (~-~-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) 804 804 )))|string 805 805 |((( 806 806 Day 807 - 808 808 (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday) 809 809 )))|string 810 810 |((( 811 811 Time 812 - 813 813 (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM) 814 814 )))|string 815 815 |((( 816 816 Duration 817 - 818 818 (corresponds to XML Schema xs:duration datatype) 819 819 )))|duration 820 820 |XHTML|Metadata type – not applicable ... ... @@ -822,27 +822,20 @@ 822 822 |IdentifiableReference|Metadata type – not applicable 823 823 |DataSetReference|Metadata type – not applicable 824 824 825 - додол729 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 826 826 827 -==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ==== 828 - 829 829 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). 830 830 831 -1. 832 -11. 833 -111. Mapping VTL basic scalar types to SDMX data types 733 +=== 12.4.4 Mapping VTL basic scalar types to SDMX data types === 834 834 835 835 The following table describes the default conversion from the VTL basic scalar types to the SDMX data types . 836 836 837 837 |((( 838 838 VTL basic 839 - 840 840 scalar type 841 841 )))|((( 842 842 Default SDMX data type 843 - 844 844 (BasicComponentDataType 845 - 846 846 ) 847 847 )))|Default output format 848 848 |String|String|Like XML (xs:string) ... ... @@ -852,17 +852,15 @@ 852 852 |Time|StandardTimePeriod|<date>/<date> (as defined above) 853 853 |time_period|((( 854 854 ReportingTimePeriod 855 - 856 856 (StandardReportingPeriod) 857 857 )))|((( 858 858 YYYY-Pppp 859 - 860 860 (according to SDMX ) 861 861 ))) 862 862 |Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS 863 863 |Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false" 864 864 865 - ====Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types====760 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 866 866 867 867 In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section 868 868 ... ... @@ -920,17 +920,13 @@ 920 920 921 921 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}}. 922 922 923 -1. 924 -11. 925 -111. Null Values 818 +=== 12.4.3 Null Values === 926 926 927 927 In the conversions from SDMX to VTL it is assumed by default that a missing value in SDMX becomes a NULL in VTL. After the conversion, the NULLs can be manipulated through the proper VTL operators. 928 928 929 929 On the other side, the VTL programs can produce in output NULL values for Measures and Attributes (Null values are not allowed in the Identifiers). In the conversion from VTL to SDMX, it is assumed that a NULL in VTL becomes a missing value in SDMX. In the conversion from VTL to SDMX, the default assumption can be overridden, separately for each VTL basic scalar type, by specifying which the value that represents the NULL in SDMX is. This can be specified in the attribute "nullValue" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model). A CustomType belongs to a CustomTypeScheme, which can be referenced by one or more TransformationScheme (i.e. VTL programs). The overriding assumption is applied for all the SDMX Dataflows calculated in the TransformationScheme. 930 930 931 -1. 932 -11. 933 -111. Format of the literals used in VTL Transformations 824 +=== 12.4.5 Format of the literals used in VTL Transformations === 934 934 935 935 The VTL programs can contain literals, i.e. specific values of certain data types written directly in the VTL definitions or expressions. The VTL does not prescribe a specific format for the literals and leave the specific VTL systems and the definers of VTL Transformations free of using their preferred formats. 936 936 ... ... @@ -944,7 +944,6 @@ 944 944 945 945 In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats. 946 946 947 - 948 948 ---- 949 949 950 950 {{putFootnotes/}}