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14 14  
15 15  The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate{{footnote}}In this chapter, in order to distinguish VTL and SDMX model artefacts, the VTL ones are written in the Arial font while the SDMX ones in Courier New{{/footnote}}. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of Transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL "Data Set", which do not correspond one another: as a matter of fact, the VTL "Data Set" maps to the SDMX "Dataflow", while the SDMX "Dataset" has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL Transformations). A SDMX "Dataset", however, is an instance of a SDMX "Dataflow" and can be the artefact on which the VTL transformations are executed (i.e., the Transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
16 16  
17 -The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
17 +The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of
18 18  
19 +Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
20 +
19 19  This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts.
20 20  
21 21  == 12.2 References to SDMX artefacts from VTL statements ==
... ... @@ -26,8 +26,10 @@
26 26  
27 27  The alias of an SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name.
28 28  
29 -In any case, the aliases used in the VTL Transformations have to be mapped to the SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
31 +In any case, the aliases used in the VTL Transformations have to be mapped to the
30 30  
33 +SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
34 +
31 31  The correspondence between an alias and a SDMX artefact must be one-to-one, meaning that a generic alias identifies one and just one SDMX artefact while a SDMX artefact is identified by one and just one alias. In other words, within a VtlMappingScheme an artefact can have just one alias and different artefacts cannot have the same alias.
32 32  
33 33  The references through the URN and the abbreviated URN are described in the following paragraphs.
... ... @@ -78,7 +78,9 @@
78 78  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}}:
79 79  
80 80  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
85 +
81 81  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
87 +
82 82  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
83 83  
84 84  === 12.2.3 Abbreviation of the URN ===
... ... @@ -89,8 +89,8 @@
89 89  
90 90  * The SDMXprefix can be omitted for all the SDMX objects, because it is a prefixed string (urn:sdmx:org), always the same for SDMX objects. • The SDMX-IM-package-name** **can be omitted as well because it can be deduced from the class-name that follows it (the table of the SDMX-IM packages and classes that allows this deduction is in the SDMX 2.1 Standards - Section 5 - Registry Specifications, paragraph 6.2.3). In particular, considering the object classes of the artefacts that VTL can reference, the package is:
91 91  ** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist.
92 -* 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}}.
93 -* 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).
98 +* 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)^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^14^^>>path:#sdfootnote14sym||name="sdfootnote14anc"]](%%)^^.
99 +* 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^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^15^^>>path:#sdfootnote15sym||name="sdfootnote15anc"]](%%)^^. 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).
94 94  * 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;
95 95  ** 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;
96 96  ** 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;
... ... @@ -103,7 +103,9 @@
103 103  For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
104 104  
105 105  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
112 +
106 106  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
114 +
107 107  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
108 108  
109 109  by omitting all the non-essential parts would become simply:
... ... @@ -110,11 +110,11 @@
110 110  
111 111  DFR := DF1 + DF2
112 112  
113 -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}}:
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" %)^^16^^>>path:#sdfootnote16sym||name="sdfootnote16anc"]](%%)^^:
114 114  
115 115  'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
116 116  
117 -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}}:
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^^:
118 118  
119 119  CL_FREQ
120 120  
... ... @@ -128,7 +128,7 @@
128 128  
129 129  SECTOR
130 130  
131 -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}}:
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" %)^^17^^>>path:#sdfootnote17sym||name="sdfootnote17anc"]](%%)^^:
132 132  
133 133  'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
134 134  
... ... @@ -160,9 +160,9 @@
160 160  
161 161  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.
162 162  
163 -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}}.
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" %)^^18^^>>path:#sdfootnote18sym||name="sdfootnote18anc"]](%%)^^.
164 164  
165 -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}}
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" %)^^19^^>>path:#sdfootnote19sym||name="sdfootnote19anc"]](%%)^^
166 166  
167 167  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.
168 168  
... ... @@ -174,15 +174,15 @@
174 174  
175 175  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.
176 176  
177 -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}}.
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" %)^^20^^>>path:#sdfootnote20sym||name="sdfootnote20anc"]](%%)^^.
178 178  
179 179  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).
180 180  
181 181  === 12.3.2 General mapping of VTL and SDMX data structures ===
182 182  
183 -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}}.
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" %)^^21^^>>path:#sdfootnote21sym||name="sdfootnote21anc"]](%%)^^ and the correspondent SDMX "Data Structure Definition"^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^22^^>>path:#sdfootnote22sym||name="sdfootnote22anc"]](%%)^^.
184 184  
185 -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}}
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" %)^^23^^>>path:#sdfootnote23sym||name="sdfootnote23anc"]](%%)^^
186 186  
187 187  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.
188 188  
... ... @@ -198,56 +198,70 @@
198 198  
199 199  === 12.3.3 Mapping from SDMX to VTL data structures ===
200 200  
201 -==== 12.3.3.1 Basic Mapping ====
209 +**12.3.3.1 Basic Mapping**
202 202  
203 203  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:
204 204  
205 -(% style="width:529.294px" %)
206 -|(% style="width:151px" %)**SDMX**|(% style="width:375px" %)**VTL**
207 -|(% style="width:151px" %)Dimension|(% style="width:375px" %)(Simple) Identifier
208 -|(% style="width:151px" %)TimeDimension|(% style="width:375px" %)(Time) Identifier
209 -|(% style="width:151px" %)Measure|(% style="width:375px" %)Measure
210 -|(% style="width:151px" %)DataAttribute|(% style="width:375px" %)Attribute
213 +|**SDMX**|**VTL**
214 +|Dimension|(Simple) Identifier
215 +|TimeDimension|(Time) Identifier
211 211  
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 +
212 212  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).
213 213  
214 -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.
224 +With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point.
215 215  
216 -==== 12.3.3.2 Pivot Mapping ====
226 +**12.3.3.2 Pivot Mapping**
217 217  
218 218  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.
219 219  
220 -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}}.
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
221 221  
232 +MeasureDimensions considered as a joint variable^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^24^^>>path:#sdfootnote24sym||name="sdfootnote24anc"]](%%)^^.
233 +
222 222  Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
223 223  
224 224  If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
225 225  
226 -Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
238 +^^27^^ Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
227 227  
228 228  The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation):
229 229  
230 230  * A SDMX simple dimension becomes a VTL (simple) identifier and a SDMX TimeDimension becomes a VTL (time) identifier;
231 -* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a Component;
243 +* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a
244 +
245 +Component;
246 +
232 232  * The SDMX MeasureDimension is not mapped to VTL (it disappears in the VTL Data Structure);
233 233  * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
234 234  * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
235 -** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension;
250 +** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the
251 +
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 +
254 +*
236 236  ** 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).
237 237  ** 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.
238 238  
239 239  The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
240 240  
241 -(% style="width:769.294px" %)
242 -|(% style="width:401px" %)**SDMX**|(% style="width:366px" %)**VTL**
243 -|(% style="width:401px" %)Dimension|(% style="width:366px" %)(Simple) Identifier
244 -|(% style="width:401px" %)TimeDimension|(% style="width:366px" %)(Time) Identifier
245 -|(% style="width:401px" %)MeasureDimension & one Measure|(% style="width:366px" %)(((
246 -One Measure for each Code of the SDMX MeasureDimension
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
247 247  )))
248 -|(% style="width:401px" %)DataAttribute not depending on the MeasureDimension|(% style="width:366px" %)Attribute
249 -|(% style="width:401px" %)DataAttribute depending on the MeasureDimension|(% style="width:366px" %)(((
250 -One Attribute for each Code of the SDMX MeasureDimension
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
251 251  )))
252 252  
253 253  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.
... ... @@ -255,11 +255,14 @@
255 255  At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
256 256  
257 257  * The set of SDMX observations having the same values for all the Dimensions except than the MeasureDimension become one multi-measure VTL Data Point, having one Measure for each Code Cj of the SDMX MeasureDimension;
258 -* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
280 +* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple)
281 +
282 +Identifiers, (time) Identifier and Attributes.
283 +
259 259  * 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
260 260  * 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
261 261  
262 -==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
287 +**12.3.3.3 From SDMX DataAttributes to VTL Measures**
263 263  
264 264  * 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
265 265  
... ... @@ -271,7 +271,7 @@
271 271  
272 272  === 12.3.4 Mapping from VTL to SDMX data structures ===
273 273  
274 -==== 12.3.4.1 Basic Mapping ====
299 +**12.3.4.1 Basic Mapping**
275 275  
276 276  The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
277 277  
... ... @@ -281,12 +281,11 @@
281 281  
282 282  Mapping table:
283 283  
284 -(% style="width:667.294px" %)
285 -|(% style="width:272px" %)**VTL**|(% style="width:392px" %)**SDMX**
286 -|(% style="width:272px" %)(Simple) Identifier|(% style="width:392px" %)Dimension
287 -|(% style="width:272px" %)(Time) Identifier|(% style="width:392px" %)TimeDimension
288 -|(% style="width:272px" %)Measure|(% style="width:392px" %)Measure
289 -|(% style="width:272px" %)Attribute|(% style="width:392px" %)DataAttribute
309 +|**VTL**|**SDMX**
310 +|(Simple) Identifier|Dimension
311 +|(Time) Identifier|TimeDimension
312 +|Measure|Measure
313 +|Attribute|DataAttribute
290 290  
291 291  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.
292 292  
... ... @@ -296,7 +296,7 @@
296 296  
297 297  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.
298 298  
299 -==== 12.3.4.2 Unpivot Mapping ====
323 +**12.3.4.2 Unpivot Mapping**
300 300  
301 301  An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
302 302  
... ... @@ -320,12 +320,11 @@
320 320  
321 321  The summary mapping table of the **unpivot** mapping method is the following:
322 322  
323 -(% style="width:994.294px" %)
324 -|(% style="width:306px" %)**VTL**|(% style="width:684px" %)**SDMX**
325 -|(% style="width:306px" %)(Simple) Identifier|(% style="width:684px" %)Dimension
326 -|(% style="width:306px" %)(Time) Identifier|(% style="width:684px" %)TimeDimension
327 -|(% style="width:306px" %)All Measure Components|(% style="width:684px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
328 -|(% style="width:306px" %)Attribute|(% style="width:684px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
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
329 329  
330 330  At observation / data point level:
331 331  
... ... @@ -339,7 +339,7 @@
339 339  
340 340  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.
341 341  
342 -==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ====
365 +**12.3.4.3 From VTL Measures to SDMX Data Attributes**
343 343  
344 344  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”).
345 345  
... ... @@ -347,13 +347,12 @@
347 347  
348 348  The mapping table is the following:
349 349  
350 -(% style="width:689.294px" %)
351 -|(% style="width:344px" %)**VTL**|(% style="width:341px" %)**SDMX**
352 -|(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension
353 -|(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension
354 -|(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure
355 -|(% style="width:344px" %)Other Measures|(% style="width:341px" %)DataAttribute
356 -|(% style="width:344px" %)Attribute|(% style="width:341px" %)DataAttribute
373 +|VTL|SDMX
374 +|(Simple) Identifier|Dimension
375 +|(Time) Identifier|TimeDimension
376 +|Some Measures|Measure
377 +|Other Measures|DataAttribute
378 +|Attribute|DataAttribute
357 357  
358 358  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.
359 359  
... ... @@ -371,20 +371,20 @@
371 371  
372 372  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).
373 373  
374 -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}}
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" %)^^25^^>>path:#sdfootnote25sym||name="sdfootnote25anc"]](%%)^^
375 375  
376 -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}}
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" %)^^26^^>>path:#sdfootnote26sym||name="sdfootnote26anc"]](%%)^^
377 377  
378 378  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.
379 379  
380 380  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:
381 381  
382 -* 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.
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" %)^^27^^>>path:#sdfootnote27sym||name="sdfootnote27anc"]](%%)^^ Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.
383 383  * The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts:
384 384  ** 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);
385 -** 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}}
407 +** a slash (“/”) as a separator; ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^28^^>>path:#sdfootnote28sym||name="sdfootnote28anc"]](%%)^^
386 386  
387 -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.
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" %)^^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.
388 388  
389 389  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.
390 390  
... ... @@ -400,7 +400,7 @@
400 400  
401 401  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.
402 402  
403 -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.
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" %)^^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.
404 404  
405 405  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.
406 406  
... ... @@ -408,20 +408,27 @@
408 408  
409 409  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.
410 410  
411 -In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …).
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" %)^^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.
412 412  
413 -In the example above, for all the datasets of the kind ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
435 +basic, pivot …).
414 414  
437 +In the example above, for all the datasets of the kind
438 +
439 +‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only.
440 +
415 415  It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression:
416 416  
417 417  ‘DF1(1.0.0)/POPULATION.USA’ :=
444 +
418 418  DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
419 419  
420 420  ‘DF1(1.0.0)/POPULATION.CANADA’ :=
448 +
421 421  DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
450 +
422 422  … … …
423 423  
424 -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}}
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" %)^^32^^>>path:#sdfootnote32sym||name="sdfootnote32anc"]](%%)^^
425 425  
426 426  In the direction from SDMX to VTL it is allowed to omit the value of one or more
427 427  
... ... @@ -432,6 +432,7 @@
432 432  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
433 433  
434 434  ‘DF1(1.0.0)/POPULATION.’ :=
464 +
435 435  DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
436 436  
437 437  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
... ... @@ -448,12 +448,12 @@
448 448  
449 449  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:
450 450  
451 -* 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}}
452 -* 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}}
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" %)^^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" %)^^34^^>>path:#sdfootnote34sym||name="sdfootnote34anc"]](%%)^^
453 453  
454 -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}}.
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" %)^^35^^>>path:#sdfootnote35sym||name="sdfootnote35anc"]](%%)^^.
455 455  
456 -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}}
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" %)^^36^^>>path:#sdfootnote36sym||name="sdfootnote36anc"]](%%)^^
457 457  
458 458  ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
459 459  
... ... @@ -462,8 +462,11 @@
462 462  ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
463 463  
464 464  … … …
495 +
465 465  ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
497 +
466 466  ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
499 +
467 467  … … …
468 468  
469 469  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:
... ... @@ -471,9 +471,13 @@
471 471  VTL dataset INDICATOR value COUNTRY value
472 472  
473 473  ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
507 +
474 474  ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
509 +
475 475  ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
511 +
476 476  ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
513 +
477 477  … … …
478 478  
479 479  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:
... ... @@ -502,9 +502,9 @@
502 502  
503 503  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
504 504  
505 -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.
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" %)^^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.
506 506  
507 -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}}
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" %)^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^39^^>>path:#sdfootnote39sym||name="sdfootnote39anc"]](%%)^^
508 508  
509 509  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).
510 510  
... ... @@ -512,51 +512,52 @@
512 512  
513 513  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
514 514  
515 -(% style="width:1170.29px" %)
516 -|**VTL**|(% style="width:754px" %)**SDMX**
517 -|**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}}
518 -|**Represented Variable**|(% style="width:754px" %)(((
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**|(((
519 519  **Concept** with a definite
520 520  
521 521  Representation
522 522  )))
523 -|**Value Domain**|(% style="width:754px" %)(((
559 +|**Value Domain**|(((
524 524  **Representation** (see the Structure
525 525  
526 526  Pattern in the Base Package)
527 527  )))
528 -|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
529 -|**Code**|(% style="width:754px" %)(((
564 +|**Enumerated Value Domain / Code List**|**Codelist**
565 +|**Code**|(((
530 530  **Code** (for enumerated
531 531  
532 532  DimensionComponent, Measure, DataAttribute)
533 533  )))
534 -|**Described Value Domain**|(% style="width:754px" %)(((
535 -non-enumerated** Representation**
570 +|**Described Value Domain**|(((
571 +non-enumerated** &nbsp;&nbsp;&nbsp;Representation**
536 536  
537 537  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
538 538  )))
539 -|**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
540 -| |(% style="width:754px" %)(((
541 -to a valid **value **(for non-enumerated** **Representations)
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)
542 542  )))
543 -|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
544 -|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
545 -|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
546 -|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
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
547 547  
548 548  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).
549 549  
550 -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.
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" %)^^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" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
551 551  
552 552  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
553 553  
554 -DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
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.
555 555  
556 -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.
557 -
558 558  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
559 559  
596 +[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape5" height="1" width="192"]]
597 +
560 560  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
561 561  
562 562  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.
... ... @@ -571,8 +571,7 @@
571 571  
572 572  [[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
573 573  
574 -(% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
575 -**Figure 22 – VTL Data Types**
612 +==== Figure 22 – VTL Data Types ====
576 576  
577 577  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.
578 578  
... ... @@ -579,12 +579,131 @@
579 579  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):
580 580  
581 581  
582 -**Figure 23 – VTL Basic Scalar Types**
583 583  
584 584  (((
585 -
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"]]
586 586  )))
587 587  
742 +==== Figure 23 – VTL Basic Scalar Types ====
743 +
588 588  === 12.4.2 VTL basic scalar types and SDMX data types ===
589 589  
590 590  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
... ... @@ -607,159 +607,204 @@
607 607  
608 608  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
609 609  
610 -(% style="width:823.294px" %)
611 -|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type**
612 -|(% style="width:509px" %)(((
766 +|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
767 +|(((
613 613  String
769 +
614 614  (string allowing any character)
615 -)))|(% style="width:312px" %)string
616 -|(% style="width:509px" %)(((
771 +)))|string
772 +|(((
617 617  Alpha
774 +
618 618  (string which only allows A-z)
619 -)))|(% style="width:312px" %)string
620 -|(% style="width:509px" %)(((
776 +)))|string
777 +|(((
621 621  AlphaNumeric
779 +
622 622  (string which only allows A-z and 0-9)
623 -)))|(% style="width:312px" %)string
624 -|(% style="width:509px" %)(((
781 +)))|string
782 +|(((
625 625  Numeric
784 +
626 626  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
627 -)))|(% style="width:312px" %)string
628 -|(% style="width:509px" %)(((
786 +)))|string
787 +|(((
629 629  BigInteger
789 +
630 630  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
631 -)))|(% style="width:312px" %)integer
632 -|(% style="width:509px" %)(((
791 +)))|integer
792 +|(((
633 633  Integer
634 -(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
635 -)))|(% style="width:312px" %)integer
636 -|(% style="width:509px" %)(((
794 +
795 +(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
796 +
797 +(inclusive))
798 +)))|integer
799 +|(((
637 637  Long
638 -(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
639 -)))|(% style="width:312px" %)integer
640 -|(% style="width:509px" %)(((
801 +
802 +(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
803 +
804 ++9223372036854775807 (inclusive))
805 +)))|integer
806 +|(((
641 641  Short
808 +
642 642  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
643 -)))|(% style="width:312px" %)integer
644 -|(% 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
645 -|(% style="width:509px" %)(((
810 +)))|integer
811 +|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
812 +|(((
646 646  Float
814 +
647 647  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
648 -)))|(% style="width:312px" %)number
649 -|(% style="width:509px" %)(((
816 +)))|number
817 +|(((
650 650  Double
819 +
651 651  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
652 -)))|(% style="width:312px" %)number
653 -|(% style="width:509px" %)(((
821 +)))|number
822 +|(((
654 654  Boolean
655 -(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
656 -)))|(% style="width:312px" %)boolean
657 657  
658 -(% style="width:822.294px" %)
659 -|(% colspan="2" style="width:507px" %)(((
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" %)(((
660 660  URI
832 +
661 661  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
662 -)))|(% colspan="1" style="width:311px" %)string
663 -|(% colspan="2" style="width:507px" %)(((
834 +)))|(% colspan="2" %)string
835 +| |(% colspan="2" %)(((
664 664  Count
837 +
665 665  (an integer following a sequential pattern, increasing by 1 for each occurrence)
666 -)))|(% colspan="1" style="width:311px" %)integer
667 -|(% colspan="2" style="width:507px" %)(((
839 +)))|(% colspan="2" %)integer
840 +| |(% colspan="2" %)(((
668 668  InclusiveValueRange
842 +
669 669  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
670 -)))|(% colspan="1" style="width:311px" %)number
671 -|(% colspan="2" style="width:507px" %)(((
844 +)))|(% colspan="2" %)number
845 +| |(% colspan="2" %)(((
672 672  ExclusiveValueRange
847 +
673 673  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
674 -)))|(% colspan="1" style="width:311px" %)number
675 -|(% colspan="2" style="width:507px" %)(((
849 +)))|(% colspan="2" %)number
850 +| |(% colspan="2" %)(((
676 676  Incremental
852 +
677 677  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
678 -)))|(% colspan="1" style="width:311px" %)number
679 -|(% colspan="2" style="width:507px" %)(((
854 +)))|(% colspan="2" %)number
855 +| |(% colspan="2" %)(((
680 680  ObservationalTimePeriod
857 +
681 681  (superset of StandardTimePeriod and TimeRange)
682 -)))|(% colspan="1" style="width:311px" %)time
683 -|(% colspan="2" style="width:507px" %)(((
859 +)))|(% colspan="2" %)time
860 +| |(% colspan="2" %)(((
684 684  StandardTimePeriod
685 -(superset of BasicTimePeriod and ReportingTimePeriod)
686 -)))|(% colspan="1" style="width:311px" %)time
687 -|(% colspan="2" style="width:507px" %)(((
862 +
863 +(superset of BasicTimePeriod and
864 +
865 +ReportingTimePeriod)
866 +)))|(% colspan="2" %)time
867 +| |(% colspan="2" %)(((
688 688  BasicTimePeriod
869 +
689 689  (superset of GregorianTimePeriod and DateTime)
690 -)))|(% colspan="1" style="width:311px" %)date
691 -|(% colspan="2" style="width:507px" %)(((
871 +)))|(% colspan="2" %)date
872 +| |(% colspan="2" %)(((
692 692  GregorianTimePeriod
874 +
693 693  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
694 -)))|(% colspan="1" style="width:311px" %)date
695 -|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date
696 -|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date
697 -|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date
698 -|(% colspan="2" style="width:507px" %)(((
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" %)(((
699 699  ReportingTimePeriod
700 -(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
701 -)))|(% colspan="1" style="width:311px" %)time_period
702 -|(% colspan="2" style="width:507px" %)(((
882 +
883 +(superset of RepostingYear, ReportingSemester,
884 +
885 +ReportingTrimester, ReportingQuarter,
886 +
887 +ReportingMonth, ReportingWeek, ReportingDay)
888 +)))|(% colspan="2" %)time_period
889 +| |(% colspan="2" %)(((
703 703  ReportingYear
891 +
704 704  (YYYY-A1 – 1 year period)
705 -)))|(% colspan="1" style="width:311px" %)time_period
706 -|(% colspan="2" style="width:507px" %)(((
893 +)))|(% colspan="2" %)time_period
894 +| |(% colspan="2" %)(((
707 707  ReportingSemester
896 +
708 708  (YYYY-Ss – 6 month period)
709 -)))|(% colspan="1" style="width:311px" %)time_period
710 -|(% colspan="2" style="width:507px" %)(((
898 +)))|(% colspan="2" %)time_period
899 +| |(% colspan="2" %)(((
711 711  ReportingTrimester
901 +
712 712  (YYYY-Tt – 4 month period)
713 -)))|(% colspan="1" style="width:311px" %)time_period
714 -|(% colspan="2" style="width:507px" %)(((
903 +)))|(% colspan="2" %)time_period
904 +| |(% colspan="2" %)(((
715 715  ReportingQuarter
906 +
716 716  (YYYY-Qq – 3 month period)
717 -)))|(% colspan="1" style="width:311px" %)time_period
718 -|(% colspan="2" style="width:507px" %)(((
908 +)))|(% colspan="2" %)time_period
909 +| |(% colspan="2" %)(((
719 719  ReportingMonth
911 +
720 720  (YYYY-Mmm – 1 month period)
721 -)))|(% colspan="1" style="width:311px" %)time_period
722 -|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period
723 -|(% 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" %)
724 -|(% colspan="1" style="width:507px" %)(((
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" %)(((
725 725  ReportingDay
920 +
726 726  (YYYY-Dddd – 1 day period)
727 -)))|(% colspan="2" style="width:312px" %)time_period
728 -|(% colspan="1" style="width:507px" %)(((
922 +)))|(% colspan="2" %)time_period|
923 +|(% colspan="2" %)(((
729 729  DateTime
925 +
730 730  (YYYY-MM-DDThh:mm:ss)
731 -)))|(% colspan="2" style="width:312px" %)date
732 -|(% colspan="1" style="width:507px" %)(((
927 +)))|(% colspan="2" %)date|
928 +|(% colspan="2" %)(((
733 733  TimeRange
930 +
734 734  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
735 -)))|(% colspan="2" style="width:312px" %)time
736 -|(% colspan="1" style="width:507px" %)(((
932 +)))|(% colspan="2" %)time|
933 +|(% colspan="2" %)(((
737 737  Month
935 +
738 738  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
739 -)))|(% colspan="2" style="width:312px" %)string
740 -|(% colspan="1" style="width:507px" %)(((
937 +)))|(% colspan="2" %)string|
938 +|(% colspan="2" %)(((
741 741  MonthDay
940 +
742 742  (~-~-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)
743 -)))|(% colspan="2" style="width:312px" %)string
744 -|(% colspan="1" style="width:507px" %)(((
942 +)))|(% colspan="2" %)string|
943 +|(% colspan="2" %)(((
745 745  Day
945 +
746 746  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
747 -)))|(% colspan="2" style="width:312px" %)string
748 -|(% colspan="1" style="width:507px" %)(((
947 +)))|(% colspan="2" %)string|
948 +|(% colspan="2" %)(((
749 749  Time
950 +
750 750  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
751 -)))|(% colspan="2" style="width:312px" %)string
752 -|(% colspan="1" style="width:507px" %)(((
952 +)))|(% colspan="2" %)string|
953 +|(% colspan="2" %)(((
753 753  Duration
955 +
754 754  (corresponds to XML Schema xs:duration datatype)
755 -)))|(% colspan="2" style="width:312px" %)duration
756 -|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable
757 -|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable
758 -|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
759 -|(% colspan="1" style="width:507px" %)DataSetReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
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|
760 760  
761 -(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %)
762 -**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
963 +==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
763 763  
764 764  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).
765 765  
... ... @@ -767,32 +767,39 @@
767 767  
768 768  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
769 769  
770 -(% style="width:1073.29px" %)
771 -|(% style="width:207px" %)(((
772 -**VTL basic scalar type**
773 -)))|(% style="width:462px" %)(((
774 -**Default SDMX data type (BasicComponentDataType)**
775 -)))|(% style="width:402px" %)**Default output format**
776 -|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string)
777 -|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float)
778 -|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int)
779 -|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z
780 -|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above)
781 -|(% style="width:207px" %)time_period|(% style="width:462px" %)(((
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|(((
782 782  ReportingTimePeriod
989 +
783 783  (StandardReportingPeriod)
784 -)))|(% style="width:402px" %)(((
991 +)))|(((
785 785  YYYY-Pppp
993 +
786 786  (according to SDMX )
787 787  )))
788 -|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)(((
996 +|Duration|Duration|(((
789 789  Like XML (xs:duration)
998 +
790 790  PnYnMnDTnHnMnS
791 791  )))
792 -|(% style="width:207px" %)Boolean|(% style="width:462px" %)Boolean|(% style="width:402px" %)Like XML (xs:boolean) with the values "true" or "false"
1001 +|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
793 793  
794 -(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes-1" %)
795 -**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
1003 +==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
796 796  
797 797  In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
798 798  
... ... @@ -846,7 +846,7 @@
846 846  |N|fixed number of digits used in the preceding textual representation of the month or the day
847 847  | |
848 848  
849 -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}}.
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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
850 850  
851 851  === 12.4.5 Null Values ===
852 852  
... ... @@ -864,8 +864,10 @@
864 864  
865 865  A different format can be specified in the attribute "vtlLiteralFormat" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model).
866 866  
867 -Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL TransformationScheme.
1075 +Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL
868 868  
1077 +TransformationScheme.
1078 +
869 869  In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
870 870  
871 871  {{putFootnotes/}}