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

From version 5.4
edited by Helena
on 2025/05/16 08:23
Change comment: There is no comment for this version
To version 6.1
edited by Helena
on 2025/05/16 09:09
Change comment: There is no comment for this version

Summary

Details

Page properties
Content
... ... @@ -53,10 +53,8 @@
53 53  
54 54  The generic structure of the URN is the following:
55 55  
56 -SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id
56 +SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id (maintainedobject-version).*container-object-id.object-id
57 57  
58 -(maintainedobject-version).*container-object-id.object-id
59 -
60 60  The **SDMXprefix** is "urn:sdmx:org", always the same for all SDMX artefacts.
61 61  
62 62  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".
... ... @@ -68,10 +68,7 @@
68 68  The maintainedobject-id is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable{{footnote}}i.e., the artefact belongs to a maintainable class{{/footnote}}, coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
69 69  
70 70  * if the artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the Dataflow name (dataflow-id);
71 -* if the artefact is a Dimension, Measure, TimeDimension or DataAttribute, which are not maintainable and belong to the
72 -
73 -DataStructure maintainable class, the maintainedobject-id is the name of the DataStructure (dataStructure-id) which the artefact belongs to;
74 -
69 +* if the artefact is a Dimension, Measure, TimeDimension or DataAttribute, which are not maintainable and belong to the DataStructure maintainable class, the maintainedobject-id is the name of the DataStructure (dataStructure-id) which the artefact belongs to;
75 75  * if the artefact is a Concept, which is not maintainable and belongs to the ConceptScheme maintainable class, the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id) which the artefact belongs to;
76 76  * if the artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the Codelist name (codelist-id).
77 77  
... ... @@ -87,9 +87,7 @@
87 87  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}}:
88 88  
89 89  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
90 -
91 91  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
92 -
93 93  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
94 94  
95 95  === 12.2.3 Abbreviation of the URN ===
... ... @@ -98,10 +98,10 @@
98 98  
99 99  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.
100 100  
101 -* 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** &nbsp;**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:
94 +* 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:
102 102  ** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist.
103 -* 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^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^13^^>>path:#sdfootnote13sym||name="sdfootnote13anc"]](%%)^^, 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" %)^^14^^>>path:#sdfootnote14sym||name="sdfootnote14anc"]](%%)^^.
104 -* 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" %)^^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).
96 +* 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}}.
97 +* 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).
105 105  * 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;
106 106  ** 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;
107 107  ** 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;
... ... @@ -114,9 +114,7 @@
114 114  For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
115 115  
116 116  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
117 -
118 118  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
119 -
120 120  'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
121 121  
122 122  by omitting all the non-essential parts would become simply:
... ... @@ -123,11 +123,11 @@
123 123  
124 124  DFR := DF1 + DF2
125 125  
126 -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" %)^^16^^>>path:#sdfootnote16sym||name="sdfootnote16anc"]](%%)^^:
117 +The references to the Codelists can be simplified similarly. For example, given the non-abbreviated reference to the Codelist AG:CL_FREQ(1.0.0), which is{{footnote}}Single quotes are needed because this reference is not a VTL regular name.{{/footnote}}:
127 127  
128 128  'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
129 129  
130 -if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply^^19^^:
121 +if the Codelist is referenced from a RulesetScheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply{{footnote}}Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}:
131 131  
132 132  CL_FREQ
133 133  
... ... @@ -141,7 +141,7 @@
141 141  
142 142  SECTOR
143 143  
144 -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" %)^^17^^>>path:#sdfootnote17sym||name="sdfootnote17anc"]](%%)^^:
135 +For example, the Transformation for renaming the component SECTOR of the Dataflow DF1 into SEC can be written as{{footnote}}The result DFR(1.0.0) is be equal to DF1(1.0.0) save that the component SECTOR is called SEC{{/footnote}}:
145 145  
146 146  'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
147 147  
... ... @@ -173,9 +173,9 @@
173 173  
174 174  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.
175 175  
176 -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" %)^^18^^>>path:#sdfootnote18sym||name="sdfootnote18anc"]](%%)^^.
167 +In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist, while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation{{footnote}}Rulesets of this kind cannot be reused when the referenced Concept has a different representation.{{/footnote}}.
177 177  
178 -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" %)^^19^^>>path:#sdfootnote19sym||name="sdfootnote19anc"]](%%)^^
169 +In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called "valueDomain" and "variable" for the Datapoint Rulesets and "ruleValueDomain", "ruleVariable", "condValueDomain" "condVariable" for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific Ruleset definition statement and cannot be mapped to SDMX.{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}}
179 179  
180 180  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.
181 181  
... ... @@ -187,15 +187,15 @@
187 187  
188 188  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.
189 189  
190 -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" %)^^20^^>>path:#sdfootnote20sym||name="sdfootnote20anc"]](%%)^^.
181 +In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged{{footnote}}If a calculated artefact is persistent, it needs a persistent definition, i.e. a SDMX definition in a SDMX environment. In addition, possible calculated artefact that are not persistent may require a SDMX definition, for example when the result of a non-persistent calculation is disseminated through SDMX tools (like an inquiry tool).{{/footnote}}.
191 191  
192 192  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).
193 193  
194 194  === 12.3.2 General mapping of VTL and SDMX data structures ===
195 195  
196 -This section makes reference to the VTL "Model for data and their structure"^^[[(% class="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" %)^^22^^>>path:#sdfootnote22sym||name="sdfootnote22anc"]](%%)^^.
187 +This section makes reference to the VTL "Model for data and their structure"{{footnote}}See the VTL 2.0 User Manual{{/footnote}} and the correspondent SDMX "Data Structure Definition"{{footnote}}See the SDMX Standards Section 2 – Information Model{{/footnote}}.
197 197  
198 -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" %)^^23^^>>path:#sdfootnote23sym||name="sdfootnote23anc"]](%%)^^
189 +The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).{{footnote}}Besides the mapping between one SDMX Dataflow and one VTL Data Set, it is also possible to map distinct parts of a SDMX Dataflow to different VTL Data Set, as explained in a following paragraph.{{/footnote}}
199 199  
200 200  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.
201 201  
... ... @@ -215,32 +215,28 @@
215 215  
216 216  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:
217 217  
218 -|**SDMX**|**VTL**
219 -|Dimension|(Simple) Identifier
220 -|TimeDimension|(Time) Identifier
209 +(% style="width:529.294px" %)
210 +|(% style="width:151px" %)**SDMX**|(% style="width:375px" %)**VTL**
211 +|(% style="width:151px" %)Dimension|(% style="width:375px" %)(Simple) Identifier
212 +|(% style="width:151px" %)TimeDimension|(% style="width:375px" %)(Time) Identifier
213 +|(% style="width:151px" %)Measure|(% style="width:375px" %)Measure
214 +|(% style="width:151px" %)DataAttribute|(% style="width:375px" %)Attribute
221 221  
222 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape4" height="1" width="192"]]
223 -
224 -|Measure|Measure
225 -|DataAttribute|Attribute
226 -
227 227  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).
228 228  
229 -With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point.
218 +With the Basic mapping, one SDMX observation{{footnote}}Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.{{/footnote}} generates one VTL data point.
230 230  
231 -**12.3.3.2 Pivot Mapping**
220 +==== 12.3.3.2 Pivot Mapping ====
232 232  
233 233  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.
234 234  
235 -In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the
224 +In SDMX 2.1 the MeasureDimension was a subclass of DimensionComponent like Dimension and TimeDimension. In the current SDMX version, this subclass does not exist anymore, however a Dimension can have the role of measure dimension (i.e. a Dimension that contributes to the identification of the measures). In SDMX 2.1 a DataStructure could have zero or one MeasureDimensions, in the current version of the standard, from zero to many Dimension may have the role of measure dimension. Hereinafter a Dimension that plays the role of measure dimension is referenced for simplicity as “MeasureDimension“, i.e. maintaining the capital letters and the courier font even if the MeasureDimension is not anymore a class in the SDMX Information Model of the current SDMX version. For the sake of simplicity, the description below considers just one Dimension having the role of MeasureDimension (i.e., the more simple and common case). Nevertheless, it maintains its validity also if in the DataStructure there are more dimension with the role of MeasureDimensions: in this case what is said about the MeasureDimension must be applied to the combination of all the MeasureDimensions considered as a joint variable{{footnote}}E.g., if in the data structure there exist 3 Dimensions C,D,E having the role of MeasureDimension, they should be considered as a joint MeasureDimension Z=(C,D,E); therefore when the description says “each possible value Cj of the MeasureDimension …” it means “each possible combination of values (Cj, Dk, Ew) of the joint MeasureDimension Z=(C,D,E)”.{{/footnote}}.
236 236  
237 -MeasureDimensions considered as a joint variable^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^24^^>>path:#sdfootnote24sym||name="sdfootnote24anc"]](%%)^^.
238 -
239 239  Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
240 240  
241 241  If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
242 242  
243 -^^27^^ Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
230 +Here an SDMX observation is meant to correspond to one combination of values of the DimensionComponents.
244 244  
245 245  The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation):
246 246  
... ... @@ -262,19 +262,16 @@
262 262  
263 263  The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
264 264  
265 -|**SDMX**|**VTL**
266 -|Dimension|(Simple) Identifier
267 -|TimeDimension|(Time) Identifier
268 -|MeasureDimension & one Measure|(((
269 -One Measure for each Code of the
270 -
271 -SDMX MeasureDimension
252 +(% style="width:769.294px" %)
253 +|(% style="width:401px" %)**SDMX**|(% style="width:366px" %)**VTL**
254 +|(% style="width:401px" %)Dimension|(% style="width:366px" %)(Simple) Identifier
255 +|(% style="width:401px" %)TimeDimension|(% style="width:366px" %)(Time) Identifier
256 +|(% style="width:401px" %)MeasureDimension & one Measure|(% style="width:366px" %)(((
257 +One Measure for each Code of the SDMX MeasureDimension
272 272  )))
273 -|DataAttribute not depending on the MeasureDimension|Attribute
274 -|DataAttribute depending on the MeasureDimension|(((
275 -One Attribute for each Code of the
276 -
277 -SDMX MeasureDimension
259 +|(% style="width:401px" %)DataAttribute not depending on the MeasureDimension|(% style="width:366px" %)Attribute
260 +|(% style="width:401px" %)DataAttribute depending on the MeasureDimension|(% style="width:366px" %)(((
261 +One Attribute for each Code of the SDMX MeasureDimension
278 278  )))
279 279  
280 280  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.
... ... @@ -289,7 +289,7 @@
289 289  * 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
290 290  * 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
291 291  
292 -**12.3.3.3 From SDMX DataAttributes to VTL Measures**
276 +==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
293 293  
294 294  * 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
295 295  
... ... @@ -301,7 +301,7 @@
301 301  
302 302  === 12.3.4 Mapping from VTL to SDMX data structures ===
303 303  
304 -**12.3.4.1 Basic Mapping**
288 +==== 12.3.4.1 Basic Mapping ====
305 305  
306 306  The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
307 307  
... ... @@ -311,11 +311,12 @@
311 311  
312 312  Mapping table:
313 313  
314 -|**VTL**|**SDMX**
315 -|(Simple) Identifier|Dimension
316 -|(Time) Identifier|TimeDimension
317 -|Measure|Measure
318 -|Attribute|DataAttribute
298 +(% style="width:667.294px" %)
299 +|(% style="width:272px" %)**VTL**|(% style="width:392px" %)**SDMX**
300 +|(% style="width:272px" %)(Simple) Identifier|(% style="width:392px" %)Dimension
301 +|(% style="width:272px" %)(Time) Identifier|(% style="width:392px" %)TimeDimension
302 +|(% style="width:272px" %)Measure|(% style="width:392px" %)Measure
303 +|(% style="width:272px" %)Attribute|(% style="width:392px" %)DataAttribute
319 319  
320 320  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.
321 321  
... ... @@ -325,7 +325,7 @@
325 325  
326 326  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.
327 327  
328 -**12.3.4.2 Unpivot Mapping**
313 +==== 12.3.4.2 Unpivot Mapping ====
329 329  
330 330  An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
331 331  
... ... @@ -349,11 +349,12 @@
349 349  
350 350  The summary mapping table of the **unpivot** mapping method is the following:
351 351  
352 -|**VTL**|**SDMX**
353 -|(Simple) Identifier|Dimension
354 -|(Time) Identifier|TimeDimension
355 -|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
356 -|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
337 +(% style="width:994.294px" %)
338 +|(% style="width:306px" %)**VTL**|(% style="width:684px" %)**SDMX**
339 +|(% style="width:306px" %)(Simple) Identifier|(% style="width:684px" %)Dimension
340 +|(% style="width:306px" %)(Time) Identifier|(% style="width:684px" %)TimeDimension
341 +|(% style="width:306px" %)All Measure Components|(% style="width:684px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
342 +|(% style="width:306px" %)Attribute|(% style="width:684px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
357 357  
358 358  At observation / data point level:
359 359  
... ... @@ -367,7 +367,7 @@
367 367  
368 368  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.
369 369  
370 -**12.3.4.3 From VTL Measures to SDMX Data Attributes**
356 +==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ====
371 371  
372 372  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”).
373 373  
... ... @@ -375,12 +375,13 @@
375 375  
376 376  The mapping table is the following:
377 377  
378 -|VTL|SDMX
379 -|(Simple) Identifier|Dimension
380 -|(Time) Identifier|TimeDimension
381 -|Some Measures|Measure
382 -|Other Measures|DataAttribute
383 -|Attribute|DataAttribute
364 +(% style="width:689.294px" %)
365 +|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX
366 +|(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension
367 +|(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension
368 +|(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure
369 +|(% style="width:344px" %)Other Measures|(% style="width:341px" %)DataAttribute
370 +|(% style="width:344px" %)Attribute|(% style="width:341px" %)DataAttribute
384 384  
385 385  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.
386 386  
... ... @@ -398,20 +398,20 @@
398 398  
399 399  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).
400 400  
401 -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" %)^^25^^>>path:#sdfootnote25sym||name="sdfootnote25anc"]](%%)^^
388 +As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.{{footnote}}A typical example of this kind is the validation, and more in general the manipulation, of individual time series belonging to the same Dataflow, identifiable through the DimensionComponents of the Dataflow except the TimeDimension. The coding of these kind of operations might be simplified by mapping distinct time series (i.e. different parts of a SDMX Dataflow) to distinct VTL Data Sets.{{/footnote}}
402 402  
403 -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" %)^^26^^>>path:#sdfootnote26sym||name="sdfootnote26anc"]](%%)^^
390 +Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL Data Sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.{{footnote}}Please note that this kind of mapping is only an option at disposal of the definer of VTL Transformations; in fact it remains always possible to manipulate the needed parts of SDMX Dataflows by means of VTL operators (e.g. “sub”, “filter”, “calc”, “union …), maintaining a mapping one-to-one between SDMX Dataflows and VTL Data Sets.{{/footnote}}
404 404  
405 405  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.
406 406  
407 407  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:
408 408  
409 -* 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" %)^^27^^>>path:#sdfootnote27sym||name="sdfootnote27anc"]](%%)^^ Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.
396 +* For a given SDMX Dataflow, the user (VTL definer) declares the DimensionComponents on which the mapping will be based, in a given order.{{footnote}}This definition is made through the ToVtlSubspace and ToVtlSpaceKey classes and/or the FromVtlSuperspace and FromVtlSpaceKey classes, depending on the direction of the mapping (“key” means “dimension”). The mapping of Dataflow subsets can be applied independently in the two directions, also according to different Dimensions. When no Dimension is declared for a given direction, it is assumed that the option of mapping different parts of a SDMX Dataflow to different VTL Data Sets is not used.{{/footnote}} Following the example above, imagine that the user declares the Dimensions INDICATOR and COUNTRY.
410 410  * The VTL Data Set is given a name using a special notation also called “ordered concatenation” and composed of the following parts:
411 411  ** 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);
412 -** a slash (“/”) as a separator; ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^28^^>>path:#sdfootnote28sym||name="sdfootnote28anc"]](%%)^^
399 +** a slash (“/”) as a separator;{{footnote}}As a consequence of this formalism, a slash in the name of the VTL Data Set assumes the specific meaning of separator between the name of the Dataflow and the values of some of its Dimensions.{{/footnote}}
413 413  
414 -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" %)^^29^^>>path:#sdfootnote29sym||name="sdfootnote29anc"]](%%)^^. For example POPULATION.USA would mean that such a VTL Data Set is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.
401 +The reference to a specific part of the SDMX Dataflow above, expressed as the concatenation of the values that the SDMX DimensionComponents declared above must have, separated by dots (“.”) and written in the order in which these DimensionComponents are defined{{footnote}}This is the order in which the dimensions are defined in the ToVtlSpaceKey class or in the FromVtlSpaceKey class, depending on the direction of the mapping.{{/footnote}}. For example POPULATION.USA would mean that such a VTL Data Set is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.
415 415  
416 416  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.
417 417  
... ... @@ -427,7 +427,7 @@
427 427  
428 428  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.
429 429  
430 -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" %)^^30^^>>path:#sdfootnote30sym||name="sdfootnote30anc"]](%%)^^ need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively.
417 +As already said, the mapping from SDMX to VTL happens when the SDMX dataflows are operand of VTL Transformations, instead the mapping from VTL to SDMX happens when the VTL Data Sets that is result of Transformations{{footnote}}It should be remembered that, according to the VTL consistency rules, a given VTL dataset cannot be the result of more than one VTL Transformation.{{/footnote}} need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively.
431 431  
432 432  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.
433 433  
... ... @@ -435,7 +435,7 @@
435 435  
436 436  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.
437 437  
438 -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" %)^^31^^>>path:#sdfootnote31sym||name="sdfootnote31anc"]](%%)^^. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
425 +In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e.
439 439  
440 440  basic, pivot …).
441 441  
... ... @@ -455,7 +455,7 @@
455 455  
456 456  … … …
457 457  
458 -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" %)^^32^^>>path:#sdfootnote32sym||name="sdfootnote32anc"]](%%)^^
445 +In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}}
459 459  
460 460  In the direction from SDMX to VTL it is allowed to omit the value of one or more
461 461  
... ... @@ -483,12 +483,12 @@
483 483  
484 484  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:
485 485  
486 -* 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" %)^^33^^>>path:#sdfootnote33sym||name="sdfootnote33anc"]](%%)^^
487 -* 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" %)^^34^^>>path:#sdfootnote34sym||name="sdfootnote34anc"]](%%)^^
473 +* each part is calculated as a VTL derived Data Set, result of a dedicated VTL Transformation;{{footnote}}If the whole DF2(1.0) is calculated by means of just one VTL Transformation, then the mapping between the SDMX Dataflow and the corresponding VTL dataset is one-to-one and this kind of mapping (one SDMX Dataflow to many VTL datasets) does not apply.{{/footnote}}
474 +* the data structure of all these VTL Data Sets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.{{footnote}}This is possible as each VTL dataset corresponds to one particular combination of values of INDICATOR and COUNTRY.{{/footnote}}
488 488  
489 -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" %)^^35^^>>path:#sdfootnote35sym||name="sdfootnote35anc"]](%%)^^.
476 +Under these hypothesis, such derived VTL Data Sets can be mapped to DF2(1.0.0) by declaring the DimensionComponents INDICATOR and COUNTRY as mapping dimensions{{footnote}}The mapping dimensions are defined as FromVtlSpaceKeys of the FromVtlSuperSpace of the VtlDataflowMapping relevant to DF2(1.0).{{/footnote}}.
490 490  
491 -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" %)^^36^^>>path:#sdfootnote36sym||name="sdfootnote36anc"]](%%)^^
478 +The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:{{footnote}}the symbol of the VTL persistent assignment is used (<-){{/footnote}}
492 492  
493 493  ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
494 494  
... ... @@ -544,9 +544,9 @@
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
546 546  
547 -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" %)^^37^^>>path:#sdfootnote37sym||name="sdfootnote37anc"]](%%)^^, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
534 +DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
548 548  
549 -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" %)^^38^^>>path:#sdfootnote38sym||name="sdfootnote38anc"]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^39^^>>path:#sdfootnote39sym||name="sdfootnote39anc"]](%%)^^
536 +Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX Dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets.{{footnote}}In case the ordered concatenation notation from VTL to SDMX is used, the set of Transformations described above is implicitly performed; therefore, in order to test the overall compliance of the VTL program to the VTL consistency rules, these implicit Transformations have to be considered as part of the VTL program even if they are not explicitly coded.{{/footnote}}
550 550  
551 551  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).
552 552  
... ... @@ -554,52 +554,51 @@
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  
557 -|VTL|SDMX
558 -|**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^^
559 -|**Represented Variable**|(((
544 +(% style="width:1170.29px" %)
545 +|**VTL**|(% style="width:754px" %)**SDMX**
546 +|**Data Set Component**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
547 +|**Represented Variable**|(% style="width:754px" %)(((
560 560  **Concept** with a definite
561 561  
562 562  Representation
563 563  )))
564 -|**Value Domain**|(((
552 +|**Value Domain**|(% style="width:754px" %)(((
565 565  **Representation** (see the Structure
566 566  
567 567  Pattern in the Base Package)
568 568  )))
569 -|**Enumerated Value Domain / Code List**|**Codelist**
570 -|**Code**|(((
557 +|**Enumerated Value Domain / Code List**|(% style="width:754px" %)**Codelist**
558 +|**Code**|(% style="width:754px" %)(((
571 571  **Code** (for enumerated
572 572  
573 573  DimensionComponent, Measure, DataAttribute)
574 574  )))
575 -|**Described Value Domain**|(((
576 -non-enumerated** &nbsp;&nbsp;&nbsp;Representation**
563 +|**Described Value Domain**|(% style="width:754px" %)(((
564 +non-enumerated** Representation**
577 577  
578 578  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
579 579  )))
580 -|**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
581 -| |(((
582 -to a valid **value &nbsp;&nbsp;&nbsp;**(for non-enumerated** &nbsp;&nbsp;&nbsp;**
583 -
584 -Representations)
568 +|**Value**|(% style="width:754px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
569 +| |(% style="width:754px" %)(((
570 +to a valid **value **(for non-enumerated** **Representations)
585 585  )))
586 -|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
587 -|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
588 -|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
589 -|**Set list**|This abstraction does not exist in SDMX
572 +|**Value Domain Subset / Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
573 +|**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
574 +|**Described Value Domain Subset / Described Set**|(% style="width:754px" %)This abstraction does not exist in SDMX
575 +|**Set list**|(% style="width:754px" %)This abstraction does not exist in SDMX
590 590  
591 591  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).
592 592  
593 -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" %)^^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" %)^^41^^>>path:#sdfootnote41sym||name="sdfootnote41anc"]](%%)^^ This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
579 +Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL Rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists). As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear{{footnote}}By using represented variables, VTL can assume that data structures having the same variables as identifiers can be composed one another because the correspondent values can match.{{/footnote}}, while the SDMX Concepts can have different Representations in different DataStructures.{{footnote}}A Concept becomes a Component in a DataStructureDefinition, and Components can have different LocalRepresentations in different DataStructureDefinitions, also overriding the (possible) base representation of the Concept.{{/footnote}} This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
594 594  
595 595  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
596 596  
597 -DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
583 +DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
598 598  
585 +if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
586 +
599 599  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
600 600  
601 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_59eee18f.gif||alt="Shape5" height="1" width="192"]]
602 -
603 603  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
604 604  
605 605  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.
... ... @@ -614,7 +614,8 @@
614 614  
615 615  [[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]]
616 616  
617 -==== Figure 22 – VTL Data Types ====
603 +(% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %)
604 +**Figure 22 – VTL Data Types**
618 618  
619 619  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.
620 620  
... ... @@ -621,131 +621,12 @@
621 621  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):
622 622  
623 623  
611 +**Figure 23 – VTL Basic Scalar Types**
624 624  
625 625  (((
626 -//n//
627 -
628 -//a//
629 -
630 -//e//
631 -
632 -//l//
633 -
634 -//o//
635 -
636 -//o//
637 -
638 -//B//
639 -
640 -//n//
641 -
642 -//o//
643 -
644 -//i//
645 -
646 -//t//
647 -
648 -//a//
649 -
650 -//r//
651 -
652 -//u//
653 -
654 -//D//
655 -
656 -//d//
657 -
658 -//o//
659 -
660 -//i//
661 -
662 -//r//
663 -
664 -//e//
665 -
666 -//p//
667 -
668 -//_//
669 -
670 -//e//
671 -
672 -//m//
673 -
674 -//i//
675 -
676 -//T//
677 -
678 -//e//
679 -
680 -//t//
681 -
682 -//a//
683 -
684 -//D//
685 -
686 -//e//
687 -
688 -//m//
689 -
690 -//i//
691 -
692 -//T//
693 -
694 -//r//
695 -
696 -//e//
697 -
698 -//g//
699 -
700 -//e//
701 -
702 -//t//
703 -
704 -//n//
705 -
706 -//I//
707 -
708 -//r//
709 -
710 -//e//
711 -
712 -//b//
713 -
714 -//m//
715 -
716 -//u//
717 -
718 -//N//
719 -
720 -//g//
721 -
722 -//n//
723 -
724 -//i//
725 -
726 -//r//
727 -
728 -//t//
729 -
730 -//S//
731 -
732 -//r//
733 -
734 -//a//
735 -
736 -//l//
737 -
738 -//a//
739 -
740 -//c//
741 -
742 -//S//
743 -
744 -[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_82d45833.gif||alt="Shape6" height="231" width="184"]]
614 +
745 745  )))
746 746  
747 -==== Figure 23 – VTL Basic Scalar Types ====
748 -
749 749  === 12.4.2 VTL basic scalar types and SDMX data types ===
750 750  
751 751  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
... ... @@ -768,204 +768,159 @@
768 768  
769 769  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
770 770  
771 -|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
772 -|(((
639 +(% style="width:823.294px" %)
640 +|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type**
641 +|(% style="width:509px" %)(((
773 773  String
774 -
775 775  (string allowing any character)
776 -)))|string
777 -|(((
644 +)))|(% style="width:312px" %)string
645 +|(% style="width:509px" %)(((
778 778  Alpha
779 -
780 780  (string which only allows A-z)
781 -)))|string
782 -|(((
648 +)))|(% style="width:312px" %)string
649 +|(% style="width:509px" %)(((
783 783  AlphaNumeric
784 -
785 785  (string which only allows A-z and 0-9)
786 -)))|string
787 -|(((
652 +)))|(% style="width:312px" %)string
653 +|(% style="width:509px" %)(((
788 788  Numeric
789 -
790 790  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
791 -)))|string
792 -|(((
656 +)))|(% style="width:312px" %)string
657 +|(% style="width:509px" %)(((
793 793  BigInteger
794 -
795 795  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
796 -)))|integer
797 -|(((
660 +)))|(% style="width:312px" %)integer
661 +|(% style="width:509px" %)(((
798 798  Integer
799 -
800 -(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
801 -
802 -(inclusive))
803 -)))|integer
804 -|(((
663 +(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
664 +)))|(% style="width:312px" %)integer
665 +|(% style="width:509px" %)(((
805 805  Long
806 -
807 -(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
808 -
809 -+9223372036854775807 (inclusive))
810 -)))|integer
811 -|(((
667 +(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
668 +)))|(% style="width:312px" %)integer
669 +|(% style="width:509px" %)(((
812 812  Short
813 -
814 814  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
815 -)))|integer
816 -|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
817 -|(((
672 +)))|(% style="width:312px" %)integer
673 +|(% style="width:509px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:312px" %)number
674 +|(% style="width:509px" %)(((
818 818  Float
819 -
820 820  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
821 -)))|number
822 -|(((
677 +)))|(% style="width:312px" %)number
678 +|(% style="width:509px" %)(((
823 823  Double
824 -
825 825  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
826 -)))|number
827 -|(((
681 +)))|(% style="width:312px" %)number
682 +|(% style="width:509px" %)(((
828 828  Boolean
684 +(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
685 +)))|(% style="width:312px" %)boolean
829 829  
830 -(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
831 -
832 -binary-valued logic: {true, false})
833 -)))|boolean
834 -
835 -| |(% colspan="2" %)(((
687 +(% style="width:822.294px" %)
688 +|(% colspan="2" style="width:507px" %)(((
836 836  URI
837 -
838 838  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
839 -)))|(% colspan="2" %)string
840 -| |(% colspan="2" %)(((
691 +)))|(% colspan="1" style="width:311px" %)string
692 +|(% colspan="2" style="width:507px" %)(((
841 841  Count
842 -
843 843  (an integer following a sequential pattern, increasing by 1 for each occurrence)
844 -)))|(% colspan="2" %)integer
845 -| |(% colspan="2" %)(((
695 +)))|(% colspan="1" style="width:311px" %)integer
696 +|(% colspan="2" style="width:507px" %)(((
846 846  InclusiveValueRange
847 -
848 848  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
849 -)))|(% colspan="2" %)number
850 -| |(% colspan="2" %)(((
699 +)))|(% colspan="1" style="width:311px" %)number
700 +|(% colspan="2" style="width:507px" %)(((
851 851  ExclusiveValueRange
852 -
853 853  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
854 -)))|(% colspan="2" %)number
855 -| |(% colspan="2" %)(((
703 +)))|(% colspan="1" style="width:311px" %)number
704 +|(% colspan="2" style="width:507px" %)(((
856 856  Incremental
857 -
858 858  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
859 -)))|(% colspan="2" %)number
860 -| |(% colspan="2" %)(((
707 +)))|(% colspan="1" style="width:311px" %)number
708 +|(% colspan="2" style="width:507px" %)(((
861 861  ObservationalTimePeriod
862 -
863 863  (superset of StandardTimePeriod and TimeRange)
864 -)))|(% colspan="2" %)time
865 -| |(% colspan="2" %)(((
711 +)))|(% colspan="1" style="width:311px" %)time
712 +|(% colspan="2" style="width:507px" %)(((
866 866  StandardTimePeriod
867 -
868 -(superset of BasicTimePeriod and
869 -
870 -ReportingTimePeriod)
871 -)))|(% colspan="2" %)time
872 -| |(% colspan="2" %)(((
714 +(superset of BasicTimePeriod and ReportingTimePeriod)
715 +)))|(% colspan="1" style="width:311px" %)time
716 +|(% colspan="2" style="width:507px" %)(((
873 873  BasicTimePeriod
874 -
875 875  (superset of GregorianTimePeriod and DateTime)
876 -)))|(% colspan="2" %)date
877 -| |(% colspan="2" %)(((
719 +)))|(% colspan="1" style="width:311px" %)date
720 +|(% colspan="2" style="width:507px" %)(((
878 878  GregorianTimePeriod
879 -
880 880  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
881 -)))|(% colspan="2" %)date
882 -| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date
883 -| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date
884 -| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date
885 -| |(% colspan="2" %)(((
723 +)))|(% colspan="1" style="width:311px" %)date
724 +|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date
725 +|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date
726 +|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date
727 +|(% colspan="2" style="width:507px" %)(((
886 886  ReportingTimePeriod
887 -
888 -(superset of RepostingYear, ReportingSemester,
889 -
890 -ReportingTrimester, ReportingQuarter,
891 -
892 -ReportingMonth, ReportingWeek, ReportingDay)
893 -)))|(% colspan="2" %)time_period
894 -| |(% colspan="2" %)(((
729 +(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
730 +)))|(% colspan="1" style="width:311px" %)time_period
731 +|(% colspan="2" style="width:507px" %)(((
895 895  ReportingYear
896 -
897 897  (YYYY-A1 – 1 year period)
898 -)))|(% colspan="2" %)time_period
899 -| |(% colspan="2" %)(((
734 +)))|(% colspan="1" style="width:311px" %)time_period
735 +|(% colspan="2" style="width:507px" %)(((
900 900  ReportingSemester
901 -
902 902  (YYYY-Ss – 6 month period)
903 -)))|(% colspan="2" %)time_period
904 -| |(% colspan="2" %)(((
738 +)))|(% colspan="1" style="width:311px" %)time_period
739 +|(% colspan="2" style="width:507px" %)(((
905 905  ReportingTrimester
906 -
907 907  (YYYY-Tt – 4 month period)
908 -)))|(% colspan="2" %)time_period
909 -| |(% colspan="2" %)(((
742 +)))|(% colspan="1" style="width:311px" %)time_period
743 +|(% colspan="2" style="width:507px" %)(((
910 910  ReportingQuarter
911 -
912 912  (YYYY-Qq – 3 month period)
913 -)))|(% colspan="2" %)time_period
914 -| |(% colspan="2" %)(((
746 +)))|(% colspan="1" style="width:311px" %)time_period
747 +|(% colspan="2" style="width:507px" %)(((
915 915  ReportingMonth
916 -
917 917  (YYYY-Mmm – 1 month period)
918 -)))|(% colspan="2" %)time_period
919 -| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period
920 -| |(% colspan="2" %) |(% colspan="2" %)
921 -| |(% colspan="2" %) |(% colspan="2" %)
922 -|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) |
923 -|(% colspan="2" %)(((
750 +)))|(% colspan="1" style="width:311px" %)time_period
751 +|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period
752 +|(% colspan="1" style="width:507px" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" style="width:312px" %)
753 +|(% colspan="1" style="width:507px" %)(((
924 924  ReportingDay
925 -
926 926  (YYYY-Dddd – 1 day period)
927 -)))|(% colspan="2" %)time_period|
928 -|(% colspan="2" %)(((
756 +)))|(% colspan="2" style="width:312px" %)time_period
757 +|(% colspan="1" style="width:507px" %)(((
929 929  DateTime
930 -
931 931  (YYYY-MM-DDThh:mm:ss)
932 -)))|(% colspan="2" %)date|
933 -|(% colspan="2" %)(((
760 +)))|(% colspan="2" style="width:312px" %)date
761 +|(% colspan="1" style="width:507px" %)(((
934 934  TimeRange
935 -
936 936  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
937 -)))|(% colspan="2" %)time|
938 -|(% colspan="2" %)(((
764 +)))|(% colspan="2" style="width:312px" %)time
765 +|(% colspan="1" style="width:507px" %)(((
939 939  Month
940 -
941 941  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
942 -)))|(% colspan="2" %)string|
943 -|(% colspan="2" %)(((
768 +)))|(% colspan="2" style="width:312px" %)string
769 +|(% colspan="1" style="width:507px" %)(((
944 944  MonthDay
945 -
946 946  (~-~-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)
947 -)))|(% colspan="2" %)string|
948 -|(% colspan="2" %)(((
772 +)))|(% colspan="2" style="width:312px" %)string
773 +|(% colspan="1" style="width:507px" %)(((
949 949  Day
950 -
951 951  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
952 -)))|(% colspan="2" %)string|
953 -|(% colspan="2" %)(((
776 +)))|(% colspan="2" style="width:312px" %)string
777 +|(% colspan="1" style="width:507px" %)(((
954 954  Time
955 -
956 956  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
957 -)))|(% colspan="2" %)string|
958 -|(% colspan="2" %)(((
780 +)))|(% colspan="2" style="width:312px" %)string
781 +|(% colspan="1" style="width:507px" %)(((
959 959  Duration
960 -
961 961  (corresponds to XML Schema xs:duration datatype)
962 -)))|(% colspan="2" %)duration|
963 -|(% colspan="2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|
964 -|(% colspan="2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|
965 -|(% colspan="2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|
966 -|(% colspan="2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|
784 +)))|(% colspan="2" style="width:312px" %)duration
785 +|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable
786 +|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable
787 +|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
788 +|(% colspan="1" style="width:507px" %)DataSetReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable
967 967  
968 -==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
790 +(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %)
791 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
969 969  
970 970  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).
971 971  
... ... @@ -973,39 +973,32 @@
973 973  
974 974  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
975 975  
976 -|(((
977 -VTL basic
978 -
979 -scalar type
980 -)))|(((
981 -Default SDMX data type
982 -
983 -(BasicComponentDataType
984 -
985 -)
986 -)))|Default output format
987 -|String|String|Like XML (xs:string)
988 -|Number|Float|Like XML (xs:float)
989 -|Integer|Integer|Like XML (xs:int)
990 -|Date|DateTime|YYYY-MM-DDT00:00:00Z
991 -|Time|StandardTimePeriod|<date>/<date> (as defined above)
992 -|time_period|(((
799 +(% style="width:1073.29px" %)
800 +|(% style="width:207px" %)(((
801 +**VTL basic scalar type**
802 +)))|(% style="width:462px" %)(((
803 +**Default SDMX data type (BasicComponentDataType)**
804 +)))|(% style="width:402px" %)**Default output format**
805 +|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string)
806 +|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float)
807 +|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int)
808 +|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z
809 +|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above)
810 +|(% style="width:207px" %)time_period|(% style="width:462px" %)(((
993 993  ReportingTimePeriod
994 -
995 995  (StandardReportingPeriod)
996 -)))|(((
813 +)))|(% style="width:402px" %)(((
997 997  YYYY-Pppp
998 -
999 999  (according to SDMX )
1000 1000  )))
1001 -|Duration|Duration|(((
817 +|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)(((
1002 1002  Like XML (xs:duration)
1003 -
1004 1004  PnYnMnDTnHnMnS
1005 1005  )))
1006 -|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
821 +|(% style="width:207px" %)Boolean|(% style="width:462px" %)Boolean|(% style="width:402px" %)Like XML (xs:boolean) with the values "true" or "false"
1007 1007  
1008 -==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
823 +(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes-1" %)
824 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
1009 1009  
1010 1010  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).
1011 1011  
... ... @@ -1059,7 +1059,7 @@
1059 1059  |N|fixed number of digits used in the preceding textual representation of the month or the day
1060 1060  | |
1061 1061  
1062 -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" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.
878 +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}}.
1063 1063  
1064 1064  === 12.4.5 Null Values ===
1065 1065  
... ... @@ -1077,10 +1077,8 @@
1077 1077  
1078 1078  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).
1079 1079  
1080 -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
896 +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.
1081 1081  
1082 -TransformationScheme.
1083 -
1084 1084  In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
1085 1085  
1086 1086  {{putFootnotes/}}