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edited by Helena
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... ... @@ -18,8 +18,7 @@
18 18  
19 19  This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts.
20 20  
21 -== 12.2 References to SDMX artefacts from VTL statements ==
22 -
21 +== 12.2 References to SDMX artefacts from VTL statements ==
23 23  === 12.2.1 Introduction ===
24 24  
25 25  The VTL can manipulate SDMX artefacts (or objects) by referencing them through predefined conventional names (aliases).
... ... @@ -49,8 +49,10 @@
49 49  
50 50  The generic structure of the URN is the following:
51 51  
52 -SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id (maintainedobject-version).*container-object-id.object-id
51 +SDMXprefix.SDMX-IM-package-name.class-name=agency-id:maintainedobject-id
53 53  
53 +(maintainedobject-version).*container-object-id.object-id
54 +
54 54  The **SDMXprefix** is "urn:sdmx:org", always the same for all SDMX artefacts.
55 55  
56 56  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".
... ... @@ -71,19 +71,24 @@
71 71  
72 72  The maintainedobject-version is the version, according to the SDMX versioning rules, of the maintained object which the artefact belongs to (for example, possible versions might be 1.0, 2.3, 1.0.0, 2.1.0 or 3.1.2).
73 73  
74 -The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN.
75 +The container-object-id does not apply to the classes that can be referenced in VTL Transformations, therefore is not present in their URN
75 75  
76 76  The object-id is the name of the non-maintainable artefact (when the artefact is maintainable its name is already specified as the maintainedobject-id, see above), in particular it has to be specified:
77 77  
78 -* if the artefact is a Dimension, TimeDimension, Measure or DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components)
79 +* if the artefact is a Dimension, TimeDimension, Measure or
80 +
81 +DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components)
82 +
79 79  * if the artefact is a Concept (the object-id is the name of the Concept)
80 80  
81 81  For example, by using the URN, the VTL Transformation that sums two SDMX Dataflows DF1 and DF2 and assigns the result to a third persistent Dataflow DFR, assuming that DF1, DF2 and DFR are the maintainedobject-id of the three Dataflows, that their version is 1.0.0 and their Agency is AG, would be written as{{footnote}}Since these references to SDMX objects include non-permitted characters as per the VTL ID notation, they need to be included between single quotes, according to the VTL rules for irregular names.{{/footnote}}:
82 82  
83 -> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
84 -> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
85 -> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
87 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' <-
86 86  
89 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
90 +
91 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
92 +
87 87  === 12.2.3 Abbreviation of the URN ===
88 88  
89 89  The complete formulation of the URN described above is exhaustive but verbose, even for very simple statements. In order to reduce the verbosity through a simplified identifier and make the work of transformation definers easier, proper abbreviations of the URN are possible. Using this approach, the referenced artefacts remain intelligible in the VTL code by a human reader.
... ... @@ -92,13 +92,10 @@
92 92  
93 93  * 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.
94 94  * 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:
95 -** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute,
96 -** "conceptscheme" for the class Concept,
97 -** "codelist" for the class Codelist.
101 +** "datastructure" for the classes Dataflow, Dimension, TimeDimension, Measure, DataAttribute, o "conceptscheme" for the class Concept, o "codelist" for the class Codelist.
98 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){{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}}.
99 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{{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).
100 -* As for the maintainedobject-id, this is essential in some cases while in other cases it can be omitted:
101 -** if the referenced artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the dataflow-id and obviously cannot be omitted;
104 +* 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;
102 102  ** 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;
103 103  ** 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;
104 104  ** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted.
... ... @@ -110,47 +110,51 @@
110 110  
111 111  For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
112 112  
113 -> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
114 -> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
115 -> 'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
116 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0.0)' :=
116 116  
118 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0.0)' +
119 +
120 +'urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0.0)'
121 +
117 117  by omitting all the non-essential parts would become simply:
118 118  
119 -> DFR  : = DF1 + DF2
124 +DFR := DF1 + DF2
120 120  
121 121  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{{footnote}}Single quotes are needed because this reference is not a VTL regular name. 19 Single quotes are not needed in this case because CL_FREQ is a VTL regular name.{{/footnote}}:
122 122  
123 -> 'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
128 +'urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0.0)'
124 124  
125 125  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^^:
126 126  
127 -> CL_FREQ
132 +CL_FREQ
128 128  
129 129  As for the references to the components, it can be enough to specify the componentId, given that the dataStructure-Id can be omitted. An example of non-abbreviated reference, if the data structure is DST1 and the component is SECTOR, is the following:
130 130  
131 -> 'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).S ECTOR'
136 +'urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0.0).S
132 132  
138 +ECTOR'
139 +
133 133  The corresponding fully abbreviated reference, if made from a TransformationScheme belonging to AG, would become simply:
134 134  
135 -> SECTOR
142 +SECTOR
136 136  
137 137  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}}:
138 138  
139 -> 'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
146 +'DFR(1.0.0)' := 'DF1(1.0.0)' [rename SECTOR to SEC]
140 140  
141 141  In the references to the Concepts, which can exist for example in the definition of the VTL Rulesets, at least the conceptScheme-id and the concept-id must be specified.
142 142  
143 143  An example of non-abbreviated reference, if the conceptScheme-id is CS1 and the concept-id is SECTOR, is the following:
144 144  
145 -> 'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR'
152 +'urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0.0).SECTOR'
146 146  
147 147  The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
148 148  
149 -> CS1(1.0.0).SECTOR
156 +CS1(1.0.0).SECTOR
150 150  
151 151  The Codes and in general all the Values can be written without any other specification, for example, the transformation to check if the values of the measures of the Dataflow DF1 are between 0 and 25000 can be written like follows:
152 152  
153 -> 'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
160 +'DFR(1.0.0)' := between ( 'DF1(1.0.0)', 0, 25000 )
154 154  
155 155  The artefact (Component, Concept, Codelist …) which the Values are referred to can be deduced from the context in which the reference is made, taking also into account the VTL syntax. In the Transformation above, for example, the values 0 and 2500 are compared to the values of the measures of DF1(1.0.0).
156 156  
... ... @@ -173,7 +173,6 @@
173 173  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.
174 174  
175 175  == 12.3 Mapping between SDMX and VTL artefacts ==
176 -
177 177  === 12.3.1. When the mapping occurs ===
178 178  
179 179  The mapping methods between the VTL and SDMX object classes allow transforming a SDMX definition in a VTL one and vice-versa for the artefacts to be manipulated. It should be remembered that VTL programs (i.e. Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformations (nameable artefacts). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result: the input operands of the expression and the result can be SDMX artefacts. Every time a SDMX object is referenced in a VTL Transformation as an input operand, there is the need to generate a VTL definition of the object, so that the VTL operations can take place. This can be made starting from the SDMX definition and applying a SDMX-VTL mapping method in the direction from SDMX to VTL. The possible mapping methods from SDMX to VTL are described in the following paragraphs and are conceived to allow the automatic deduction of the VTL definition of the object from the knowledge of the SDMX definition.
... ... @@ -198,7 +198,7 @@
198 198  
199 199  The possible mapping options are described in more detail in the following sections.
200 200  
201 -=== 12.3.3 Mapping from SDMX to VTL data structures ===
207 +=== 12.3.2 Mapping from SDMX to VTL data structures ===
202 202  
203 203  ==== 12.3.3.1 Basic Mapping ====
204 204  
... ... @@ -206,23 +206,24 @@
206 206  
207 207  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:
208 208  
209 -(% style="width:468.294px" %)
210 -|(% style="width:196px" %)**SDMX**|(% style="width:269px" %)**VTL**
211 -|(% style="width:196px" %)Dimension|(% style="width:269px" %)(Simple) Identifier
212 -|(% style="width:196px" %)TimeDimension|(% style="width:269px" %)(Time) Identifier
213 -|(% style="width:196px" %)Measure|(% style="width:269px" %)Measure
214 -|(% style="width:196px" %)DataAttribute|(% style="width:269px" %)Attribute
215 +|**SDMX**|**VTL**
216 +|Dimension|(Simple) Identifier
217 +|TimeDimension|(Time) Identifier
218 +|Measure|Measure
219 +|DataAttribute|Attribute
215 215  
216 216  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).
217 217  
218 218  With the Basic mapping, one SDMX observation^^27^^ generates one VTL data point.
219 219  
220 -==== 12.3.3.2 Pivot Mapping ====
225 +**12.3.3.2 Pivot Mapping**
221 221  
222 222  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.
223 223  
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}}.
229 +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
225 225  
231 +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}}.
232 +
226 226  Among other things, the Pivot method provides also backward compatibility with the SDMX 2.1 data structures that contained a MeasureDimension.
227 227  
228 228  If applied to SDMX structures that do not contain any MeasureDimension, this method behaves like the Basic mapping (see the previous paragraph).
... ... @@ -235,19 +235,18 @@
235 235  * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure);
236 236  * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
237 237  ** 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;
238 -** 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).
239 -** 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.
245 +** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators). o Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship.
240 240  
241 241  The summary mapping table of the "pivot" mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
242 242  
243 -(% style="width:739.294px" %)
244 -|(% style="width:335px" %)**SDMX**|(% style="width:400px" %)**VTL**
245 -|(% style="width:335px" %)Dimension|(% style="width:400px" %)(Simple) Identifier
246 -|(% style="width:335px" %)TimeDimension|(% style="width:400px" %)(Time) Identifier
247 -|(% style="width:335px" %)MeasureDimension & one Measure|(% style="width:400px" %)One Measure for each Code of the SDMX MeasureDimension
248 -|(% style="width:335px" %)DataAttribute not depending on the MeasureDimension|(% style="width:400px" %)Attribute
249 -|(% style="width:335px" %)DataAttribute depending on the MeasureDimension|(% style="width:400px" %)(((
249 +|**SDMX**|**VTL**
250 +|Dimension|(Simple) Identifier
251 +|TimeDimension|(Time) Identifier
252 +|MeasureDimension & one Measure|One Measure for each Code of the SDMX MeasureDimension
253 +|DataAttribute not depending on the MeasureDimension|Attribute
254 +|DataAttribute depending on the MeasureDimension|(((
250 250  One Attribute for each Code of the
256 +
251 251  SDMX MeasureDimension
252 252  )))
253 253  
... ... @@ -256,21 +256,31 @@
256 256  At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension:
257 257  
258 258  * 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;
259 -* The values of the SDMX simple Dimensions, TimeDimension and DataAttributes not depending on the MeasureDimension (these components by definition have always the same values for all the observations of the set above) become the values of the corresponding VTL (simple) Identifiers, (time) Identifier and Attributes.
260 -* 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
265 +* 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)
266 +
267 +Identifiers, (time) Identifier and Attributes.
268 +
269 +* 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
270 +
271 +Cj
272 +
261 261  * 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
262 262  
263 -==== 12.3.3.3 From SDMX DataAttributes to VTL Measures ====
275 +**12.3.3.3 From SDMX DataAttributes to VTL Measures**
264 264  
265 -* In some cases, it may happen that the DataAttributes of the SDMX DataStructure need to be managed as Measures in VTL. Therefore, a variant of both the methods above consists in transforming all the SDMX DataAttributes in VTL Measures. When DataAttributes are converted to Measures, the two methods above are called Basic_A2M and Pivot_A2M (the suffix "A2M" stands for Attributes to Measures). Obviously, the resulting VTL data structure is, in general, multi-measure and does not contain Attributes.
277 +* 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
266 266  
279 +Attributes.
280 +
267 267  The Basic_A2M and Pivot_A2M behaves respectively like the Basic and Pivot methods, except that the final VTL components, which according to the Basic and Pivot methods would have had the role of Attribute, assume instead the role of Measure.
268 268  
269 269  Proper VTL features allow changing the role of specific attributes even after the SDMX to VTL mapping: they can be useful when only some of the DataAttributes need to be managed as VTL Measures.
270 270  
271 -=== 12.3.4 Mapping from VTL to SDMX data structures ===
285 +1.
286 +11.
287 +111. Mapping from VTL to SDMX data structures
272 272  
273 -==== 12.3.4.1 Basic Mapping ====
289 +**12.3.4.1 Basic Mapping**
274 274  
275 275  The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
276 276  
... ... @@ -280,12 +280,11 @@
280 280  
281 281  Mapping table:
282 282  
283 -(% style="width:470.294px" %)
284 -|(% style="width:262px" %)**VTL**|(% style="width:205px" %)**SDMX**
285 -|(% style="width:262px" %)(Simple) Identifier|(% style="width:205px" %)Dimension
286 -|(% style="width:262px" %)(Time) Identifier|(% style="width:205px" %)TimeDimension
287 -|(% style="width:262px" %)Measure|(% style="width:205px" %)Measure
288 -|(% style="width:262px" %)Attribute|(% style="width:205px" %)DataAttribute
299 +|**VTL**|**SDMX**
300 +|(Simple) Identifier|Dimension
301 +|(Time) Identifier|TimeDimension
302 +|Measure|Measure
303 +|Attribute|DataAttribute
289 289  
290 290  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.
291 291  
... ... @@ -295,7 +295,7 @@
295 295  
296 296  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.
297 297  
298 -==== 12.3.4.2 Unpivot Mapping ====
313 +**12.3.4.2 Unpivot Mapping**
299 299  
300 300  An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
301 301  
... ... @@ -313,12 +313,11 @@
313 313  
314 314  The summary mapping table of the **unpivot** mapping method is the following:
315 315  
316 -(% style="width:638.294px" %)
317 -|(% style="width:200px" %)**VTL**|(% style="width:435px" %)**SDMX**
318 -|(% style="width:200px" %)(Simple) Identifier|(% style="width:435px" %)Dimension
319 -|(% style="width:200px" %)(Time) Identifier|(% style="width:435px" %)TimeDimension
320 -|(% style="width:200px" %)All Measure Components|(% style="width:435px" %)MeasureDimension (having one Code for each VTL measure component) & one Measure
321 -|(% style="width:200px" %)Attribute|(% style="width:435px" %)DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
331 +|**VTL**|**SDMX**
332 +|(Simple) Identifier|Dimension
333 +|(Time) Identifier|TimeDimension
334 +|All Measure Components|MeasureDimension (having one Code for each VTL measure component) & one Measure
335 +|Attribute|DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
322 322  
323 323  At observation / data point level:
324 324  
... ... @@ -332,7 +332,7 @@
332 332  
333 333  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.
334 334  
335 -==== 12.3.4.3 From VTL Measures to SDMX Data Attributes ====
349 +**12.3.4.3 From VTL Measures to SDMX Data Attributes**
336 336  
337 337  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”).
338 338  
... ... @@ -340,17 +340,18 @@
340 340  
341 341  The mapping table is the following:
342 342  
343 -(% style="width:467.294px" %)
344 -|(% style="width:214px" %)VTL|(% style="width:250px" %)SDMX
345 -|(% style="width:214px" %)(Simple) Identifier|(% style="width:250px" %)Dimension
346 -|(% style="width:214px" %)(Time) Identifier|(% style="width:250px" %)TimeDimension
347 -|(% style="width:214px" %)Some Measures|(% style="width:250px" %)Measure
348 -|(% style="width:214px" %)Other Measures|(% style="width:250px" %)DataAttribute
349 -|(% style="width:214px" %)Attribute|(% style="width:250px" %)DataAttribute
357 +|VTL|SDMX
358 +|(Simple) Identifier|Dimension
359 +|(Time) Identifier|TimeDimension
360 +|Some Measures|Measure
361 +|Other Measures|DataAttribute
362 +|Attribute|DataAttribute
350 350  
351 351  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.
352 352  
353 -=== 12.3.5 Declaration of the mapping methods between data structures ===
366 +1.
367 +11.
368 +111. Declaration of the mapping methods between data structures
354 354  
355 355  In order to define and understand properly VTL Transformations, the applied mapping methods must be specified in the SDMX structural metadata. If the default mapping method (Basic) is applied, no specification is needed.
356 356  
... ... @@ -360,10 +360,14 @@
360 360  
361 361  The VtlMappingScheme is a container for zero or more VtlDataflowMapping (it may contain also mappings towards artefacts other than dataflows).
362 362  
363 -=== 12.3.6 Mapping dataflow subsets to distinct VTL Data Sets ===
378 +1.
379 +11.
380 +111. Mapping dataflow subsets to distinct VTL Data Sets
364 364  
365 -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).
382 +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
366 366  
384 +(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).
385 +
367 367  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}}
368 368  
369 369  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}}
... ... @@ -384,11 +384,11 @@
384 384  
385 385  Therefore, the generic name of this kind of VTL datasets would be:
386 386  
387 -> 'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
406 +'DF(1.0.0)/INDICATORvalue.COUNTRYvalue'
388 388  
389 389  Where DF(1.0.0) is the Dataflow and //INDICATORvalue// and //COUNTRYvalue //are placeholders for one value of the INDICATOR and COUNTRY dimensions. Instead the specific name of one of these VTL datasets would be:
390 390  
391 -> ‘DF(1.0.0)/POPULATION.USA’
410 +‘DF(1.0.0)/POPULATION.USA’
392 392  
393 393  In particular, this is the VTL dataset that contains all the observations of the Dataflow DF(1.0.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA.
394 394  
... ... @@ -402,22 +402,26 @@
402 402  
403 403  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.
404 404  
405 -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 …).
424 +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.
406 406  
426 +basic, pivot …).
427 +
407 407  In the example above, for all the datasets of the kind
408 408  
409 -> ‘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.
430 +‘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.
410 410  
411 411  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:
412 412  
413 -> ‘DF1(1.0.0)/POPULATION.USA’ :=
414 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
415 ->
416 -> ‘DF1(1.0.0)/POPULATION.CANADA’ :=
417 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
418 ->
419 -> … … …
434 +‘DF1(1.0.0)/POPULATION.USA’ :=
420 420  
436 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
437 +
438 +‘DF1(1.0.0)/POPULATION.CANADA’ :=
439 +
440 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
441 +
442 +… … …
443 +
421 421  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}}
422 422  
423 423  In the direction from SDMX to VTL it is allowed to omit the value of one or more DimensionComponents on which the mapping is based, but maintaining all the separating dots (therefore it may happen to find two or more consecutive dots and dots in the beginning or in the end). The absence of value means that for the corresponding Dimension all the values are kept and the Dimension is not dropped.
... ... @@ -426,9 +426,10 @@
426 426  
427 427  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
428 428  
429 -> ‘DF1(1.0.0)/POPULATION.’ :=
430 -> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
452 +‘DF1(1.0.0)/POPULATION.’ :=
431 431  
454 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
455 +
432 432  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
433 433  
434 434  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
... ... @@ -446,40 +446,59 @@
446 446  
447 447  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}}
448 448  
449 -> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
473 +‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
450 450  
451 451  Some examples follow, for some specific values of INDICATOR and COUNTRY:
452 452  
453 -> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
454 -> … … …
455 -> ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
456 -> ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
457 -> … … …
477 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
458 458  
479 +… … …
480 +
481 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
482 +
483 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
484 +
485 +… … …
486 +
459 459  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:
460 460  
461 -> VTL dataset  INDICATOR value COUNTRY value
462 ->
463 -> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
464 -> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
465 ->
466 -> ‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
467 -> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
468 -> … … …
489 +VTL dataset   INDICATOR value COUNTRY value
469 469  
491 +
492 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
493 +
494 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
495 +
496 +‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
497 +
498 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
499 +
500 +… … …
501 +
470 470  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:
471 471  
472 -> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
473 -> DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
474 -> DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’  [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
475 -> DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
476 -> DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
477 -> DF2bis_GDPPERCAPITA_CANADA’,
478 -> … ,
479 -> DF2bis_POPGROWTH_USA’,
480 -> DF2bis_POPGROWTH_CANADA’
481 -> …);
504 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
482 482  
506 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
507 +
508 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
509 +
510 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
511 +
512 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
513 +
514 +DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
515 +
516 +DF2bis_GDPPERCAPITA_CANADA’,
517 +
518 +… ,
519 +
520 +DF2bis_POPGROWTH_USA’,
521 +
522 +DF2bis_POPGROWTH_CANADA’
523 +
524 +…);
525 +
483 483  In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
484 484  
485 485  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}}{{footnote}}Through SDMX Constraints, it is possible to specify the values that a Component of a Dataflow can assume.{{/footnote}}
... ... @@ -486,30 +486,33 @@
486 486  
487 487  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).
488 488  
489 -=== 12.3.7 Mapping variables and value domains between VTL and SDMX ===
532 +1.
533 +11.
534 +111. Mapping variables and value domains between VTL and SDMX
490 490  
491 491  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
492 492  
493 -(% style="width:706.294px" %)
494 -|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX
495 -|(% style="width:257px" %)**Data Set Component**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
496 -|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation
497 -|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)(((
538 +|VTL|SDMX
539 +|**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^^
540 +|**Represented Variable**|**Concept** with a definite Representation
541 +|**Value Domain**|(((
498 498  **Representation** (see the Structure
543 +
499 499  Pattern in the Base Package)
500 500  )))
501 -|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
502 -|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
503 -|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
546 +|**Enumerated Value Domain / Code List**|**Codelist**
547 +|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
548 +|**Described Value Domain**|(((
504 504  non-enumerated** Representation**
550 +
505 505  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
506 506  )))
507 -|(% style="width:257px" %)**Value**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
508 -|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)
509 -|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
510 -|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
511 -|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
512 -|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX
553 +|**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
554 +| |to a valid **value **(for non-enumerated** **Representations)
555 +|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
556 +|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
557 +|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
558 +|**Set list**|This abstraction does not exist in SDMX
513 513  
514 514  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).
515 515  
... ... @@ -517,10 +517,8 @@
517 517  
518 518  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
519 519  
520 -> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
566 +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.
521 521  
522 -if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
523 -
524 524  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
525 525  
526 526  Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
... ... @@ -527,29 +527,28 @@
527 527  
528 528  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.
529 529  
530 -== 12.4 Mapping between SDMX and VTL Data Types ==
574 +1.
575 +11. Mapping between SDMX and VTL Data Types
576 +111. VTL Data types
531 531  
532 -=== 12.4.1 VTL Data types ===
533 -
534 534  According to the VTL User Guide the possible operations in VTL depend on the data types of the artefacts. For example, numbers can be multiplied but text strings cannot. In the VTL Transformations, the compliance between the operators and the data types of their operands is statically checked, i.e., violations result in compile-time errors.
535 535  
536 536  The VTL data types are sub-divided in scalar types (like integers, strings, etc.), which are the types of the scalar values, and compound types (like Data Sets, Components, Rulesets, etc.), which are the types of the compound structures. See below the diagram of the VTL data types, taken from the VTL User Manual:
537 537  
582 +[[image:1750067055028-964.png]]
538 538  
539 -[[image:1750070288958-132.png]]
584 +==== Figure 22 – VTL Data Types ====
540 540  
541 -**Figure 22 – VTL Data Types**
542 -
543 543  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.
544 544  
545 545  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):
546 546  
547 -[[image:1750070310572-584.png]]
590 +==== Figure 23 – VTL Basic Scalar Types ====
548 548  
549 -**Figure 23 – VTL Basic Scalar Types**
592 +1.
593 +11.
594 +111. VTL basic scalar types and SDMX data types
550 550  
551 -=== 12.4.2 VTL basic scalar types and SDMX data types ===
552 -
553 553  The VTL assumes that a basic scalar type has a unique internal representation and can have more external representations.
554 554  
555 555  The internal representation is the format used within a VTL system to represent (and process) all the scalar values of a certain type. In principle, this format is hidden and not necessarily known by users. The external representations are instead the external formats of the values of a certain basic scalar type, i.e. the formats known by the users. For example, the internal representation of the dates can be an integer counting the days since a predefined date (e.g. from 01/01/4713 BC up to 31/12/5874897 AD like in Postgres) while two possible external representations are the formats YYYY-MMGG and MM-GG-YYYY (e.g. respectively 2010-12-31 and 12-31-2010).
... ... @@ -566,256 +566,309 @@
566 566  
567 567  The opposite conversion, i.e. from VTL to SDMX, happens when a VTL result, i.e. a VTL Data Set output of a Transformation, must become a SDMX artefact (or part of it). The values of the VTL result must be converted into the desired (SDMX) external representations (data types) of the SDMX artefact.
568 568  
569 -=== 12.4.3 Mapping SDMX data types to VTL basic scalar types ===
612 +1.
613 +11.
614 +111. Mapping SDMX data types to VTL basic scalar types
570 570  
571 571  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
572 572  
573 -(% style="width:583.294px" %)
574 -|(% style="width:360px" %)SDMX data type (BasicComponentDataType)|(% style="width:221px" %)Default VTL basic scalar type
575 -|(% style="width:360px" %)(((
618 +|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type
619 +|(((
576 576  String
621 +
577 577  (string allowing any character)
578 -)))|(% style="width:221px" %)string
579 -|(% style="width:360px" %)(((
580 -Alpha
623 +)))|string
624 +|(((
625 +Alpha 
626 +
581 581  (string which only allows A-z)
582 -)))|(% style="width:221px" %)string
583 -|(% style="width:360px" %)(((
628 +)))|string
629 +|(((
584 584  AlphaNumeric
631 +
585 585  (string which only allows A-z and 0-9)
586 -)))|(% style="width:221px" %)string
587 -|(% style="width:360px" %)(((
633 +)))|string
634 +|(((
588 588  Numeric
636 +
589 589  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
590 -)))|(% style="width:221px" %)string
591 -|(% style="width:360px" %)(((
638 +)))|string
639 +|(((
592 592  BigInteger
641 +
593 593  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
594 -)))|(% style="width:221px" %)integer
595 -|(% style="width:360px" %)(((
643 +)))|integer
644 +|(((
596 596  Integer
646 +
597 597  (corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647
648 +
598 598  (inclusive))
599 -)))|(% style="width:221px" %)integer
600 -|(% style="width:360px" %)(((
650 +)))|integer
651 +|(((
601 601  Long
653 +
602 602  (corresponds to XML Schema xs:long datatype; between -9223372036854775808 and
655 +
603 603  +9223372036854775807 (inclusive))
604 -)))|(% style="width:221px" %)integer
605 -|(% style="width:360px" %)(((
657 +)))|integer
658 +|(((
606 606  Short
660 +
607 607  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
608 -)))|(% style="width:221px" %)integer
609 -|(% style="width:360px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:221px" %)number
610 -|(% style="width:360px" %)(((
662 +)))|integer
663 +|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number
664 +|(((
611 611  Float
666 +
612 612  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
613 -)))|(% style="width:221px" %)number
614 -|(% style="width:360px" %)(((
668 +)))|number
669 +|(((
615 615  Double
671 +
616 616  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
617 -)))|(% style="width:221px" %)number
618 -|(% style="width:360px" %)(((
673 +)))|number
674 +|(((
619 619  Boolean
676 +
620 620  (corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of
678 +
621 621  binary-valued logic: {true, false})
622 -)))|(% style="width:221px" %)boolean
623 -|(% style="width:360px" %)(((
680 +)))|boolean
681 +|(((
624 624  URI
683 +
625 625  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
626 -)))|(% style="width:221px" %)string
627 -|(% style="width:360px" %)(((
685 +)))|string
686 +|(((
628 628  Count
688 +
629 629  (an integer following a sequential pattern, increasing by 1 for each occurrence)
630 -)))|(% style="width:221px" %)integer
631 -|(% style="width:360px" %)(((
690 +)))|integer
691 +|(((
632 632  InclusiveValueRange
693 +
633 633  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
634 -)))|(% style="width:221px" %)number
635 -|(% style="width:360px" %)(((
695 +)))|number
696 +|(((
636 636  ExclusiveValueRange
698 +
637 637  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
638 -)))|(% style="width:221px" %)number
639 -|(% style="width:360px" %)(((
700 +)))|number
701 +|(((
640 640  Incremental
703 +
641 641  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
642 -)))|(% style="width:221px" %)number
643 -|(% style="width:360px" %)(((
705 +)))|number
706 +|(((
644 644  ObservationalTimePeriod
708 +
645 645  (superset of StandardTimePeriod and TimeRange)
646 -)))|(% style="width:221px" %)time
647 -|(% style="width:360px" %)(((
710 +)))|time
711 +|(((
648 648  StandardTimePeriod
713 +
649 649  (superset of BasicTimePeriod and ReportingTimePeriod)
650 -)))|(% style="width:221px" %)time
651 -|(% style="width:360px" %)(((
715 +)))|time
716 +|(((
652 652  BasicTimePeriod
718 +
653 653  (superset of GregorianTimePeriod and DateTime)
654 -)))|(% style="width:221px" %)date
655 -|(% style="width:360px" %)(((
720 +)))|date
721 +|(((
656 656  GregorianTimePeriod
723 +
657 657  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
658 -)))|(% style="width:221px" %)date
659 -|(% style="width:360px" %)GregorianYear (YYYY)|(% style="width:221px" %)date
660 -|(% style="width:360px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% style="width:221px" %)date
661 -|(% style="width:360px" %)GregorianDay (YYYY-MM-DD)|(% style="width:221px" %)date
662 -|(% style="width:360px" %)(((
725 +)))|date
726 +|GregorianYear (YYYY)|date
727 +|GregorianYearMonth / GregorianMonth (YYYY-MM)|date
728 +|GregorianDay (YYYY-MM-DD)|date
729 +|(((
663 663  ReportingTimePeriod
731 +
664 664  (superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
665 -)))|(% style="width:221px" %)time_period
666 -|(% style="width:360px" %)(((
733 +)))|time_period
734 +|(((
667 667  ReportingYear
736 +
668 668  (YYYY-A1 – 1 year period)
669 -)))|(% style="width:221px" %)time_period
670 -|(% style="width:360px" %)(((
738 +)))|time_period
739 +|(((
671 671  ReportingSemester
741 +
672 672  (YYYY-Ss – 6 month period)
673 -)))|(% style="width:221px" %)time_period
674 -|(% style="width:360px" %)(((
743 +)))|time_period
744 +|(((
675 675  ReportingTrimester
746 +
676 676  (YYYY-Tt – 4 month period)
677 -)))|(% style="width:221px" %)time_period
678 -|(% style="width:360px" %)(((
748 +)))|time_period
749 +|(((
679 679  ReportingQuarter
751 +
680 680  (YYYY-Qq – 3 month period)
681 -)))|(% style="width:221px" %)time_period
682 -|(% style="width:360px" %)(((
753 +)))|time_period
754 +|(((
683 683  ReportingMonth
756 +
684 684  (YYYY-Mmm – 1 month period)
685 -)))|(% style="width:221px" %)time_period
686 -|(% style="width:360px" %)ReportingWeek|(% style="width:221px" %)time_period
687 -|(% style="width:360px" %) (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% style="width:221px" %)
688 -|(% style="width:360px" %)(((
758 +)))|time_period
759 +|ReportingWeek|time_period
760 +| (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|
761 +|(((
689 689  ReportingDay
763 +
690 690  (YYYY-Dddd – 1 day period)
691 -)))|(% style="width:221px" %)time_period
692 -|(% style="width:360px" %)(((
765 +)))|time_period
766 +|(((
693 693  DateTime
768 +
694 694  (YYYY-MM-DDThh:mm:ss)
695 -)))|(% style="width:221px" %)date
696 -|(% style="width:360px" %)(((
770 +)))|date
771 +|(((
697 697  TimeRange
773 +
698 698  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
699 -)))|(% style="width:221px" %)time
700 -|(% style="width:360px" %)(((
775 +)))|time
776 +|(((
701 701  Month
778 +
702 702  (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
703 -)))|(% style="width:221px" %)string
704 -|(% style="width:360px" %)(((
780 +)))|string
781 +|(((
705 705  MonthDay
783 +
706 706  (~-~-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)
707 -)))|(% style="width:221px" %)string
708 -|(% style="width:360px" %)(((
785 +)))|string
786 +|(((
709 709  Day
788 +
710 710  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
711 -)))|(% style="width:221px" %)string
712 -|(% style="width:360px" %)(((
790 +)))|string
791 +|(((
713 713  Time
793 +
714 714  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
715 -)))|(% style="width:221px" %)string
716 -|(% style="width:360px" %)(((
795 +)))|string
796 +|(((
717 717  Duration
798 +
718 718  (corresponds to XML Schema xs:duration datatype)
719 -)))|(% style="width:221px" %)duration
720 -|(% style="width:360px" %)XHTML|(% style="width:221px" %)Metadata type – not applicable
721 -|(% style="width:360px" %)KeyValues|(% style="width:221px" %)Metadata type – not applicable
722 -|(% style="width:360px" %)IdentifiableReference|(% style="width:221px" %)Metadata type – not applicable
723 -|(% style="width:360px" %)DataSetReference|(% style="width:221px" %)Metadata type – not applicable
800 +)))|duration
801 +|XHTML|Metadata type – not applicable
802 +|KeyValues|Metadata type – not applicable
803 +|IdentifiableReference|Metadata type – not applicable
804 +|DataSetReference|Metadata type – not applicable
724 724  
725 -**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
806 +додол
726 726  
808 +==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
809 +
727 727  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).
728 728  
729 -=== 12.4.4 Mapping VTL basic scalar types to SDMX data types ===
812 +1.
813 +11.
814 +111. Mapping VTL basic scalar types to SDMX data types
730 730  
731 731  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
732 732  
733 -(% style="width:748.294px" %)
734 -|(% style="width:164px" %)(((
735 -VTL basic scalar type
736 -)))|(% style="width:304px" %)(((
818 +|(((
819 +VTL basic
820 +
821 +scalar type
822 +)))|(((
737 737  Default SDMX data type
738 -(BasicComponentDataType)
739 -)))|(% style="width:277px" %)Default output format
740 -|(% style="width:164px" %)String|(% style="width:304px" %)String|(% style="width:277px" %)Like XML (xs:string)
741 -|(% style="width:164px" %)Number|(% style="width:304px" %)Float|(% style="width:277px" %)Like XML (xs:float)
742 -|(% style="width:164px" %)Integer|(% style="width:304px" %)Integer|(% style="width:277px" %)Like XML (xs:int)
743 -|(% style="width:164px" %)Date|(% style="width:304px" %)DateTime|(% style="width:277px" %)YYYY-MM-DDT00:00:00Z
744 -|(% style="width:164px" %)Time|(% style="width:304px" %)StandardTimePeriod|(% style="width:277px" %)<date>/<date> (as defined above)
745 -|(% style="width:164px" %)time_period|(% style="width:304px" %)(((
824 +
825 +(BasicComponentDataType
826 +
827 +)
828 +)))|Default output format
829 +|String|String|Like XML (xs:string)
830 +|Number|Float|Like XML (xs:float)
831 +|Integer|Integer|Like XML (xs:int)
832 +|Date|DateTime|YYYY-MM-DDT00:00:00Z
833 +|Time|StandardTimePeriod|<date>/<date> (as defined above)
834 +|time_period|(((
746 746  ReportingTimePeriod
836 +
747 747  (StandardReportingPeriod)
748 -)))|(% style="width:277px" %)(((
838 +)))|(((
749 749   YYYY-Pppp
840 +
750 750  (according to SDMX )
751 751  )))
752 -|(% style="width:164px" %)Duration|(% style="width:304px" %)Duration|(% style="width:277px" %)Like XML (xs:duration) PnYnMnDTnHnMnS
753 -|(% style="width:164px" %)Boolean|(% style="width:304px" %)Boolean|(% style="width:277px" %)Like XML (xs:boolean) with the values "true" or "false"
843 +|Duration|Duration|Like XML (xs:duration) PnYnMnDTnHnMnS
844 +|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false"
754 754  
755 -**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
846 +==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ====
756 756  
757 -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).
848 +In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section
758 758  
850 +Transformations and Expressions of the SDMX information model).
851 +
759 759  The custom output formats can be specified by means of the VTL formatting mask described in the section "Type Conversion and Formatting Mask" of the VTL Reference Manual. Such a section describes the masks for the VTL basic scalar types "number", "integer", "date", "time", "time_period" and "duration" and gives examples. As for the types "string" and "boolean" the VTL conventions are extended with some other special characters as described in the following table.
760 760  
761 -(% style="width:717.294px" %)
762 -|(% colspan="2" style="width:714px" %)VTL special characters for the formatting masks
763 -|(% colspan="2" style="width:714px" %)
764 -|(% colspan="2" style="width:714px" %)Number
765 -|(% style="width:122px" %)D|(% style="width:591px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
766 -|(% style="width:122px" %)E|(% style="width:591px" %)one numeric digit (for the exponent of the scientific notation)
767 -|(% style="width:122px" %). (dot)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
768 -|(% style="width:122px" %), (comma)|(% style="width:591px" %)possible separator between the integer and the decimal parts.
769 -|(% style="width:122px" %) |(% style="width:591px" %)
770 -|(% colspan="2" style="width:714px" %)Time and duration
771 -|(% style="width:122px" %)C|(% style="width:591px" %)century
772 -|(% style="width:122px" %)Y|(% style="width:591px" %)year
773 -|(% style="width:122px" %)S|(% style="width:591px" %)semester
774 -|(% style="width:122px" %)Q|(% style="width:591px" %)quarter
775 -|(% style="width:122px" %)M|(% style="width:591px" %)month
776 -|(% style="width:122px" %)W|(% style="width:591px" %)week
777 -|(% style="width:122px" %)D|(% style="width:591px" %)day
778 -|(% style="width:122px" %)h|(% style="width:591px" %)hour digit (by default on 24 hours)
779 -|(% style="width:122px" %)M|(% style="width:591px" %)minute
780 -|(% style="width:122px" %)S|(% style="width:591px" %)second
781 -|(% style="width:122px" %)D|(% style="width:591px" %)decimal of second
782 -|(% style="width:122px" %)P|(% style="width:591px" %)period indicator (representation in one digit for the duration)
783 -|(% style="width:122px" %)P|(% style="width:591px" %)number of the periods specified in the period indicator
784 -|(% style="width:122px" %)AM/PM|(% style="width:591px" %)indicator of AM / PM (e.g. am/pm for "am" or "pm")
785 -|(% style="width:122px" %)MONTH|(% style="width:591px" %)uppercase textual representation of the month (e.g., JANUARY for January)
786 -|(% style="width:122px" %)DAY|(% style="width:591px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
787 -|(% style="width:122px" %)Month|(% style="width:591px" %)lowercase textual representation of the month (e.g., january)
788 -|(% style="width:122px" %)Day|(% style="width:591px" %)lowercase textual representation of the month (e.g., monday)
789 -|(% style="width:122px" %)Month|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
790 -|(% style="width:122px" %)Day|(% style="width:591px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
791 -|(% style="width:122px" %) |(% style="width:591px" %)
792 -|(% colspan="2" style="width:714px" %)String
793 -|(% style="width:122px" %)X|(% style="width:591px" %)any string character
794 -|(% style="width:122px" %)Z|(% style="width:591px" %)any string character from "A" to "z"
795 -|(% style="width:122px" %)9|(% style="width:591px" %)any string character from "0" to "9"
796 -|(% style="width:122px" %) |(% style="width:591px" %)
797 -|(% colspan="2" style="width:714px" %)Boolean
798 -|(% style="width:122px" %)B|(% style="width:591px" %)Boolean using "true" for True and "false" for False
799 -|(% style="width:122px" %)1|(% style="width:591px" %)Boolean using "1" for True and "0" for False
800 -|(% style="width:122px" %)0|(% style="width:591px" %)Boolean using "0" for True and "1" for False
801 -|(% style="width:122px" %) |(% style="width:591px" %)
802 -|(% colspan="2" style="width:714px" %)Other qualifiers
803 -|(% style="width:122px" %)*|(% style="width:591px" %)an arbitrary number of digits (of the preceding type)
804 -|(% style="width:122px" %)+|(% style="width:591px" %)at least one digit (of the preceding type)
805 -|(% style="width:122px" %)( )|(% style="width:591px" %)optional digits (specified within the brackets)
806 -|(% style="width:122px" %)\|(% style="width:591px" %)prefix for the special characters that must appear in the mask
807 -|(% style="width:122px" %)N|(% style="width:591px" %)fixed number of digits used in the preceding textual representation of the month or the day
808 -|(% style="width:122px" %) |(% style="width:591px" %)
854 +|(% colspan="2" %)VTL special characters for the formatting masks
855 +|(% colspan="2" %)
856 +|(% colspan="2" %)Number
857 +|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
858 +|E|one numeric digit (for the exponent of the scientific notation)
859 +|. (dot)|possible separator between the integer and the decimal parts.
860 +|, (comma)|possible separator between the integer and the decimal parts.
861 +| |
862 +|(% colspan="2" %)Time and duration
863 +|C|century
864 +|Y|year
865 +|S|semester
866 +|Q|quarter
867 +|M|month
868 +|W|week
869 +|D|day
870 +|h|hour digit (by default on 24 hours)
871 +|M|minute
872 +|S|second
873 +|D|decimal of second
874 +|P|period indicator (representation in one digit for the duration)
875 +|P|number of the periods specified in the period indicator
876 +|AM/PM|indicator of AM / PM (e.g. am/pm for "am" or "pm")
877 +|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
878 +|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
879 +|Month|lowercase textual representation of the month (e.g., january)
880 +|Day|lowercase textual representation of the month (e.g., monday)
881 +|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
882 +|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
883 +| |
884 +|(% colspan="2" %)String
885 +|X|any string character
886 +|Z|any string character from "A" to "z"
887 +|9|any string character from "0" to "9"
888 +| |
889 +|(% colspan="2" %)Boolean
890 +|B|Boolean using "true" for True and "false" for False
891 +|1|Boolean using "1" for True and "0" for False
892 +|0|Boolean using "0" for True and "1" for False
893 +| |
894 +|(% colspan="2" %)Other qualifiers
895 +|*|an arbitrary number of digits (of the preceding type)
896 +|+|at least one digit (of the preceding type)
897 +|( )|optional digits (specified within the brackets)
898 +|\|prefix for the special characters that must appear in the mask
899 +|N|fixed number of digits used in the preceding textual representation of the month or the day
900 +| |
809 809  
810 810  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}}.
811 811  
812 -=== 12.4.3 Null Values ===
904 +1.
905 +11.
906 +111. Null Values
813 813  
814 814  In the conversions from SDMX to VTL it is assumed by default that a missing value in SDMX becomes a NULL in VTL. After the conversion, the NULLs can be manipulated through the proper VTL operators.
815 815  
816 816  On the other side, the VTL programs can produce in output NULL values for Measures and Attributes (Null values are not allowed in the Identifiers). In the conversion from VTL to SDMX, it is assumed that a NULL in VTL becomes a missing value in SDMX. In the conversion from VTL to SDMX, the default assumption can be overridden, separately for each VTL basic scalar type, by specifying which the value that represents the NULL in SDMX is. This can be specified in the attribute "nullValue" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model). A CustomType belongs to a CustomTypeScheme, which can be referenced by one or more TransformationScheme (i.e. VTL programs). The overriding assumption is applied for all the SDMX Dataflows calculated in the TransformationScheme.
817 817  
818 -=== 12.4.5 Format of the literals used in VTL Transformations ===
912 +1.
913 +11.
914 +111. Format of the literals used in VTL Transformations
819 819  
820 820  The VTL programs can contain literals, i.e. specific values of certain data types written directly in the VTL definitions or expressions. The VTL does not prescribe a specific format for the literals and leave the specific VTL systems and the definers of VTL Transformations free of using their preferred formats.
821 821  
... ... @@ -829,6 +829,7 @@
829 829  
830 830  In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
831 831  
928 +
832 832  ----
833 833  
834 834  {{putFootnotes/}}
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