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1 -{{box title="**Contents**"}}
2 -{{toc/}}
3 -{{/box}}
1 +Revision History
4 4  
5 -**Revision History**
6 -
7 7  |**Revision**|**Date**|**Contents**
8 8  | |April 2011|Initial release
9 9  |1.0|April 2013|Added section 9 - Transforming between versions of SDMX
... ... @@ -13,8 +13,10 @@
13 13  
14 14  == 1.1 Purpose ==
15 15  
16 -The intention of this document is to document certain aspects of SDMX that are important to understand and will aid implementation decisions. The explanations here supplement the information documented in the SDMX XML schema and the Information Model.
12 +The intention of this document is to document certain aspects of SDMX that are important to understand and will aid implementation decisions. The explanations here supplement the information documented in the SDMX XML schema and the
17 17  
14 +Information Model.
15 +
18 18  == 1.2 Structure ==
19 19  
20 20  This document is organized into the following major parts:
... ... @@ -39,7 +39,7 @@
39 39  
40 40  == 3.2 SDMX Information Model for Format Implementers ==
41 41  
42 -=== 3.2.1 Introduction ===
40 +=== 3.2.1 Introduction ===
43 43  
44 44  The purpose of this sub-section is to provide an introduction to the SDMX-IM relating to Data Structure Definitions and Data Sets for those whose primary interest is in the use of the XML or EDI formats.  For those wishing to have a deeper understanding of the Information Model, the full SDMX-IM document, and other sections in this guide provide a more in-depth view, along with UML diagrams and supporting explanation. For those who are unfamiliar with DSDs, an appendix to the SDMX-IM provides a tutorial which may serve as a useful introduction.
45 45  
... ... @@ -47,12 +47,16 @@
47 47  
48 48  The Data Structure Definition and Data Set parts of the information model are consistent with the GESMES/TS version 3.0 Data Model (called SDMX-EDI in the SDMX standard), with these exceptions:
49 49  
50 -* the “sibling group” construct has been generalized to permit any dimension or dimensions to be wildcarded, and not just frequency, as in GESMES/TS. It has been renamed a “group” to distinguish it from the “sibling group” where only frequency is wildcarded. The set of allowable partial “group” keys must be declared in the DSD, and attributes may be attached to any of these group keys;
51 -* furthermore, whilst the “group” has been retained for compatibility with version 2.0 and with SDMX-EDI, it has, at version 2.1, been replaced by the “Attribute Relationship” definition which is explained later
52 -* the section on data representation is now a convention, to support interoperability with EDIFACT-syntax implementations ( see section 3.3.2);
48 +the “sibling group” construct has been generalized to permit any dimension or dimensions to be wildcarded, and not just frequency, as in GESMES/TS. It has been renamed a “group” to distinguish it from the “sibling group” where only frequency is wildcarded. The set of allowable partial “group” keys must be declared in the DSD, and attributes may be attached to any of these group keys;
53 53  
54 -DSD-specific data formats are derived from the model, and some supporting features for declaring multiple measures have been added to the structural metadata descriptions Clearly, this is not a coincidence. The GESMES/TS Data Model provides the foundation for the EDIFACT messages in SDMX-EDI, and also is the starting point for the development of SDMX-ML.
50 +furthermore, whilst the “group” has been retained for compatibility with version 2.0 and with SDMX-EDI, it has, at version 2.1, been replaced by the “Attribute Relationship” definition which is explained later
55 55  
52 +the section on data representation is now a convention, to support interoperability with EDIFACT-syntax implementations ( see section 3.3.2);
53 +
54 +DSD-specific data formats are derived from the model, and some supporting features for declaring multiple measures have been added to the structural metadata descriptions
55 +
56 +Clearly, this is not a coincidence. The GESMES/TS Data Model provides the foundation for the EDIFACT messages in SDMX-EDI, and also is the starting point for the development of SDMX-ML.
57 +
56 56  Note that in the descriptions below, text in courier and italicised are the names used in the information model (e.g. //DataSet//).
57 57  
58 58  == 3.3 SDMX-ML and SDMX-EDI: Comparison of Expressive Capabilities and Function ==
... ... @@ -59,16 +59,22 @@
59 59  
60 60  SDMX offers several equivalent formats for describing data and structural metadata, optimized for use in different applications. Although all of these formats are derived directly from the SDM-IM, and are thus equivalent, the syntaxes used to express the model place some restrictions on their use. Also, different optimizations provide different capabilities. This section describes these differences, and provides some rules for applications which may need to support more than one SDMX format or syntax. This section is constrained to the Data Structure Definitionand the Date Set.
61 61  
62 -=== 3.3.1 Format Optimizations and Differences ===
64 +=== 3.3.1 Format Optimizations and Differences ===
63 63  
64 64  The following section provides a brief overview of the differences between the various SDMX formats.
65 65  
66 -Version 2.0 was characterised by 4 data messages, each with a distinct format: Generic, Compact, Cross-Sectional and Utility. Because of the design, data in some formats could not always be related to another format. In version 2.1, this issue has been addressed by merging some formats and eliminating others. As a result, in SDMX 2.1 there are just two types of data formats: //GenericData// and //StructureSpecificData// (i.e. specific to one Data Structure Definition).
68 +Version 2.0 was characterised by 4 data messages, each with a distinct format: Generic, Compact, Cross-Sectional and Utility. Because of the design, data in some formats could not always be related to another format. In version 2.1, this issue has been addressed by merging some formats and eliminating others. As a result, in
67 67  
70 +SDMX 2.1 there are just two types of data formats: //GenericData// and
71 +
72 +//StructureSpecificData// (i.e. specific to one Data Structure Definition).
73 +
68 68  Both of these formats are now flexible enough to allow for data to be oriented in series with any dimension used to disambiguate the observations (as opposed to only time or a cross sectional measure in version 2.0). The formats have also been expanded to allow for ungrouped observations.
69 69  
70 -To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages; //GenericTimeSeriesData// and //StructureSpecificTimeSeriesData//. It is important to note that these variations are built on the same root structure and can be processed in the same manner as the base format so that they do NOT introduce additional processing requirements.
76 +To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages;
71 71  
78 +//GenericTimeSeriesData// and //StructureSpecificTimeSeriesData//. It is important to note that these variations are built on the same root structure and can be processed in the same manner as the base format so that they do NOT introduce additional processing requirements.
79 +
72 72  === //Structure Definition// ===
73 73  
74 74  The SDMX-ML Structure Message supports the use of annotations to the structure, which is not supported by the SDMX-EDI syntax.
... ... @@ -77,8 +77,10 @@
77 77  
78 78  === //Validation// ===
79 79  
80 -SDMX-EDI – as is typical of EDIFACT syntax messages – leaves validation to dedicated applications (“validation” being the checking of syntax, data typing, and adherence of the data message to the structure as described in the structural definition.)
88 +SDMX-EDI – as is typical of EDIFACT syntax messages – leaves validation to dedicated applications (“validation” being the checking of syntax, data typing, and adherence of the data message to the structure as described in the structural
81 81  
90 +definition.)
91 +
82 82  The SDMX-ML Generic Data Message also leaves validation above the XML syntax level to the application.
83 83  
84 84  The SDMX-ML DSD-specific messages will allow validation of XML syntax and datatyping to be performed with a generic XML parser, and enforce agreement between the structural definition and the data to a moderate degree with the same tool.
... ... @@ -89,13 +89,17 @@
89 89  
90 90  === //Character Encodings// ===
91 91  
92 -All SDMX-ML messages use the UTF-8 encoding, while SDMX-EDI uses the ISO 8879-1 character encoding. There is a greater capacity with UTF-8 to express some character sets (see the “APPENDIX: MAP OF ISO 8859-1 (UNOC) CHARACTER SET (LATIN 1 OR “WESTERN”) in the document “SYNTAX AND DOCUMENTATION VERSION 2.0”.) Many transformation tools are available which allow XML instances with UTF-8 encodings to be expressed as ISO 8879-1-encoded characters, and to transform UTF-8 into ISO 8879-1. Such tools should be used when transforming SDMX-ML messages into SDMX-EDI messages and vice-versa.
102 +All SDMX-ML messages use the UTF-8 encoding, while SDMX-EDI uses the ISO 8879-1 character encoding. There is a greater capacity with UTF-8 to express some character sets (see the “APPENDIX: MAP OF ISO 8859-1 (UNOC) CHARACTER
93 93  
104 +SET (LATIN 1 OR “WESTERN”) in the document “SYNTAX AND
105 +
106 +DOCUMENTATION VERSION 2.0”.) Many transformation tools are available which allow XML instances with UTF-8 encodings to be expressed as ISO 8879-1-encoded characters, and to transform UTF-8 into ISO 8879-1. Such tools should be used when transforming SDMX-ML messages into SDMX-EDI messages and vice-versa.
107 +
94 94  === //Data Typing// ===
95 95  
96 96  The XML syntax and EDIFACT syntax have different data-typing mechanisms. The section below provides a set of conventions to be observed when support for messages in both syntaxes is required. For more information on the SDMX-ML representations of data, see below.
97 97  
98 -==== 3.3.2 Data Types ====
112 +==== 3.3.2 Data Types ====
99 99  
100 100  The XML syntax has a very different mechanism for data-typing than the EDIFACT syntax, and this difference may create some difficulties for applications which support both EDIFACT-based and XML-based SDMX data formats. This section provides a set of conventions for the expression in data in all formats, to allow for clean interoperability between them.
101 101  
... ... @@ -111,8 +111,7 @@
111 111  1*. Maximum 70 characters.
112 112  1*. From ISO 8859-1 character set (including accented characters)
113 113  1. **Descriptions **are:
114 -1*. Maximum 350 characters;
115 -1*. From ISO 8859-1 character set.
128 +1*. Maximum 350 characters;  From ISO 8859-1 character set.
116 116  1. **Code values** are:
117 117  1*. Maximum 18 characters;
118 118  1*. Any of A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore), / (solidus, slash), = (equal sign), - (hyphen);
... ... @@ -181,7 +181,7 @@
181 181  
182 182  The same code list can be used for several statistical concepts, within a data structure definition or across DSDs. Note that SDMX has recognised that these classifications are often quite large and the usage of codes in any one DSD is only a small extract of the full code list. In this version of the standard it is possible to exchange and disseminate a **partial code list** which is extracted from the full code list and which supports the dimension values valid for a particular DSD.
183 183  
184 -=== Data Structure Definition Structure ===
197 +=== Data Structure Definition Structure  ===
185 185  
186 186  The following items have to be specified by a structural definitions maintenance agency when defining a new data structure definition:
187 187  
... ... @@ -365,7 +365,7 @@
365 365  
366 366  == 4.2 Time and Time Format ==
367 367  
368 -==== 4.2.1 Introduction ====
381 +==== 4.2.1 Introduction ====
369 369  
370 370  First, it is important to recognize that most observation times are a period. SDMX specifies precisely how Time is handled.
371 371  
... ... @@ -414,7 +414,7 @@
414 414  
415 415  This is used to unambiguously state that a date-time represents an observation at a single point in time. Therefore, if one wants to use SDMX for data which is measured at a distinct point in time rather than being reported over a period, the date-time representation can be used.
416 416  
417 -Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
430 +Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[^^~[1~]^^>>path:#_ftn1]]
418 418  
419 419  ==== 4.2.6 Standard Reporting Period ====
420 420  
... ... @@ -482,7 +482,7 @@
482 482  
483 483  Representation: common:ReportingWeekType (YYYY-Www, e.g. 2000-W53)
484 484  
485 -Notes: There are either 52 or 53 weeks in a reporting year. This is based on the ISO 8601 definition of a week (Monday - Saturday), where the first week of a reporting year is defined as the week with the first Thursday on or after the reporting year start day.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[2~]^^>>path:#_ftn2]](%%) The reporting week is always represented as two digits, therefore 1-9 are 0 padded (e.g. 01). This allows the values to be sorted chronologically using textual sorting methods.
498 +Notes: There are either 52 or 53 weeks in a reporting year. This is based on the ISO 8601 definition of a week (Monday - Saturday), where the first week of a reporting year is defined as the week with the first Thursday on or after the reporting year start day.[[^^~[2~]^^>>path:#_ftn2]] The reporting week is always represented as two digits, therefore 1-9 are 0 padded (e.g. 01). This allows the values to be sorted chronologically using textual sorting methods.
486 486  
487 487  **Reporting Day**:
488 488  
... ... @@ -539,7 +539,7 @@
539 539  111. If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D.
540 540  1. **Determine [PERIOD_START]:**
541 541  
542 -Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
555 +Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[^^~[3~]^^>>path:#_ftn3]] this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
543 543  
544 544  1. **Determine the [PERIOD_END]:**
545 545  
... ... @@ -638,7 +638,7 @@
638 638  
639 639  When converting data from SDMX-EDI to SDMX-ML, the source time format is only necessary to determine the format of the target time value. For example, a source time format of will result in a target time in the format YYYY-Ss whereas a source format of will result in a target time value in the format YYYY-Qq.
640 640  
641 -==== 4.2.10 Time Zones ====
654 +==== 4.2.10 Time Zones ====
642 642  
643 643  In alignment with ISO 8601, SDMX allows the specification of a time zone on all time periods and on the reporting year start day. If a time zone is provided on a reporting year start day, then the same time zone (or none) should be reported for each reporting time period. If the reporting year start day and the reporting period time zone differ, the time zone of the reporting period will take precedence. Examples of each format with time zones are as follows (time zone indicated in bold):
644 644  
... ... @@ -659,7 +659,7 @@
659 659  
660 660  According to ISO 8601, a date without a time-zone is considered "local time". SDMX assumes that local time is that of the sender of the message. In this version of SDMX, an optional field is added to the sender definition in the header for specifying a time zone. This field has a default value of 'Z' (UTC). This determination of local time applies for all dates in a message.
661 661  
662 -==== 4.2.11 Representing Time Spans Elsewhere ====
675 +==== 4.2.11 Representing Time Spans Elsewhere ====
663 663  
664 664  It has been possible since SDMX 2.0 for a Component to specify a representation of a time span. Depending on the format of the data message, this resulted in either an element with 2 XML attributes for holding the start time and the duration or two separate XML attributes based on the underlying Component identifier. For example if REF_PERIOD were given a representation of time span, then in the Compact data format, it would be represented by two XML attributes; REF_PERIODStartTime (holding the start) and REF_PERIOD (holding the duration). If a new simple type is introduced in the SDMX schemas that can hold ISO 8601 time intervals, then this will no longer be necessary. What was represented as this:
665 665  
... ... @@ -669,11 +669,11 @@
669 669  
670 670  <Series REF_PERIOD="2000-01-01T00:00:00/P2M"/>
671 671  
672 -==== 4.2.12 Notes on Formats ====
685 +==== 4.2.12 Notes on Formats ====
673 673  
674 674  There is no ambiguity in these formats so that for any given value of time, the category of the period (and thus the intended time period range) is always clear. It should also be noted that by utilizing the ISO 8601 format, and a format loosely based on it for the report periods, the values of time can easily be sorted chronologically without additional parsing.
675 675  
676 -==== 4.2.13 Effect on Time Ranges ====
689 +==== 4.2.13 Effect on Time Ranges ====
677 677  
678 678  All SDMX-ML data messages are capable of functioning in a manner similar to SDMX-EDI if the Dimension at the observation level is time: the time period for the first observation can be stated and the rest of the observations can omit the time value as it can be derived from the start time and the frequency. Since the frequency can be determined based on the actual format of the time value for everything but distinct points in time and time ranges, this makes is even simpler to process as the interval between time ranges is known directly from the time value.
679 679  
... ... @@ -752,7 +752,7 @@
752 752  
753 753   2010-D185 or later (reporting year start day ~-~-07-01)
754 754  
755 -== 4.3 Structural Metadata Querying Best Practices ==
768 +== 4.3 Structural Metadata Querying Best Practices ==
756 756  
757 757  When querying for structural metadata, the ability to state how references should be resolved is quite powerful. However, this mechanism is not always necessary and can create an undue burden on the systems processing the queries if it is not used properly.
758 758  
... ... @@ -760,7 +760,7 @@
760 760  
761 761  When the referenced object is not known, then the reference resolution mechanism could be used. For example, suppose one wanted to find all category schemes and the related categorisations for a given maintenance agency. In this case, one could query for the category scheme by the maintenance agency and specify that parent and sibling references should be resolved. This would result in the categorisations which reference the categories in the matched schemes to be returned, as well as the object which they categorise.
762 762  
763 -== 4.4 Versioning and External Referencing ==
776 +== 4.4 Versioning and External Referencing ==
764 764  
765 765  Within the SDMX-ML Structure Message, there is a pattern for versioning and external referencing which should be pointed out. The identifiers are qualified by their version numbers – that is, an object with an Agency of “A”, and ID of “X” and a version of “1.0” is a different object than one with an Agency of “A’, an ID of “X”, and a version of “1.1”.
766 766  
... ... @@ -1175,12 +1175,12 @@
1175 1175  1. Restricts the code list for the CAS Dimension to codes TOT and NAP.
1176 1176  1. Inherits the AGE constraint applied at the level of the DSD.
1177 1177  
1178 -=== Provision Agreements CENSUS_CUBE1_IT ===
1191 +=== Provision Agreements CENSUS_CUBE1_IT ===
1179 1179  
1180 1180  1. Restricts the codes for the GEO Dimension to IT and its children.
1181 1181  1. Inherits the constraints from Dataflow CENSUS_CUBE1  for the AGE and CAS Dimensions.
1182 1182  
1183 -=== Provision Agreements CENSUS_CUBE2_IT ===
1196 +=== Provision Agreements CENSUS_CUBE2_IT ===
1184 1184  
1185 1185  1. Restricts the codes for the GEO Dimension to IT and its children.
1186 1186  1. Inherits the constraints from Dataflow CENSUS_CUBE2 for the CAS Dimension.
... ... @@ -1210,7 +1210,7 @@
1210 1210  
1211 1211  == 9.2 Groups and Dimension Groups ==
1212 1212  
1213 -=== 9.2.1 Issue ===
1226 +=== 9.2.1 Issue ===
1214 1214  
1215 1215  Version 2.1 introduces a more granular mechanism for specifying the relationship between a Data Attribute and the Dimensions to which the attribute applies. The technical construct for this is the Dimension Group. This Dimension Group has no direct equivalent in versions 2.0 and 1.0 and so the application transforming data from a version 2.1 data set to a version 2.0 or version 1.0 data set must decide to which construct the attribute value, whose Attribute is declared in a Dimension Group, should be attached. The closest construct is the “Series” attachment level and in many cases this is the correct construct to use.
1216 1216  
... ... @@ -1235,7 +1235,7 @@
1235 1235  
1236 1236  == 10.1 Introduction ==
1237 1237  
1238 -The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
1251 +The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones[[^^~[4~]^^>>path:#_ftn4]]. The purpose of the VTL in the SDMX context is to enable the:
1239 1239  
1240 1240  * definition of validation and transformation algorithms, in order to specify how to calculate new data  from existing ones;
1241 1241  * exchange of the definition of VTL algorithms, also together the definition of the data structures of the involved data (for example, exchange the data structures of a reporting framework together with the validation rules to be applied, exchange the input and output data structures of a calculation task together with the VTL Transformations describing the calculation algorithms);
... ... @@ -1249,7 +1249,7 @@
1249 1249  
1250 1250  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.
1251 1251  
1252 -== 10.2 References to SDMX artefacts from VTL statements ==
1265 +== 10.2 References to SDMX artefacts from VTL statements ==
1253 1253  
1254 1254  === 10.2.1 Introduction ===
1255 1255  
... ... @@ -1259,7 +1259,7 @@
1259 1259  
1260 1260  In any case, the aliases used in the VTL transformations have to be mapped to the
1261 1261  
1262 -SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL transformations, rulesets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%)  to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 
1275 +SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL transformations, rulesets[[^^~[5~]^^>>path:#_ftn5]] or user defined operators[[^^~[6~]^^>>path:#_ftn6]]  to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 
1263 1263  
1264 1264  The correspondence between an alias and a SDMX artefact must be one-to-one, meaning that a generic alias  identifies one and just one SDMX artefact while a SDMX artefact is identified by one and just one alias. In other words, within a VtlMappingScheme an artefact can have just one alias and different artefacts cannot have the same alias.
1265 1265  
... ... @@ -1269,15 +1269,15 @@
1269 1269  
1270 1270  This approach has the advantage that in the VTL code the URN of the referenced artefacts is directly intelligible by a human reader but has the drawback that the references are verbose.
1271 1271  
1272 -The SDMX URN[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[7~]^^>>path:#_ftn7]](%%) is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:^^ ^^
1285 +The SDMX URN[[^^~[7~]^^>>path:#_ftn7]] is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:^^ ^^
1273 1273  
1274 -* SDMXprefix                                                                                   
1275 -* SDMX-IM-package-name             
1276 -* class-name                                                                        
1277 -* agency-id                                                                          
1287 +* SDMXprefix
1288 +* SDMX-IM-package-name 
1289 +* class-name
1290 +* agency-id 
1278 1278  * maintainedobject-id
1279 1279  * maintainedobject-version
1280 -* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
1293 +* container-object-id [[^^~[8~]^^>>path:#_ftn8]]
1281 1281  * object-id
1282 1282  
1283 1283  The generic structure of the URN is the following:
... ... @@ -1296,7 +1296,7 @@
1296 1296  
1297 1297  The **agency-id** is the acronym of the agency that owns the definition of the artefact, for example for the Eurostat artefacts the agency-id is “ESTAT”). The agency-id can be composite (for example AgencyA.Dept1.Unit2).
1298 1298  
1299 -The **maintainedobject-id** is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
1312 +The **maintainedobject-id** is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable[[^^~[9~]^^>>path:#_ftn9]], coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
1300 1300  
1301 1301  * if the artefact is a ,,Dataflow,,, which is a maintainable class,  the maintainedobject-id is the Dataflow name (dataflow-id);
1302 1302  * if the artefact is a Dimension, MeasureDimension, TimeDimension, PrimaryMeasure 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;
... ... @@ -1316,7 +1316,7 @@
1316 1316  
1317 1317  * if the artefact is a ,,Concept ,,(the object-id is the name of the ,,Concept,,)
1318 1318  
1319 -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 and their Agency is AG, would be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[10~]^^>>path:#_ftn10]](%%):
1332 +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 and their Agency is AG, would be written as[[^^~[10~]^^>>path:#_ftn10]]:
1320 1320  
1321 1321  ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  <-
1322 1322  
... ... @@ -1332,10 +1332,10 @@
1332 1332  
1333 1333  * 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.
1334 1334  * 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: 
1335 -** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,  
1348 +** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,
1336 1336  ** “conceptscheme” for the classes Concept and ConceptScheme o “codelist” for the class Codelist.
1337 -* 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" %)^^~[11~]^^>>path:#_ftn11]](%%), 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" %)^^~[12~]^^>>path:#_ftn12]](%%).
1338 -* 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 agency-id can be omitted if it is the same as the invoking T,,ransformationScheme,, and cannot be omitted if the artefact comes from another agency.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[13~]^^>>path:#_ftn13]](%%)  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).
1350 +* 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[[^^~[11~]^^>>path:#_ftn11]], the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section “Mapping between VTL and SDMX” hereinafter)[[^^~[12~]^^>>path:#_ftn12]].
1351 +* 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 agency-id can be omitted if it is the same as the invoking T,,ransformationScheme,, and cannot be omitted if the artefact comes from another agency.[[^^~[13~]^^>>path:#_ftn13]]  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).
1339 1339  * 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;
1340 1340  ** if the referenced artefact is a Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, 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
1341 1341  
... ... @@ -1346,7 +1346,7 @@
1346 1346  ** if the referenced artefact is a ,,Codelist, ,,which is a maintainable class, the maintainedobject-id is the ,,codelist-id,, and obviously cannot be omitted.
1347 1347  * When the maintainedobject-id is omitted, the **maintainedobject-version** is omitted too. When the maintainedobject-id is not omitted and the maintainedobject-version is omitted, the version 1.0 is assumed by default.,, ,,
1348 1348  * As said, the **container-object-id** does not apply to the classes that can be referenced in VTL transformations, therefore is not present in their URN
1349 -* The **object-id** does not exist for the artefacts belonging to the ,,Dataflow, ConceptScheme,, and ,,Codelist,, classes, while it exists and cannot be omitted for the artefacts belonging to the classes Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute and Concept, as for
1362 +* The **object-id** does not exist for the artefacts belonging to the ,,Dataflow,,,,, ConceptScheme,, and ,,Codelist,, classes, while it exists and cannot be omitted for the artefacts belonging to the classes Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute and Concept, as for
1350 1350  
1351 1351  them the object-id is the main identifier of the artefact
1352 1352  
... ... @@ -1358,15 +1358,15 @@
1358 1358  
1359 1359  ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0)’
1360 1360  
1361 -by omitting all the non-essential parts would become simply:                          
1374 +by omitting all the non-essential parts would become simply:  
1362 1362  
1363 1363  DFR  :=  DF1 + DF2
1364 1364  
1365 -The references to the ,,Codelists,, can be simplified similarly. For example, given the non-abbreviated reference to the ,,Codelist,,  AG:CL_FREQ(1.0), which is[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[14~]^^>>path:#_ftn14]](%%):
1378 +The references to the ,,Codelists,, can be simplified similarly. For example, given the non-abbreviated reference to the ,,Codelist,,  AG:CL_FREQ(1.0), which is[[^^~[14~]^^>>path:#_ftn14]]:
1366 1366  
1367 1367  ‘urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0)’
1368 1368  
1369 -if the ,,Codelist,, is referenced from a ruleset scheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[15~]^^>>path:#_ftn15]](%%):
1382 +if the ,,Codelist,, is referenced from a ruleset scheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply[[^^~[15~]^^>>path:#_ftn15]]:
1370 1370  
1371 1371  CL_FREQ
1372 1372  
... ... @@ -1376,7 +1376,7 @@
1376 1376  
1377 1377  SECTOR
1378 1378  
1379 -For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[16~]^^>>path:#_ftn16]](%%):
1392 +For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[^^~[16~]^^>>path:#_ftn16]]:
1380 1380  
1381 1381  ‘DFR(1.0)’ := ‘DF1(1.0)’ [rename SECTOR to SEC]
1382 1382  
... ... @@ -1410,9 +1410,9 @@
1410 1410  
1411 1411  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. 
1412 1412  
1413 -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 or to a SDMX ConceptScheme (for SDMX measure dimensions), 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" %)^^~[17~]^^>>path:#_ftn17]](%%).
1426 +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 or to a SDMX ConceptScheme (for SDMX measure dimensions), while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation[[^^~[17~]^^>>path:#_ftn17]].
1414 1414  
1415 -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" %)^^~[18~]^^>>path:#_ftn18]](%%)
1428 +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.[[^^~[18~]^^>>path:#_ftn18]]
1416 1416  
1417 1417  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, ConceptScheme, Concept) to can be deduced from the Ruleset signature.
1418 1418  
... ... @@ -1426,15 +1426,15 @@
1426 1426  
1427 1427  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. 
1428 1428  
1429 -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" %)^^~[19~]^^>>path:#_ftn19]](%%).
1442 +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[[^^~[19~]^^>>path:#_ftn19]].
1430 1430  
1431 1431  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 assignmentStatus 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). 
1432 1432  
1433 1433  === 10.3.2 General mapping of VTL and SDMX data structures ===
1434 1434  
1435 -This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%).
1448 +This section makes reference to the VTL “Model for data and their structure”[[^^~[20~]^^>>path:#_ftn20]] and the correspondent SDMX “Data Structure Definition”[[^^~[21~]^^>>path:#_ftn21]].
1436 1436  
1437 -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" %)^^~[22~]^^>>path:#_ftn22]](%%)
1450 +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).[[^^~[22~]^^>>path:#_ftn22]]
1438 1438  
1439 1439  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.
1440 1440  
... ... @@ -1444,7 +1444,7 @@
1444 1444  
1445 1445  SDMX DimensionComponent can be a Dimension, a TimeDimension or a MeasureDimension. Correspondingly, in the SDMX implementation of the VTL, the VTL Identifiers can be (optionally) distinguished in three sub-classes (Simple Identifier, Time Identifier, Measure Identifier) even if such a distinction is not evidenced in the VTL IM. 
1446 1446  
1447 -However, a VTL Data Structure can have any number of Identifiers, Measures and Attributes, while a SDMX 2.1 DataStructureDefinition can have any number of Dimensions and DataAttributes but just one PrimaryMeasure[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[23~]^^>>path:#_ftn23]](%%). This is due to a difference between SDMX 2.1 and VTL in the possible representation methods of the data that contain more measures.
1460 +However, a VTL Data Structure can have any number of Identifiers, Measures and Attributes, while a SDMX 2.1 DataStructureDefinition can have any number of Dimensions and DataAttributes but just one PrimaryMeasure[[^^~[23~]^^>>path:#_ftn23]]. This is due to a difference between SDMX 2.1 and VTL in the possible representation methods of the data that contain more measures.
1448 1448  
1449 1449  As for SDMX, because the data structure cannot contain more than one measure component (i.e., the primaryMeasure), the representation of data having more measures is possible only by means of a particular dimension, called MeasureDimension, which is aimed at containing the name of the measure concepts, so that for each observation the value contained in the PrimaryMeasure component is the value of the measure concept reported in the MeasureDimension component. 
1450 1450  
... ... @@ -1534,7 +1534,7 @@
1534 1534  
1535 1535  This mapping method cannot be applied for SDMX 2.1 if the VTL data structure has more than one measure component, given that the SDMX 2.1 DataStructureDefinition allows just one measure component (the
1536 1536  
1537 -PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)
1550 +PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[^^~[24~]^^>>path:#_ftn24]]
1538 1538  
1539 1539  1960 Please note that the VTL measures can have any name while in SDMX 2.1 the 1961 MeasureComponent has the mandatory name “obs_value”, therefore the name of the VTL measure name must become “obs_value” in SDMX 2.1. 
1540 1540  
... ... @@ -1651,15 +1651,15 @@
1651 1651  
1652 1652   The VtlMappingScheme is a container for zero or more VtlDataflowMapping (besides possible mappings to artefacts other than dataflows).
1653 1653  
1654 -=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
1667 +=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[^^**~[25~]**^^>>path:#_ftn25]] ===
1655 1655  
1656 1656  Until now it as been assumed to map one SMDX Dataflow to one VTL dataset 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
1657 1657  
1658 1658  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).
1659 1659  
1660 -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" %)^^~[26~]^^>>path:#_ftn26]](%%)
1673 +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.[[^^~[26~]^^>>path:#_ftn26]]
1661 1661  
1662 -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" %)^^~[27~]^^>>path:#_ftn27]](%%)
1675 +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.[[^^~[27~]^^>>path:#_ftn27]]
1663 1663  
1664 1664   Given a SDMX Dataflow and some predefined Dimensions of its
1665 1665  
... ... @@ -1671,14 +1671,14 @@
1671 1671  
1672 1672  In practice, this kind mapping is obtained like follows:
1673 1673  
1674 -* For a given SDMX dataflow, the user (VTL definer) declares  the dimension components on which the mapping will be based, in a given order.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
1687 +* For a given SDMX dataflow, the user (VTL definer) declares  the dimension components on which the mapping will be based, in a given order.[[^^~[28~]^^>>path:#_ftn28]] Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
1675 1675  * The VTL dataset is given a name using a special notation also called “ordered concatenation” and composed of the following parts: 
1676 1676  ** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated
1677 1677  
1678 -URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
1691 +URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[^^~[29~]^^>>path:#_ftn29]]
1679 1679  
1680 1680  *
1681 -** The reference to a specific part of the SDMX dataflow above, expressed as the concatenation of the values that the SDMX dimensions declared above must have, separated by dots (“.”) and written in the order in which these dimensions are defined[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[30~]^^>>path:#_ftn30]](%%) . For example  POPULATION.USA would mean that such a VTL dataset is mapped to the SDMX observations for which the dimension  //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.
1694 +** The reference to a specific part of the SDMX dataflow above, expressed as the concatenation of the values that the SDMX dimensions declared above must have, separated by dots (“.”) and written in the order in which these dimensions are defined[[^^~[30~]^^>>path:#_ftn30]] . For example  POPULATION.USA would mean that such a VTL dataset is mapped to the SDMX observations for which the dimension  //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.
1682 1682  
1683 1683  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.
1684 1684  
... ... @@ -1696,7 +1696,7 @@
1696 1696  
1697 1697  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.
1698 1698  
1699 -As already said, the mapping from SDMX to VTL happens when the VTL datasets are operand of VTL transformations, instead the mapping from VTL to SDMX happens when the VTL datasets are result of VTL transformations[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[31~]^^>>path:#_ftn31]](%%) and 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.
1712 +As already said, the mapping from SDMX to VTL happens when the VTL datasets are operand of VTL transformations, instead the mapping from VTL to SDMX happens when the VTL datasets are result of VTL transformations[[^^~[31~]^^>>path:#_ftn31]] and 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.
1700 1700  
1701 1701  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)) need to be mapped to distinct VTL datasets that are operand of some VTL transformations.
1702 1702  
... ... @@ -1706,7 +1706,7 @@
1706 1706  
1707 1707  //COUNTRYvalue//. For example, the VTL dataset ‘DF1(1.0)/POPULATION.USA’ would contain all the observations of DF1(1.0) having INDICATOR = POPULATION and COUNTRY = USA.
1708 1708  
1709 -In order to obtain the data structure of these VTL datasets from the SDMX one, it is assumed that the SDMX dimensions 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 datasets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[32~]^^>>path:#_ftn32]](%%). After that, the mapping method from SDMX to VTL specified for the dataflow DF1(1.0) is applied (i.e. basic, pivot …). 
1722 +In order to obtain the data structure of these VTL datasets from the SDMX one, it is assumed that the SDMX dimensions 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 datasets[[^^~[32~]^^>>path:#_ftn32]]. After that, the mapping method from SDMX to VTL specified for the dataflow DF1(1.0) is applied (i.e. basic, pivot …). 
1710 1710  
1711 1711  In the example above, for all the datasets of the kind
1712 1712  
... ... @@ -1726,7 +1726,7 @@
1726 1726  
1727 1727  …   …   …
1728 1728  
1729 -In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX dataflow to different VTL datasets 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" %)^^~[33~]^^>>path:#_ftn33]]
1742 +In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX dataflow to different VTL datasets 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. [[^^~[33~]^^>>path:#_ftn33]]
1730 1730  
1731 1731  In the direction from SDMX to VTL it is allowed to omit the value of one or more Dimensions 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.
1732 1732  
... ... @@ -1749,12 +1749,12 @@
1749 1749  
1750 1750  For example, let us assume that the VTL programmer wants to calculate the SDMX dataflow DF2(1.0) 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) that have different combinations of values for INDICATOR and COUNTRY:
1751 1751  
1752 -* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)
1753 -* the data structure of all these VTL datasets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[35~]^^>>path:#_ftn35]]
1765 +* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[^^~[34~]^^>>path:#_ftn34]]
1766 +* the data structure of all these VTL datasets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.[[^^~[35~]^^>>path:#_ftn35]]
1754 1754  
1755 -Under these hypothesis, such derived VTL datasets can be mapped to DF2(1.0) by declaring the Dimensions INDICATOR and COUNTRY as mapping dimensions[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[36~]^^>>path:#_ftn36]](%%).
1768 +Under these hypothesis, such derived VTL datasets can be mapped to DF2(1.0) by declaring the Dimensions INDICATOR and COUNTRY as mapping dimensions[[^^~[36~]^^>>path:#_ftn36]].
1756 1756  
1757 -The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]
1770 +The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[^^~[37~]^^>>path:#_ftn37]]
1758 1758  
1759 1759  ‘DF2(1.0)///INDICATORvalue//.//COUNTRYvalue//’  <-  expression
1760 1760  
... ... @@ -1776,19 +1776,19 @@
1776 1776  As said, it is assumed that these VTL derived datasets 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:
1777 1777  
1778 1778  |(((
1779 - //VTL dataset                                             //
1792 + //VTL dataset //
1780 1780  
1781 1781  
1782 1782  )))|(% colspan="2" %)//INDICATOR value //|(% colspan="2" %)//COUNTRY value//
1783 -|‘DF2(1.0)/GDPPERCAPITA.USA’              |GDPPERCAPITA| | |USA
1796 +|‘DF2(1.0)/GDPPERCAPITA.USA’    |GDPPERCAPITA| | |USA
1784 1784  |(((
1785 1785  ‘DF2(1.0)/GDPPERCAPITA.CANADA’  
1786 1786  
1787 1787  …   …   …
1788 1788  )))|GDPPERCAPITA| | |CANADA
1789 -|‘DF2(1.0)/POPGROWTH.USA’                  |POPGROWTH | | |USA
1802 +|‘DF2(1.0)/POPGROWTH.USA’   |POPGROWTH | | |USA
1790 1790  |(((
1791 -‘DF2(1.0)/POPGROWTH.CANADA’         
1804 +‘DF2(1.0)/POPGROWTH.CANADA’   
1792 1792  
1793 1793  …   …   …
1794 1794  )))|POPGROWTH | | |CANADA 
... ... @@ -1821,9 +1821,9 @@
1821 1821  
1822 1822  …);
1823 1823  
1824 -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)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[38~]^^>>path:#_ftn38]](%%), which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
1837 +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)[[^^~[38~]^^>>path:#_ftn38]], which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
1825 1825  
1826 -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" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
1839 +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. [[^^~[39~]^^>>path:#_ftn39]][[^^~[40~]^^>>path:#_ftn40]]
1827 1827  
1828 1828  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).
1829 1829  
... ... @@ -1846,7 +1846,7 @@
1846 1846  )))
1847 1847  |**Code**|**Code** (for enumerated Dimension, PrimaryMeasure, DataAttribute) or **Concept** (for MeasureDimension)
1848 1848  |**Described Value Domain**|(((
1849 -non-enumerated** Representation**
1862 +non-enumerated** Representation**
1850 1850  
1851 1851  (having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
1852 1852  )))
... ... @@ -1872,7 +1872,7 @@
1872 1872  
1873 1873  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). 
1874 1874  
1875 -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" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[42~]^^>>path:#_ftn42]](%%) This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
1888 +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[[^^~[41~]^^>>path:#_ftn41]], while the SDMX Concepts can have different Representations in different DataStructures.[[^^~[42~]^^>>path:#_ftn42]] This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
1876 1876  
1877 1877  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
1878 1878  
... ... @@ -1921,7 +1921,7 @@
1921 1921  
1922 1922  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.
1923 1923  
1924 -=== 10.4.3 Mapping SDMX data types to VTL basic scalar types ===
1937 +=== 10.4.3 Mapping SDMX data types to VTL basic scalar types ===
1925 1925  
1926 1926  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
1927 1927  
... ... @@ -1988,7 +1988,7 @@
1988 1988  |(((
1989 1989  **Boolean **
1990 1990  
1991 -(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false}) 
2004 +(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
1992 1992  )))|**boolean**
1993 1993  |(((
1994 1994  **URI **
... ... @@ -2131,7 +2131,7 @@
2131 2131  
2132 2132  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).
2133 2133  
2134 -=== 10.4.4 Mapping VTL basic scalar types to SDMX data types ===
2147 +=== 10.4.4 Mapping VTL basic scalar types to SDMX data types ===
2135 2135  
2136 2136  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
2137 2137  
... ... @@ -2217,7 +2217,7 @@
2217 2217  |N|fixed number of digits used in the preceding  textual representation of the month or the day
2218 2218  | |
2219 2219  
2220 -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" %)^^~[43~]^^>>path:#_ftn43]](%%).
2233 +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[[^^~[43~]^^>>path:#_ftn43]].
2221 2221  
2222 2222  === 10.4.5 Null Values ===
2223 2223