Changes for page SDMX 2.1 Standards. Section 6. Technical Notes

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@@ -1,21 +1,18 @@
--{{box title="**Contents**"}}
--{{toc/}}
--{{/box}}
++Revision History
--**Revision History**
++|**Revision**|**Date**|**Contents**
++| |April 2011|Initial release
++|1.0|April 2013|Added section 9 - Transforming between versions of SDMX
++|2.0|July 2020|Added section 10 – Validation and Transformation Language – before the Annex 1.
--(% style="width:954.835px" %)
--|(% style="width:106px" %)**Revision**|(% style="width:124px" %)**Date**|(% style="width:723px" %)**Contents**
--|(% style="width:106px" %) |(% style="width:124px" %)April 2011|(% style="width:723px" %)Initial release
--|(% style="width:106px" %)1.0|(% style="width:124px" %)April 2013|(% style="width:723px" %)Added section 9 - Transforming between versions of SDMX
--|(% style="width:106px" %)2.0|(% style="width:124px" %)July 2020|(% style="width:723px" %)Added section 10 – Validation and Transformation Language – before the Annex 1.
--
  = 1 Purpose and Structure =
  == 1.1 Purpose ==
--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.
++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.
++
  == 1.2 Structure ==
  This document is organized into the following major parts:
@@ -40,20 +40,24 @@
  == 3.2 SDMX Information Model for Format Implementers ==
--=== 3.2.1 Introduction ===
++=== 3.2.1       Introduction ===
--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.
++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.
  The SDMX-IM is used to describe the basic data and metadata structures used in all of the SDMX data formats. The Information Model concerns itself with statistical data and its structural metadata, and that is what is described here. Both structural metadata and data have some additional metadata in common, related to their management and administration. These aspects of the data model are not addressed in this section and covered elsewhere in this guide or in the full SDMX-IM document.
  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:
--* 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;
--* 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
--* the section on data representation is now a convention, to support interoperability with EDIFACT-syntax implementations ( see section 3.3.2);
++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;
--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.
++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
++the section on data representation is now a convention, to support interoperability with EDIFACT-syntax implementations ( see section 3.3.2);
++
++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.
++
  Note that in the descriptions below, text in courier and italicised are the names used in the information model (e.g. //DataSet//).
  == 3.3 SDMX-ML and SDMX-EDI: Comparison of Expressive Capabilities and Function ==
@@ -60,43 +60,55 @@
  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.
--=== 3.3.1 Format Optimizations and Differences ===
++=== 3.3.1        Format Optimizations and Differences ===
  The following section provides a brief overview of the differences between the various SDMX formats.
--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).
++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).
++
  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.
--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.
++To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages;
--**//Structure Definition//**
++//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.
++=== //Structure Definition// ===
++
  The SDMX-ML Structure Message supports the use of annotations to the structure, which is not supported by the SDMX-EDI syntax.
  The SDMX-ML Structure Message allows for the structures on which a Data Structure Definition depends – that is, codelists and concepts – to be either included in the message or to be referenced by the message containing the data structure definition. XML syntax is designed to leverage URIs and other Internet-based referencing mechanisms, and these are used in the SDMX-ML message. This option is not available to those using the SDMX-EDI structure message.
--**//Validation//**
++=== //Validation// ===
--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.)
++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.)
++
  The SDMX-ML Generic Data Message also leaves validation above the XML syntax level to the application.
  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.
--//Update and Delete Messages and Documentation Messages//
++=== //Update and Delete Messages and Documentation Messages// ===
  All SDMX data messages allow for both delete messages and messages consisting of only data or only documentation.
--**//Character Encodings//**
++=== //Character Encodings// ===
--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.
++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
--**//Data Typing//**
++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.
++
++=== //Data Typing// ===
++
  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.
--=== 3.3.2 Data Types ===
++==== 3.3.2        Data Types ====
  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.
@@ -112,8 +112,7 @@
 *. Maximum 70 characters.
 *. From ISO 8859-1 character set (including accented characters)
 . **Descriptions **are:
--1*. Maximum 350 characters;
--1*. From ISO 8859-1 character set.
++1*. Maximum 350 characters;             From ISO 8859-1 character set.
 . **Code values** are:
 *. Maximum 18 characters;
 *. Any of A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore), / (solidus, slash), = (equal sign), - (hyphen);
@@ -122,51 +122,45 @@
  A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore)
--**5. Observation values** are:
++1. **Observation values** are:
++1*. Decimal numerics (signed only if they are negative);
++1*. The maximum number of significant figures is:
++1*. 15 for a positive number
++1*. 14 for a positive decimal or a negative integer
++1*. 13 for a negative decimal
++1*. Scientific notation may be used.
++1. **Uncoded statistical concept** text values are:
++1*.
++1**. Maximum 1050 characters;
++1**. From ISO 8859-1 character set.
++1. **Time series keys**:
--* Decimal numerics (signed only if they are negative);
--* The maximum number of significant figures is:
--* 15 for a positive number
--* 14 for a positive decimal or a negative integer
--* 13 for a negative decimal
--* Scientific notation may be used.
++In principle, the maximum permissible length of time series keys used in a data exchange does not need to be restricted. However, for working purposes, an effort is made to limit the maximum length to 35 characters; in this length, also (for SDMXEDI) one (separator) position is included between all successive dimension values; this means that the maximum length allowed for a pure series key (concatenation of dimension values) can be less than 35 characters.  The separator character is a colon (“:”) by conventional usage.
--**6. Uncoded statistical concept** text values are:
--
--* Maximum 1050 characters;
--* From ISO 8859-1 character set.
--
--**7. Time series keys**:
--
--In principle, the maximum permissible length of time series keys used in a data exchange does not need to be restricted. However, for working purposes, an effort is made to limit the maximum length to 35 characters; in this length, also (for SDMXEDI) one (separator) position is included between all successive dimension values; this means that the maximum length allowed for a pure series key (concatenation of dimension values) can be less than 35 characters. The separator character is a colon (“:”) by conventional usage.
--
  == 3.4 SDMX-ML and SDMX-EDI Best Practices ==
--=== 3.4.1 Reporting and Dissemination Guidelines ===
++=== 3.4.1        Reporting and Dissemination Guidelines ===
--==== 3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges ====
++**3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges **Central institutions are the organisations to which other partner institutions "report" statistics. These statistics are used by central institutions either to compile aggregates and/or they are put together and made available in a uniform manner (e.g. on-line or on a CD-ROM or through file transfers). Therefore, central institutions receive data from other institutions and, usually, they also "disseminate" data to individual and/or institutions for end-use.  Within a country, a NSI or a national central bank (NCB) plays, of course, a central institution role as it collects data from other entities and it disseminates statistical information to end users. In SDMX the role of central institution is very important: every statistical message is based on underlying structural definitions (statistical concepts, code lists, DSDs) which have been devised by a particular agency, usually a central institution. Such an institution plays the role of the reference "structural definitions maintenance agency" for the corresponding messages which are exchanged. Of course, two institutions could exchange data using/referring to structural information devised by a third institution.
--Central institutions are the organisations to which other partner institutions "report" statistics. These statistics are used by central institutions either to compile aggregates and/or they are put together and made available in a uniform manner (e.g. on-line or on a CD-ROM or through file transfers). Therefore, central institutions receive data from other institutions and, usually, they also "disseminate" data to individual and/or institutions for end-use. Within a country, a NSI or a national central bank (NCB) plays, of course, a central institution role as it collects data from other entities and it disseminates statistical information to end users. In SDMX the role of central institution is very important: every statistical message is based on underlying structural definitions (statistical concepts, code lists, DSDs) which have been devised by a particular agency, usually a central institution. Such an institution plays the role of the reference "structural definitions maintenance agency" for the corresponding messages which are exchanged. Of course, two institutions could exchange data using/referring to structural information devised by a third institution.
--
  Central institutions can play a double role:
  * collecting and further disseminating statistics;
  * devising structural definitions for use in data exchanges.
--==== 3.4.1.2 Defining Data Structure Definitions (DSDs) ====
++**3.4.1.2 Defining Data Structure Definitions (DSDs)**
  The following guidelines are suggested for building a DSD. However, it is expected that these guidelines will be considered by central institutions when devising new DSDs.
--(% class="wikigeneratedid" id="HDimensions2CAttributesandCodeLists" %)
--__Dimensions, Attributes and Code Lists__
++=== Dimensions, Attributes and Code Lists ===
--**//Avoid dimensions that are not appropriate for all the series in the data structure definition.//** If some dimensions are not applicable (this is evident from the need to have a code in a code list which is marked as “not applicable”, “not relevant” or “total”) for some series then consider moving these series to a new data structure definition in which these dimensions are dropped from the key structure. This is a judgement call as it is sometimes difficult to achieve this without increasing considerably the number of DSDs.
++**//Avoid dimensions that are not appropriate for all the series in the data structure definition.//**  If some dimensions are not applicable (this is evident from the need to have a code in a code list which is marked as “not applicable”, “not relevant” or “total”) for some series then consider moving these series to a new data structure definition in which these dimensions are dropped from the key structure. This is a judgement call as it is sometimes difficult to achieve this without increasing considerably the number of DSDs.
  **//Devise DSDs with a small number of Dimensions for public viewing of data.//** A DSD with the number dimensions in excess 6 or 7 is often difficult for non specialist users to understand. In these cases it is better to have a larger number of DSDs with smaller “cubes” of data, or to eliminate dimensions and aggregate the data at a higher level. Dissemination of data on the web is a growing use case for the SDMX standards: the differentiation of observations by dimensionality which are necessary for statisticians and economists are often obscure to public consumers who may not always understand the semantic of the differentiation.
--**//Avoid composite dimensions.//** Each dimension should correspond to a single characteristic of the data, not to a combination of characteristics.
++**//Avoid composite dimensions.//**  Each dimension should correspond to a single characteristic of the data, not to a combination of characteristics.
--**//Consider the inclusion of the following attributes//**. Once the key structure of a data structure definition has been decided, then the set of (preferably mandatory) attributes of this data structure definition has to be defined. In general, some statistical concepts are deemed necessary across all Data Structure Definitions to qualify the contained information. Examples of these are:
++**//Consider the inclusion of the following attributes//**. Once the key structure of a data structure definition has been decided, then the set of (preferably mandatory) attributes  of this data structure definition has to be defined. In general, some statistical concepts are deemed necessary across all Data Structure Definitions to qualify the contained information. Examples of these are:
  * A descriptive title for the series (this is most useful for dissemination of data for viewing e.g. on the web)
  * Collection (e.g. end of period, averaged or summed over period)
@@ -188,7 +188,7 @@
  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.
--__Data Structure Definition Structure__
++=== Data Structure Definition Structure   ===
  The following items have to be specified by a structural definitions maintenance agency when defining a new data structure definition:
@@ -218,7 +218,7 @@
  * code list name
  * code values and descriptions
--Definition of data flow definitions. Two (or more) partners performing data exchanges in a certain context need to agree on:
++Definition of data flow definitions.  Two (or more) partners performing data exchanges in a certain context need to agree on:
  * the list of data set identifiers they will be using;
  * for each data flow:
@@ -225,13 +225,11 @@
  * its content and description
  * the relevant DSD that defines the structure of the data reported or disseminated according the the dataflow definition
--==== 3.4.1.3 Exchanging Attributes ====
++**3.4.1.3 Exchanging Attributes**
--===== //3.4.1.3.1 Attributes on series, sibling and data set level // =====
++**//3.4.1.3.1 Attributes on series, sibling and data set level //**//Static properties//.
--//Static properties//.
--
--* Upon creation of a series the sender has to provide to the receiver values for all mandatory attributes. In case they are available, values for conditional attributes should also be provided. Whereas initially this information may be provided by means other than SDMX-ML or SDMX-EDI messages (e.g. paper, telephone) it is expected that partner institutions will be in a position to provide this information in SDMX-ML or SDMX-EDI format over time.
++* Upon creation of a series the sender has to provide to the receiver values for all mandatory attributes. In case they are available, values for conditional attributes  should also be provided. Whereas initially this information may be provided by means other than SDMX-ML or SDMX-EDI messages (e.g. paper, telephone) it is expected that partner institutions will be in a position to provide this information in SDMX-ML or SDMX-EDI format over time.
  * A centre may agree with its data exchange partners special procedures for authorising the setting of attributes' initial values.
  * Attribute values at a data set level are set and maintained exclusively by the centre administrating the exchanged data set.
@@ -238,7 +238,7 @@
  //Communication of changes// to the centre.
  * Following the creation of a series, the attribute values do not have to be reported again by senders, as long as they do not change.
--* Whenever changes in attribute values for a series (or sibling group) occur, the reporting institutions should report either all attribute values again (this is the recommended option) or only the attribute values which have changed. This applies both to the mandatory and the conditional attributes. For example, if a previously reported value for a conditional attribute is no longer valid, this has to be reported to the centre.
++* Whenever changes in attribute values for a series (or sibling group) occur, the reporting institutions should report either all attribute values again (this is the recommended option) or only the attribute values which have changed.  This applies both to the mandatory and the conditional attributes. For example, if a previously reported value for a conditional attribute is no longer valid, this has to be reported to the centre.
  * A centre may agree with its data exchange partners special procedures for authorising modifications in the attribute values.
  Communication of observation level attributes “observation status”, "observation confidentiality", "observation pre-break".
@@ -247,21 +247,21 @@
  * If the “observation status” changes and the observation remains unchanged, both components would have to be reported.
  * For Data Structure Definitions having also the observation level attributes “observation confidentiality” and "observation pre-break" defined, this rule applies to these attribute as well: if an institution receives from another institution an observation with an observation status attribute only attached, this means that the associated observation confidentiality and prebreak observation attributes either never existed or from now they do not have a value for this observation.
--=== 3.4.2 Best Practices for Batch Data Exchange ===
++==== 3.4.2        Best Practices for Batch Data Exchange ====
--==== 3.4.2.1 Introduction ====
++**3.4.2.1 Introduction**
  Batch data exchange is the exchange and maintenance of entire databases between counterparties. It is an activity that often employs SDMX-EDI formats, and might also use the SDMX-ML DSD-specific data set. The following points apply equally to both formats.
--==== 3.4.2.2 Positioning of the Dimension "Frequency" ====
++**3.4.2.2 Positioning of the Dimension "Frequency"**
  The position of the “frequency” dimension is unambiguously identified in the data structure definition. Moreover, most central institutions devising structural definitions have decided to assign to this dimension the first position in the key structure. This facilitates the easy identification of this dimension, something that it is necessary to frequency's crucial role in several database systems and in attaching attributes at the “sibling” group level.
--==== 3.4.2.3 Identification of Data Structure Definitions (DSDs) ====
++**3.4.2.3 Identification of Data Structure Definitions (DSDs)**
  In order to facilitate the easy and immediate recognition of the structural definition maintenance agency that defined a data structure definition, most central institutions devising structural definitions use the first characters of the data structure definition identifiers to identify their institution: e.g. BIS_EER, EUROSTAT_BOP_01, ECB_BOP1, etc.
--==== 3.4.2.4 Identification of the Data Flows ====
++**3.4.2.4 Identification of the Data Flows**
  In order to facilitate the easy and immediate recognition of the institution administrating a data flow definitions, many central institutions prefer to use the first characters of the data flow definition identifiers to identify their institution: e.g. BIS_EER, ECB_BOP1, ECB_BOP1, etc. Note that in GESMES/TS the Data Set plays the role of the data flow definition (see //DataSet //in the SDMX-IM//)//.
@@ -269,7 +269,7 @@
  Note that the role of the Data Flow (called //DataflowDefintion// in the model) and Data Set is very specific in the model, and the terminology used may not be the same as used in all organisations, and specifically the term Data Set is used differently in SDMX than in GESMES/TS. Essentially the GESMES/TS term "Data Set" is, in SDMX, the "Dataflow Definition" whist the term "Data Set" in SDMX is used to describe the "container" for an instance of the data.
--==== 3.4.2.5 Special Issues ====
++**3.4.2.5 Special Issues**
  ===== 3.4.2.5.1 "Frequency" related issues =====
@@ -280,9 +280,10 @@
  **//Tick data.//** The issue of data collected at irregular intervals at a higher than daily frequency (e.g. tick-by-tick data) is not discussed here either. However, for data exchange purposes, such series can already be exchanged in the SDMX-EDI format by using the option to send observations with the associated time stamp.
++
  = 4 General Notes for Implementers =
--This section discusses a number of topics other than the exchange of data sets in SDMX-ML and SDMX-EDI. Supported only in SDMX-ML, these topics include the use of the reference metadata mechanism in SDMX, the use of Structure Sets and Reporting Taxonomies, the use of Processes, a discussion of time and data-typing, and some of the conventional mechanisms within the SDMX-ML Structure message regarding versioning and external referencing.
++This section discusses a number of topics other than the exchange of data sets in SDMX-ML and SDMX-EDI. Supported only in SDMX-ML, these topics include the use of the reference metadata mechanism in SDMX, the use of Structure Sets and Reporting Taxonomies, the use of Processes, a discussion of time and data-typing, and some of the conventional mechanisms within the SDMX-ML Structure message  regarding versioning and external referencing.
  This section does not go into great detail on these topics, but provides a useful overview of these features to assist implementors in further use of the parts of the specification which are relevant to them.
@@ -290,31 +290,39 @@
  There are several different representations in SDMX-ML, taken from XML Schemas and common programming languages. The table below describes the various representations which are found in SDMX-ML, and their equivalents.
--(% style="width:912.294px" %)
--|(% style="width:172px" %)**SDMX-ML Data Type**|(% style="width:204px" %)**XML Schema Data Type**|(% style="width:189px" %)**.NET Framework Type**|(% style="width:342px" %)(((
--**Java Data Type **
++|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|(((
++**Java Data Type**
++
++**~ **
  )))
--|(% style="width:172px" %)String|(% style="width:204px" %)xsd:string|(% style="width:189px" %)System.String|(% style="width:342px" %)java.lang.String
--|(% style="width:172px" %)Big Integer|(% style="width:204px" %)xsd:integer|(% style="width:189px" %)System.Decimal|(% style="width:342px" %)java.math.BigInteg er
--|(% style="width:172px" %)Integer|(% style="width:204px" %)xsd:int|(% style="width:189px" %)System.Int32|(% style="width:342px" %)int
--|(% style="width:172px" %)Long|(% style="width:204px" %)xsd.long|(% style="width:189px" %)System.Int64|(% style="width:342px" %)long
--|(% style="width:172px" %)Short|(% style="width:204px" %)xsd:short|(% style="width:189px" %)System.Int16|(% style="width:342px" %)short
--|(% style="width:172px" %)Decimal|(% style="width:204px" %)xsd:decimal|(% style="width:189px" %)System.Decimal|(% style="width:342px" %)java.math.BigDecim al
--|(% style="width:172px" %)Float|(% style="width:204px" %)xsd:float|(% style="width:189px" %)System.Single|(% style="width:342px" %)float
--|(% style="width:172px" %)Double|(% style="width:204px" %)xsd:double|(% style="width:189px" %)System.Double|(% style="width:342px" %)double
--|(% style="width:172px" %)Boolean|(% style="width:204px" %)xsd:boolean|(% style="width:189px" %)System.Boolean|(% style="width:342px" %)boolean
--|(% style="width:172px" %)URI|(% style="width:204px" %)xsd:anyURI|(% style="width:189px" %)System.Uri|(% style="width:342px" %)Java.net.URI or java.lang.String
--|(% style="width:172px" %)DateTime|(% style="width:204px" %)xsd:dateTime|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
--|(% style="width:172px" %)Time|(% style="width:204px" %)xsd:time|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
--|(% style="width:172px" %)GregorianYear|(% style="width:204px" %)xsd:gYear|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
--|(% style="width:172px" %)GregorianMonth|(% style="width:204px" %)xsd:gYearMonth|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
--|(% style="width:172px" %)GregorianDay|(% style="width:204px" %)xsd:date|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
--|(% style="width:172px" %)(((
--Day, MonthDay, Month
--)))|(% style="width:204px" %)xsd:g*|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
--|(% style="width:172px" %)Duration|(% style="width:204px" %)xsd:duration |(% style="width:189px" %)System.TimeSpa|(% style="width:342px" %)javax.xml.datatype
--|(% style="width:172px" %) |(% style="width:204px" %) |(% style="width:189px" %)n|(% style="width:342px" %).Duration
++|String|xsd:string|System.String|java.lang.String
++|Big Integer|xsd:integer|System.Decimal|java.math.BigInteg er
++|Integer|xsd:int|System.Int32|int
++|Long|xsd.long|System.Int64|long
++|Short|xsd:short|System.Int16|short
++|Decimal|xsd:decimal|System.Decimal|java.math.BigDecim al
++|Float|xsd:float|System.Single|float
++|Double|xsd:double|System.Double|double
++|Boolean|xsd:boolean|System.Boolean|boolean
++|URI|xsd:anyURI|System.Uri|Java.net.URI or java.lang.String
++|DateTime|xsd:dateTime|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
++|Time|xsd:time|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
++|GregorianYear|xsd:gYear|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
++|GregorianMont h|xsd:gYearMont h|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
++|GregorianDay|xsd:date|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
++|(((
++Day,
++MonthDay, Month
++)))|xsd:g*|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
++|Duration|xsd:duration |System.TimeSpa|javax.xml.datatype
++|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|(((
++**Java Data Type**
++
++**~ **
++)))
++| | |n|.Duration
++
  There are also a number of SDMX-ML data types which do not have these direct correspondences, often because they are composite representations or restrictions of a broader data type. For most of these, there are simple types which can be referenced from the SDMX schemas, for others a derived simple type will be necessary:
  * AlphaNumeric (common:AlphaNumericType, string which only allows A-z and 0-9)
@@ -325,7 +325,7 @@
  * ExclusiveValueRange (xs:decimal with the minValue and maxValue facets supplying the bounds)
  * Incremental (xs:decimal with a specified interval; the interval is typically enforced outside of the XML validation)
  * TimeRange (common:TimeRangeType, start DateTime + Duration,)
--* ObservationalTimePeriod (common: ObservationalTimePeriodType, a union of StandardTimePeriod and TimeRange).
++* ObservationalTimePeriod (common: ObservationalTimePeriodType,  a union of StandardTimePeriod and TimeRange).
  * StandardTimePeriod (common: StandardTimePeriodType, a union of BasicTimePeriod and TimeRange).
  * BasicTimePeriod (common: BasicTimePeriodType, a union of GregorianTimePeriod and DateTime)
  * GregorianTimePeriod (common:GregorianTimePeriodType, a union of GregorianYear, GregorianMonth, and GregorianDay)
@@ -340,8 +340,10 @@
  * KeyValues (common:DataKeyType)
  * IdentifiableReference (types for each identifiable object)
  * DataSetReference (common:DataSetReferenceType)
--* AttachmentConstraintReference (common:AttachmentConstraintReferenceType)
++* AttachmentConstraintReference
++(common:AttachmentConstraintReferenceType)
++
  Data types also have a set of facets:
  * isSequence = true | false (indicates a sequentially increasing value)
@@ -363,7 +363,7 @@
  == 4.2 Time and Time Format ==
--=== 4.2.1 Introduction ===
++==== 4.2.1 Introduction  ====
  First, it is important to recognize that most observation times are a period. SDMX specifies precisely how Time is handled.
@@ -371,47 +371,50 @@
  The hierarchy of time formats is as follows (**bold** indicates a category which is made up of multiple formats, //italic// indicates a distinct format):
--* **Observational Time Period**
--** **Standard Time Period**
--*** **Basic Time Period**
--**** **Gregorian Time Period**
--**** //Date Time//
--*** **Reporting Time Period**
--** //Time Range//
++* **Observational Time Period **o **Standard Time Period**
++                                                        §    **Basic Time Period**
++
++* **Gregorian Time Period**
++* //Date Time//
++
++§   **Reporting Time Period **o //Time Range//
++
  The details of these time period categories and of the distinct formats which make them up are detailed in the sections to follow.
--=== 4.2.2 Observational Time Period ===
++==== 4.2.2 Observational Time Period ====
  This is the superset of all time representations in SDMX. This allows for time to be expressed as any of the allowable formats.
--=== 4.2.3 Standard Time Period ===
++==== 4.2.3 Standard Time Period ====
  This is the superset of any predefined time period or a distinct point in time. A time period consists of a distinct start and end point. If the start and end of a period are expressed as date instead of a complete date time, then it is implied that the start of the period is the beginning of the start day (i.e. 00:00:00) and the end of the period is the end of the end day (i.e. 23:59:59).
--=== 4.2.4 Gregorian Time Period ===
++==== 4.2.4 Gregorian Time Period ====
  A Gregorian time period is always represented by a Gregorian year, year-month, or day. These are all based on ISO 8601 dates. The representation in SDMX-ML messages and the period covered by each of the Gregorian time periods are as follows:
--**Gregorian Year:**
++**Gregorian Year:**
++
  Representation: xs:gYear (YYYY)
--Period: the start of January 1 to the end of December 31
--**Gregorian Year Month**:
++Period: the start of January 1 to the end of December 31 **Gregorian Year Month**:
++
  Representation: xs:gYearMonth (YYYY-MM)
--Period: the start of the first day of the month to end of the last day of the month
--**Gregorian Day**:
++Period: the start of the first day of the month to end of the last day of the month **Gregorian Day**:
++
  Representation: xs:date (YYYY-MM-DD)
++
  Period: the start of the day (00:00:00) to the end of the day (23:59:59)
--=== 4.2.5 Date Time ===
++==== 4.2.5 Date Time ====
  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.
--Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
++Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[^^~[1~]^^>>path:#_ftn1]]
--=== 4.2.6 Standard Reporting Period ===
++==== 4.2.6 Standard Reporting Period ====
  Standard reporting periods are periods of time in relation to a reporting year. Each of these standard reporting periods has a duration (based on the ISO 8601 definition) associated with it. The general format of a reporting period is as follows:
@@ -418,52 +418,75 @@
  [REPORTING_YEAR]-[PERIOD_INDICATOR][PERIOD_VALUE]
  Where:
++
  REPORTING_YEAR represents the reporting year as four digits (YYYY) PERIOD_INDICATOR identifies the type of period which determines the duration of the period
++
  PERIOD_VALUE indicates the actual period within the year
  The following section details each of the standard reporting periods defined in SDMX:
--**Reporting Year**:
--Period Indicator: A
++**Reporting Year**:
++
++                           Period Indicator: A
++
  Period Duration: P1Y (one year)
++
  Limit per year: 1
--Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1)
--**Reporting Semester:**
--Period Indicator: S
++Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1) **Reporting Semester:**
++
++                           Period Indicator: S
++
  Period Duration: P6M (six months)
++
  Limit per year: 2
--Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2)
--**Reporting Trimester:**
--Period Indicator: T
++Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2) **Reporting Trimester:**
++
++                           Period Indicator: T
++
  Period Duration: P4M (four months)
++
  Limit per year: 3
--Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3)
--**Reporting Quarter:**
--Period Indicator: Q
++Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3) **Reporting Quarter:**
++
++                           Period Indicator: Q
++
  Period Duration: P3M (three months)
++
  Limit per year: 4
--Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4)
--**Reporting Month**:
++Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4) **Reporting Month**:
++
  Period Indicator: M
++
  Period Duration: P1M (one month)
++
  Limit per year: 1
++
  Representation: common:ReportingMonthType (YYYY-Mmm, e.g. 2000-M12) Notes: The reporting month 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.
  **Reporting Week**:
++
  Period Indicator: W
++
  Period Duration: P7D (seven days)
++
  Limit per year: 53
++
  Representation: common:ReportingWeekType (YYYY-Www, e.g. 2000-W53)
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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.
++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.
++
  **Reporting Day**:
++
  Period Indicator: D
++
  Period Duration: P1D (one day)
++
  Limit per year: 366
++
  Representation: common:ReportingDayType (YYYY-Dddd, e.g. 2000-D366) Notes: There are either 365 or 366 days in a reporting year, depending on whether the reporting year includes leap day (February 29). The reporting day is always represented as three digits, therefore 1-99 are 0 padded (e.g. 001).
  This allows the values to be sorted chronologically using textual sorting methods.
@@ -474,109 +474,143 @@
  Since the duration and the reporting year start day are known for any reporting period, it is possible to relate any reporting period to a distinct calendar period. The actual Gregorian calendar period covered by the reporting period can be computed as follows (based on the standard format of [REPROTING_YEAR][PERIOD_INDICATOR][PERIOD_VALUE] and the reporting year start day as [REPORTING_YEAR_START_DAY]):
--**~1. Determine [REPORTING_YEAR_BASE]:**
++1. **Determine [REPORTING_YEAR_BASE]:**
++
  Combine [REPORTING_YEAR] of the reporting period value (YYYY) with [REPORTING_YEAR_START_DAY] (MM-DD) to get a date (YYYY-MM-DD).
++
  This is the [REPORTING_YEAR_START_DATE]
--**a) If the [PERIOD_INDICATOR] is W:
--~1. If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
++
++**a) If the [PERIOD_INDICATOR] is W:**
++
++1.
++11.
++111.
++1111. **If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
++
  Add^^3^^ (P3D, P2D, or P1D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE].
--2. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
++1.
++11.
++111.
++1111. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
++
  Add^^3^^ (P0D, -P1D, -P2D, or -P3D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE].
--b) **Else:**
--The [REPORTING_YEAR_START_DATE] is the [REPORTING_YEAR_BASE]
--**2. Determine [PERIOD_DURATION]:**
++b) **Else:**
--a) If the [PERIOD_INDICATOR] is A, the [PERIOD_DURATION] is P1Y.
--b) If the [PERIOD_INDICATOR] is S, the [PERIOD_DURATION] is P6M.
--c) If the [PERIOD_INDICATOR] is T, the [PERIOD_DURATION] is P4M.
--d) If the [PERIOD_INDICATOR] is Q, the [PERIOD_DURATION] is P3M.
--e) If the [PERIOD_INDICATOR] is M, the [PERIOD_DURATION] is P1M.
--f) If the [PERIOD_INDICATOR] is W, the [PERIOD_DURATION] is P7D.
--g) If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D.
++The [REPORTING_YEAR_START_DATE] is the [REPORTING_YEAR_BASE].
--**3. Determine [PERIOD_START]:**
--Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
++1. **Determine [PERIOD_DURATION]:**
++11.
++111. If the [PERIOD_INDICATOR] is A, the [PERIOD_DURATION] is P1Y.
++111. If the [PERIOD_INDICATOR] is S, the [PERIOD_DURATION] is P6M.
++111. If the [PERIOD_INDICATOR] is T, the [PERIOD_DURATION] is P4M.
++111. If the [PERIOD_INDICATOR] is Q, the [PERIOD_DURATION] is P3M.
++111. If the [PERIOD_INDICATOR] is M, the [PERIOD_DURATION] is P1M.
++111. If the [PERIOD_INDICATOR] is W, the [PERIOD_DURATION] is P7D.
++111. If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D.
++1. **Determine [PERIOD_START]:**
--**4. Determine the [PERIOD_END]:**
++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].
++
++1. **Determine the [PERIOD_END]:**
++
  Multiply the [PERIOD_VALUE] by the [PERIOD_DURATION]. Add^^3^^ this to the [REPORTING_YEAR_BASE] add^^3^^ -P1D. The result is the [PERIOD_END].
  For all of these ranges, the bounds include the beginning of the [PERIOD_START] (i.e. 00:00:00) and the end of the [PERIOD_END] (i.e. 23:59:59).
--**Examples:**
++**Examples: **
  **2010-Q2, REPORTING_YEAR_START_DAY = ~-~-07-01 (July 1)**
++
  ~1. [REPORTING_YEAR_START_DATE] = 2010-07-01
++
  b) [REPORTING_YEAR_BASE] = 2010-07-01
--[PERIOD_DURATION] = P3M
--(2-1) * P3M = P3M
++
++1. [PERIOD_DURATION] = P3M
++1. (2-1) * P3M = P3M
++
 -07-01 + P3M = 2010-10-01
++
  [PERIOD_START] = 2010-10-01
++
 . 2 * P3M = P6M
++
 -07-01 + P6M = 2010-13-01 = 2011-01-01
++
 -01-01 + -P1D = 2010-12-31
++
  [PERIOD_END] = 2011-12-31
  The actual calendar range covered by 2010-Q2 (assuming the reporting year begins July 1) is 2010-10-01T00:00:00/2010-12-31T23:59:59
  **2011-W36, REPORTING_YEAR_START_DAY = ~-~-07-01 (July 1)**
++
  ~1. [REPORTING_YEAR_START_DATE] = 2010-07-01
++
  a) 2011-07-01 = Friday
++
 -07-01 + P3D = 2011-07-04
++
  [REPORTING_YEAR_BASE] = 2011-07-04
--2. [PERIOD_DURATION] = P7D
--3. (36-1) * P7D = P245D
++
++1. [PERIOD_DURATION] = P7D
++1. (36-1) * P7D = P245D
++
 -07-04 + P245D = 2012-03-05
++
  [PERIOD_START] = 2012-03-05
++
 . 36 * P7D = P252D
++
 -07-04 + P252D =2012-03-12
++
 -03-12 + -P1D = 2012-03-11
++
  [PERIOD_END] = 2012-03-11
  The actual calendar range covered by 2011-W36 (assuming the reporting year begins July 1) is 2012-03-05T00:00:00/2012-03-11T23:59:59
--=== 4.2.7 Distinct Range ===
++==== 4.2.7 Distinct Range ====
  In the case that the reporting period does not fit into one of the prescribe periods above, a distinct time range can be used. The value of these ranges is based on the ISO 8601 time interval format of start/duration. Start can be expressed as either an ISO 8601 date or a date-time, and duration is expressed as an ISO 8601 duration. However, the duration can only be postive.
--=== 4.2.8 Time Format ===
++==== 4.2.8 Time Format ====
--In version 2.0 of SDMX there is a recommendation to use the time format attribute to gives additional information on the way time is represented in the message. Following an appraisal of its usefulness this is no longer required. However, it is still possible, if required , to include the time format attribute in SDMX-ML.
++In version 2.0 of SDMX there is a recommendation to use the time format attribute to gives additional information on the way time is represented in the message. Following an appraisal of its usefulness this is no longer required. However, it is still possible, if required , to include the time format attribute in SDMX-ML.
--(% style="width:716.835px" %)
--|(% style="width:197px" %)**Code**|(% style="width:517px" %)**Format**
--|(% style="width:197px" %)**OTP**|(% style="width:517px" %)Observational Time Period: Superset of all SDMX time formats (Gregorian Time Period, Reporting Time Period, and Time Range)
--|(% style="width:197px" %)**STP**|(% style="width:517px" %)Standard Time Period: Superset of Gregorian and Reporting Time Periods
--|(% style="width:197px" %)**GTP**|(% style="width:517px" %)Superset of all Gregorian Time Periods and date-time
--|(% style="width:197px" %)**RTP**|(% style="width:517px" %)Superset of all Reporting Time Periods
--|(% style="width:197px" %)**TR**|(% style="width:517px" %)Time Range: Start time and duration (YYYY-MMDD(Thh:mm:ss)?/<duration>)
--|(% style="width:197px" %)**GY**|(% style="width:517px" %)Gregorian Year (YYYY)
--|(% style="width:197px" %)**GTM**|(% style="width:517px" %)Gregorian Year Month (YYYY-MM)
--|(% style="width:197px" %)**GD**|(% style="width:517px" %)Gregorian Day (YYYY-MM-DD)
--|(% style="width:197px" %)**DT**|(% style="width:517px" %)Distinct Point: date-time (YYYY-MM-DDThh:mm:ss)
--|(% style="width:197px" %)**RY**|(% style="width:517px" %)Reporting Year (YYYY-A1)
--|(% style="width:197px" %)**RS**|(% style="width:517px" %)Reporting Semester (YYYY-Ss)
--|(% style="width:197px" %)**RT**|(% style="width:517px" %)Reporting Trimester (YYYY-Tt)
--|(% style="width:197px" %)**RQ**|(% style="width:517px" %)Reporting Quarter (YYYY-Qq)
--|(% style="width:197px" %)**RM**|(% style="width:517px" %)Reporting Month (YYYY-Mmm)
--|(% style="width:197px" %)**Code**|(% style="width:517px" %)**Format**
--|(% style="width:197px" %)**RW**|(% style="width:517px" %)Reporting Week (YYYY-Www)
--|(% style="width:197px" %)**RD**|(% style="width:517px" %)Reporting Day (YYYY-Dddd)
++|**Code**|**Format**
++|**OTP**|Observational Time Period: Superset of all SDMX time formats (Gregorian Time Period, Reporting Time Period, and Time Range)
++|**STP**|Standard Time Period: Superset of Gregorian and Reporting Time Periods
++|**GTP**|Superset of all Gregorian Time Periods and date-time
++|**RTP**|Superset of all Reporting Time Periods
++|**TR**|Time Range: Start time and duration (YYYY-MMDD(Thh:mm:ss)?/<duration>)
++|**GY**|Gregorian Year (YYYY)
++|**GTM**|Gregorian Year Month (YYYY-MM)
++|**GD**|Gregorian Day (YYYY-MM-DD)
++|**DT**|Distinct Point: date-time (YYYY-MM-DDThh:mm:ss)
++|**RY**|Reporting Year (YYYY-A1)
++|**RS**|Reporting Semester (YYYY-Ss)
++|**RT**|Reporting Trimester (YYYY-Tt)
++|**RQ**|Reporting Quarter (YYYY-Qq)
++|**RM**|Reporting Month (YYYY-Mmm)
++|**Code**|**Format**
++|**RW**|Reporting Week (YYYY-Www)
++|**RD**|Reporting Day (YYYY-Dddd)
--**Table 1: SDMX-ML Time Format Codes**
++  **Table 1: SDMX-ML Time Format Codes**
--=== 4.2.9 Transformation between SDMX-ML and SDMX-EDI ===
++==== 4.2.9 Transformation between SDMX-ML and SDMX-EDI ====
  When converting SDMX-ML data structure definitions to SDMX-EDI data structure definitions, only the identifier of the time format attribute will be retained. The representation of the attribute will be converted from the SDMX-ML format to the fixed SDMX-EDI code list. If the SDMX-ML data structure definition does not define a time format attribute, then one will be automatically created with the identifier "TIME_FORMAT".
--When converting SDMX-ML data to SDMX-EDI, the source time format attribute will be irrelevant. Since the SDMX-ML time representation types are not ambiguous, the target time format can be determined from the source time value directly. For example, if the SDMX-ML time is 2000-Q2 the SDMX-EDI format will always be 608/708 (depending on whether the target series contains one observation or a range of observations).
++When converting SDMX-ML data to SDMX-EDI, the source time format attribute will be irrelevant. Since the SDMX-ML time representation types are not ambiguous, the target time format can be determined from the source time value directly. For example, if the SDMX-ML time is 2000-Q2 the SDMX-EDI format will always be 608/708 (depending on whether the target series contains one observation or a range of observations)
  When converting a data structure definition originating in SDMX-EDI, the time format attribute should be ignored, as it serves no purpose in SDMX-ML.
  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.
--=== 4.2.10 Time Zones ===
++====                 4.2.10    Time Zones ====
  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):
@@ -597,39 +597,40 @@
  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.
--=== 4.2.11 Representing Time Spans Elsewhere ===
++====                 4.2.11    Representing Time Spans Elsewhere ====
  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:
--<Series REF_PERIODStartTime="2000-01-01T00:00:00" REF_PERIOD="P2M"/>
++  <Series REF_PERIODStartTime="2000-01-01T00:00:00" REF_PERIOD="P2M"/>
  can now be represented with this:
  <Series REF_PERIOD="2000-01-01T00:00:00/P2M"/>
--=== 4.2.12 Notes on Formats ===
++====                 4.2.12    Notes on Formats ====
  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.
--=== 4.2.13 Effect on Time Ranges ===
++====                 4.2.13    Effect on Time Ranges ====
  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.
--=== 4.2.14 Time in Query Messages ===
++==== 4.2.14 Time in Query Messages ====
  When querying for time values, the value of a time parameter can be provided as any of the Observational Time Period formats and must be paired with an operator. In addition, an explicit value for the reporting year start day can be provided, or this can be set to "Any". This section will detail how systems processing query messages should interpret these parameters.
  Fundamental to processing a time value parameter in a query message is understanding that all time periods should be handled as a distinct range of time. Since the time parameter in the query is paired with an operator, this is also effectively represents a distinct range of time. Therefore, a system processing the query must simply match the data where the time period for requested parameter is encompassed by the time period resulting from value of the query parameter. The following table details how the operators should be interpreted for any time period provided as a parameter.
--(% style="width:1024.29px" %)
--|(% style="width:238px" %)**Operator**|(% style="width:782px" %)**Rule**
--|(% style="width:238px" %)Greater Than|(% style="width:782px" %)Any data after the last moment of the period
--|(% style="width:238px" %)Less Than|(% style="width:782px" %)Any data before the first moment of the period
--|(% style="width:238px" %)Greater Than or Equal To|(% style="width:782px" %)(((
--Any data on or after the first moment of the period
++|**Operator**|**Rule**
++|Greater Than|Any data after the last moment of the period
++|Less Than|Any data before the first moment of the period
++|Greater Than or Equal To|(((
++Any data on or after the first moment of
++
++the period
  )))
--|(% style="width:238px" %)Less Than or Equal To|(% style="width:782px" %)Any data on or before the last moment of the period
--|(% style="width:238px" %)Equal To|(% style="width:782px" %)Any data which falls on or after the first moment of the period and before or on the last moment of the period
++|Less Than or Equal To|Any data on or before the last moment of the period
++|Equal To|Any data which falls on or after the first moment of the period and before or on the last moment of the period
  Reporting Time Periods as query parameters are handled based on whether the value of the reportingYearStartDay XML attribute is an explicit month and day or "Any":
@@ -642,7 +642,9 @@
  **Examples:**
  **Gregorian Period**
++
  Query Parameter: Greater than 2010
++
  Literal Interpretation: Any data where the start period occurs after 2010-1231T23:59:59.
  Example Matches:
@@ -660,11 +660,15 @@
  * 2010-D185 or later (reporting year start day ~-~-07-01 or later)
  **Reporting Period with explicit start day**
++
  Query Parameter: Greater than or equal to 2009-Q3, reporting year start day = "-07-01"
++
  Literal Interpretation: Any data where the start period occurs on after 2010-0101T00:00:00 (Note that in this case 2009-Q3 is converted to the explicit date range of 2010-01-01/2010-03-31 because of the reporting year start day value). Example Matches: Same as previous example
  **Reporting Period with "Any" start day**
++
  Query Parameter: Greater than or equal to 2010-Q3, reporting year start day = "Any"
++
  Literal Interpretation: Any data with a reporting period where the start period is on or after the start period of 2010-Q3 for the same reporting year start day, or and data where the start period is on or after 2010-07-01. Example Matches:
  * 2011 or later
@@ -676,12 +676,15 @@
  * 2010-T3 (any reporting year start day)
  * 2010-Q3 or later (any reporting year start day)
  * 2010-M07 or later (any reporting year start day)
--* 2010-W27 or later (reporting year start day ~-~-01-01){{footnote}}2010-Q3 (with a reporting year start day of --01-01) starts on 2010-07-01. This is day 4 of week 26, therefore the first week matched is week 27.{{/footnote}}  2010-D182 or later (reporting year start day ~-~-01-01)
--* 2010-W28 or later (reporting year start day ~-~-07-01){{footnote}}2010-Q3 (with a reporting year start day of --07-01) starts on 2011-01-01. This is day 6 of week 27, therefore the first week matched is week 28.{{/footnote}}
--* 2010-D185 or later (reporting year start day ~-~-07-01)
++* 2010-W27 or later (reporting year start day ~-~-01-01)^^4^^  2010-D182 or later (reporting year start day ~-~-01-01)
++* 2010-W28 or later (reporting year start day ~-~-07-01)^^5^^
--== 4.3 Structural Metadata Querying Best Practices ==
++^^4^^ 2010-Q3 (with a reporting year start day of ~-~-01-01) starts on 2010-07-01. This is day 4 of week 26, therefore the first week matched is week 27.
++ 2010-D185 or later (reporting year start day ~-~-07-01)
++
++== 4.3 Structural Metadata Querying Best Practices  ==
++
  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.
  Any structural metadata object which contains a reference to an object can be queried based on that reference. For example, a categorisation references both a category and the object is it categorising. As this is the case, one can query for categorisations which categorise a particular object or which categorise against a particular category or category scheme. This mechanism should be used when the referenced object is known.
@@ -688,7 +688,7 @@
  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.
--== 4.4 Versioning and External Referencing ==
++== 4.4 Versioning and External Referencing  ==
  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”.
@@ -696,6 +696,8 @@
  This mechanism is an “early binding” one – everything with a versioned identity is a known quantity, and will not change. It is worth pointing out that in some cases relationships are essentially one-way references: an illustrative case is that of Categories. While a Category may be referenced by many dataflows and metadata flows, the addition of more references from flow objects does not version the Category. This is because the flows are not properties of the Categories – they merely make references to it. If the name of a Category changed, or its subCategories changed, then versioning would be necessary.
++^^5^^ 2010-Q3 (with a reporting year start day of ~-~-07-01) starts on 2011-01-01. This is day 6 of week 27, therefore the first week matched is week 28.
++
  Versioning operates at the level of versionable and maintainable objects in the SDMX information model. If any of the children of objects at these levels change, then the objects themselves are versioned.
  One area which is much impacted by this versioning scheme is the ability to reference external objects. With the many dependencies within the various structural objects in SDMX, it is useful to have a scheme for external referencing. This is done at the level of maintainable objects (DSDs, code lists, concept schemes, etc.) In an SDMX-ML Structure Message, whenever an “isExternalReference” attribute is set to true, then the application must resolve the address provided in the associated “uri” attribute and use the SDMX-ML Structure Message stored at that location for the full definition of the object in question. Alternately, if a registry “urn” attribute has been provided, the registry can be used to supply the full details of the object.
@@ -718,13 +718,13 @@
  [[image:1747836776649-282.jpeg]]
--**Figure 1: Schematic of the Metadata Structure Definition**
++1. **1: Schematic of the Metadata Structure Definition**
  The MSD comprises the specification of the object types to which metadata can be reported in a Metadata Set (Metadata Target(s)), and the Report Structure(s) comprising the Metadata Attributes that identify the Concept for which metadata may be reported in the Metadata Set. Importantly, one Report Structure references the Metadata Target for which it is relevant. One Report Structure can reference many Metadata Target i.e. the same Report Structure can be used for different target objects.
  [[image:1747836776655-364.jpeg]]
--**Figure 2: Example MSD showing Metadata Targets**
++1. **2: Example MSD showing Metadata Targets**
  Note that the SDMX-ML schemas have explicit XML elements for each identifiable object type because identifying, for instance, a Maintainable Object has different properties from an Identifiable Object which must also include the agencyId, version, and id of the Maintainable Object in which it resides.
@@ -734,10 +734,8 @@
  [[image:1747836776658-510.jpeg]]
--**Figure 3: Example MSD showing specification of three Metadata Attributes**
++**Figure 3: Example MSD showing specification of three Metadata Attributes **This example shows the following hierarchy of Metadata Attributes:
--This example shows the following hierarchy of Metadata Attributes:
--
  Source – this is presentational and no metadata is expected to be reported at this level
  * Source Type
@@ -749,9 +749,12 @@
  [[image:1747836776677-246.jpeg]]
--**Figure 4: Example Metadata Set **This example shows:
++  **Figure 4: Example Metadata Set **This example shows:
--1. The reference to the MSD, Metadata Report, and Metadata Target (MetadataTargetValue)
++1. The reference to the MSD, Metadata Report, and Metadata Target
++
++(MetadataTargetValue)
++
 . The reported metadata attributes (AttributeValueSet)
  = 6 Maintenance Agencies =
@@ -772,7 +772,7 @@
  [[image:1747836776680-229.jpeg]]
--**Figure 5: Example of Hierarchic Structure of Agencies**
++  **Figure 5: Example of Hierarchic Structure of Agencies**
  Each agency is identified by its full hierarchy excluding SDMX.
@@ -808,11 +808,10 @@
  The Information Model for this is shown below:
--[[image:1747855024745-946.png]]
--**Figure 8: Information Model Extract for Concept Role**
++  **Figure 8: Information Model Extract for Concept Role**
--It is possible to specify zero or more concept roles for a Dimension, Measure Dimension and Data Attribute (but not the ReportingYearStartDay). The Time Dimension, Primary Measure, and the Attribute ReportingYearStartDay have explicitly defined roles and cannot be further specified with additional concept roles.
++It is possible to specify zero or more concept roles for a Dimension, Measure Dimension and Data Attribute (but not the ReportingYearStartDay). The Time Dimension, Primary Measure, and the  Attribute ReportingYearStartDay have explicitly defined roles and cannot be further specified with additional concept roles.
  == 7.3 Technical Mechanism ==
@@ -830,14 +830,15 @@
  The Cross-Domain Concept Scheme maintained by SDMX contains concept role concepts (FREQ chosen as an example).
--[[image:1747855054559-410.png]]
++[[image:1747836776691-440.jpeg]]
  Whether this is a role or not depends upon the application understanding that FREQ in the Cross-Domain Concept Scheme is a role of Frequency.
  Using a Concept Scheme that is not the Cross-Domain Concept Scheme where it is required to assign a role using the Cross-Domain Concept Scheme. Again FREQ is chosen as the example.
--[[image:1747855075263-887.png]]
++[[image:1747836776693-898.jpeg]]
++
  This explicitly states that this Dimension is playing a role identified by the FREQ concept in the Cross-Domain Concept Scheme. Again the application needs to understand what FREQ in the Cross-Domain Concept Scheme implies in terms of a role.
  This is all that is required for interoperability within a community. The important point is that a community must recognise a specific Agency as having the authority to define concept roles and to maintain these “role” concepts in a concept scheme together with documentation on the meaning of the role and any relevant processing implications. This will then ensure there is interoperability between systems that understand the use of these concepts.
@@ -885,7 +885,7 @@
  == 8.3 Rules for a Content Constraint ==
--=== 8.3.1 Scope of a Content Constraint ===
++=== 8.3.1      Scope of a Content Constraint ===
  A Content Constraint is used specify the content of a data or metadata source in terms of the component values or the keys.
@@ -906,7 +906,7 @@
  ** IdentifiableObject
  * Metadata Attribute
--The “key” is therefore the combination of the Target Objects that are defined for the Metadata Target.
++The “key” is therefore the combination of the Target Objects that are defined for the  Metadata Target.
  For a Constraint based on a DSD the Content Constraint can reference one or more of:
@@ -924,60 +924,60 @@
  In view of the flexibility of constraints attachment, clear rules on their usage are required. These are elaborated below.
--=== 8.3.2 Multiple Content Constraints ===
++=== 8.3.2      Multiple Content Constraints ===
  There can be many Content Constraints for any Constrainable Artefact (e.g. DSD), subject to the following restrictions:
--==== 8.3.2.1 Cube Region ====
++**8.3.2.1 Cube Region**
 . The constraint can contain multiple Member Selections (e.g. Dimension) but:
--1. A specific Member Selection (e.g. Dimension FREQ) can only be contained in one Content Constraint for any one attached object (e.g. a specific DSD or specific Dataflow)
++1. A specific  Member Selection (e.g. Dimension FREQ)  can only be contained in one Content Constraint for any one attached object (e.g. a specific DSD or specific Dataflow)
--==== 8.3.2.2 Key Set ====
++**8.3.2.2 Key Set**
--Key Sets will be processed in the order they appear in the Constraint and wildcards can be used (e.g. any key position not reference explicitly is deemed to be “all values”). As the Key Sets can be “included” or “excluded” it is recommended that Key Sets with wildcards are declared before KeySets with specific series keys. This will minimize the risk that keys are inadvertently included or excluded.
++Key Sets will be processed in the order they appear in the Constraint and wildcards can be used (e.g. any key position not reference explicitly is deemed to be “all values”). As the Key Sets can be “included” or “excluded” it is recommended that Key Sets with wildcards are declared before KeySets with specific series keys. This will minimize the risk that keys are inadvertently included or excluded.
--=== 8.3.3 Inheritance of a Content Constraint ===
++=== 8.3.3      Inheritance of a Content Constraint ===
--==== 8.3.3.1 Attachment levels of a Content Constraint ====
++**8.3.3.1 Attachment levels of a Content Constraint**
  There are three levels of constraint attachment for which these inheritance rules apply:
--* DSD/MSD – top level
--** Dataflow/Metadataflow – second level
--*** Provision Agreement – third level
++ DSD/MSD – top level o Dataflow/Metadataflow – second level
++§ Provision Agreement – third level
++
  Note that these rules do not apply to the Simple Datasoucre or Queryable Datasource: the Content Constraint(s) attached to these artefacts are resolved for this artefact only and do not take into account Constraints attached to other artefacts (e.g. Provision Agreement. Dataflow, DSD).
  It is not necessary for a Content Constraint to be attached to higher level artifact. e.g. it is valid to have a Content Constraint for a Provision Agreement where there are no constraints attached the relevant dataflow or DSD.
--==== 8.3.3.2 Cascade rules for processing Constraints ====
++**8.3.3.2 Cascade rules for processing Constraints**
  The processing of the constraints on either Dataflow/Metadataflow or Provision Agreement must take into account the constraints declared at higher levels. The rules for the lower level constraints (attached to Dataflow/ Metadataflow and Provision Agreement) are detailed below.
  Note that there can be a situation where a constraint is specified at a lower level before a constraint is specified at a higher level. Therefore, it is possible that a higher level constraint makes a lower level constraint invalid. SDMX makes no rules on how such a conflict should be handled when processing the constraint for attachment. However, the cascade rules on evaluating constraints for usage are clear - the higher level constraint takes precedence in any conflicts that result in a less restrictive specification at the lower level.
--==== 8.3.3.3 Cube Region ====
++**8.3.3.3 Cube Region**
 . It is not necessary to have a constraint on the higher level artifact (e.g. DSD referenced by the Dataflow) but if there is such a constraint at the higher level(s) then:
--a. The lower level constraint cannot be less restrictive than the constraint specified for the same Member Selection (e.g. Dimension) at the next higher level which constraints that Member Selection (e.g. if the Dimension FREQ is constrained to A, Q in a DSD then the constraint at the Dataflow or Provision Agreement cannot be A, Q, M or even just M – it can only further constrain A,Q).
--b. The constraint at the lower level for any one Member Selection further constrains the content for the same Member Selection at the higher level(s).
++11. The lower level constraint cannot be less restrictive than the constraint specified for the same Member Selection (e.g. Dimension) at the next higher level which constraints that Member Selection (e.g. if the Dimension FREQ is constrained to A, Q in a DSD then the constraint at the Dataflow or Provision Agreement cannot be A, Q, M or even just M – it can only further constrain A,Q).
++11. The constraint at the lower level for any one Member Selection further constrains the content for the same Member Selection at the higher level(s).
 . Any Member Selection which is not referenced in a Content Constraint is deemed to be constrained according to the Content Constraint specified at the next higher level which constraints that Member Selection.
 . If there is a conflict when resolving the constraint in terms of a lower-level constraint being less restrictive than a higher-level constraint then the constraint at the higher-level is used.
  Note that it is possible for a Content Constraint at a higher level to constrain, say, four Dimensions in a single constraint, and a Content Constraint at a lower level to constrain the same four in two, three, or four Content Constraints.
--==== 8.3.3.4 Key Set ====
++**8.3.3.4 Key Set**
 . It is not necessary to have a constraint on the higher level artefact (e.g. DSD referenced by the Dataflow) but if there is such a constraint at the higher level(s) then:
--a. The lower level constraint cannot be less restrictive than the constraint specified at the higher level.
--b. The constraint at the lower level for any one Member Selection further constrains the keys specified at the higher level(s).
++11. The lower level constraint cannot be less restrictive than the constraint specified at the higher level.
++11. The constraint at the lower level for any one Member Selection further constrains the keys specified at the higher level(s).
 . Any Member Selection which is not referenced in a Content Constraint is deemed to be constrained according to the Content Constraint specified at the next higher level which constraints that Member Selection.
 . If there is a conflict when resolving the keys in the constraint at two levels, in terms of a lower-level constraint being less restrictive than a higher-level constraint, then the offending keys specified at the lower level are not deemed part of the constraint.
  Note that a Key in a Key Set can have wildcarded Components. For instance the constraint may simply constrain the Dimension FREQ to “A”, and all keys where the FREQ=A are therefore valid.
--The following logic explains how the inheritance mechanism works. Note that this is conceptual logic and actual systems may differ in the way this is implemented.
++The following logic explains how the inheritance mechanism works. Note that this is conceptual logic and actual systems may differ in the way this is implemented.
 . Determine all possible keys that are valid at the higher level.
 . These keys are deemed to be inherited by the lower level constrained object, subject to the constraints specified at the lower level.
@@ -985,11 +985,11 @@
 . At the lower level inherit all keys that match with the higher level constraint.
 . If there are keys in the lower level constraint that are not inherited then the key is invalid (i.e. it is less restrictive).
--=== 8.3.4 Constraints Examples ===
++**8.3.4       Constraints Examples**
  The following scenario is used.
--__DSD__
++=== DSD ===
  This contains the following Dimensions:
@@ -998,45 +998,114 @@
  * AGE – Age
  * CAS – Current Activity Status
--In the DSD common code lists are used and the requirement is to restrict these at various levels to specify the actual code that are valid for the object to which the Content Constraint is attached.
++In the DSD common code lists are used and the requirement is to restrict these at various levels to specify the actual code that are valid for the object to which the Content Constraint is attached.
--[[image:1747855493531-357.png]]
--**Figure 10: Example Scenario for Constraints**
++|(((
++
++)))
++|(((
++
++)))
++
++|(((
++
++)))
++
++|(((
++**Figure**
++)))
++
++|(((
++**10**
++)))
++
++|(((
++**:**
++)))
++
++|(((
++**~ Example Sce**
++)))
++
++|(((
++**nario for Constraints**
++)))
++
++|(((
++**~ **
++)))
++
++
++
  Constraints are declared as follows:
--[[image:1747855462293-368.png]]
--**Figure 11: Example Content Constraints**
++|(((
++
++)))
++|(((
++
++)))
++
++|(((
++
++)))
++
++|(((
++**Figure**
++)))
++
++|(((
++**11**
++)))
++
++|(((
++**:**
++)))
++
++|(((
++**~ Example Content Constraints**
++)))
++
++|(((
++**~ **
++)))
++
++
++
  **Notes:**
--1. AGE is constrained for the DSD and is further restricted for the Dataflow CENSUS_CUBE1.
++1. AGE is constrained for the DSD and is further restricted for the Dataflow
++
++CENSUS_CUBE1.
++
 . The same Constraint applies to both Provision Agreements.
  The cascade rules elaborated above result as follows:
--__DSD__
++DSD
  ~1. Constrained by eliminating code 001 from the code list for the AGE Dimension.
--__Dataflow CENSUS_CUBE1__
++=== Dataflow CENSUS_CUBE1 ===
 . Constrained by restricting the code list for the AGE Dimension to codes 002 and 003(note that this is a more restrictive constraint than that declared for the DSD which specifies all codes except code 001).
 . Restricts the CAS codes to 003 and 004.
--__Dataflow CENSUS_CUBE2__
++=== Dataflow CENSUS_CUBE2 ===
 . Restricts the code list for the CAS Dimension to codes TOT and NAP.
 . Inherits the AGE constraint applied at the level of the DSD.
--__Provision Agreements CENSUS_CUBE1_IT__
++=== Provision Agreements CENSUS_CUBE1_IT  ===
 . Restricts the codes for the GEO Dimension to IT and its children.
--1. Inherits the constraints from Dataflow CENSUS_CUBE1 for the AGE and CAS Dimensions.
++1. Inherits the constraints from Dataflow CENSUS_CUBE1  for the AGE and CAS Dimensions.
--__Provision Agreements CENSUS_CUBE2_IT__
++=== Provision Agreements CENSUS_CUBE2_IT  ===
 . Restricts the codes for the GEO Dimension to IT and its children.
 . Inherits the constraints from Dataflow CENSUS_CUBE2 for the CAS Dimension.
@@ -1044,17 +1044,17 @@
  The constraints are defined as follows:
--__DSD Constraint__
++=== DSD Constraint ===
  [[image:1747836776698-720.jpeg]]
--__Dataflow Constraints__
++=== Dataflow Constraints ===
  [[image:1747836776701-360.jpeg]]
--[[image:1747836776707-834.jpeg]]
++=== [[image:1747836776707-834.jpeg]] ===
--__Provision Agreement Constraint__
++=== Provision Agreement Constraint ===
  [[image:1747836776710-262.jpeg]]
@@ -1066,7 +1066,7 @@
  == 9.2 Groups and Dimension Groups ==
--=== 9.2.1 Issue ===
++===                    9.2.1      Issue ===
  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.
@@ -1079,7 +1079,7 @@
  If the conditions defined in 9.2.1are true then on conversion to a version 2.0 or 1.0 DSD (Key Family) the Component/Attribute.attachmentLevel must be set to “Group” and the Component/Attribute/AttachmentGroup” is used to identify the Group. Note that under rule(1) in 1.2.1 this group will have been defined in the V 2.1 DSD and so will be present in the V 2.0 transformation.
--=== 9.2.3 Data ===
++=== 9.2.3      Data ===
  If the conditions defined in 9.2.1are true then, on conversion from a 2.1 data set to a 2.0 or 1.0 dataset the attribute value will be placed in the relevant <Group>. If these conditions are not true then the attribute value will be placed in the <Series>.
@@ -1091,32 +1091,34 @@
  == 10.1 Introduction ==
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
++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:
--* definition of validation and transformation algorithms, in order to specify how to calculate new data from existing ones;
++* definition of validation and transformation algorithms, in order to specify how to calculate new data  from existing ones;
  * 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);
  * compilation and execution of VTL algorithms, either interpreting the VTL transformations or translating them in whatever other computer language is deemed as appropriate.
--It is important to note that the VTL has its own information model (IM), derived from the Generic Statistical Information Model (GSIM) and described in the VTL User Guide. The VTL IM is designed to be compatible with more standards, like SDMX, DDI (Data Documentation Initiative) and GSIM, and includes the model artefacts that can be manipulated (inputs and/or outputs of transformations, e.g. “Data Set”, “Data Structure”) and the model artefacts that allow the definition of the transformation algorithms (e.g. “Transformation”, “Transformation Scheme”).
++It is important to note that the VTL has its own information model (IM), derived from the Generic Statistical Information Model (GSIM) and described in the VTL User Guide. The VTL IM is designed to be compatible with more standards, like SDMX, DDI (Data Documentation Initiative) and GSIM, and includes the model artefacts that can be manipulated (inputs and/or outputs of transformations, e.g. “Data Set”, “Data Structure”) and the model artefacts that allow the definition of  the transformation algorithms (e.g. “Transformation”, “Transformation Scheme”).
--The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL “Data Set”, which do not correspond one another: as a matter of fact, the VTL “Data Set” maps to the SDMX “Dataflow”, while the SDMX “Dataset” has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL transformations). A SDMX “Dataset”, however, is an instance of a SDMX “Dataflow” and can be the artefact on which the VTL transformations are executed (i.e., the transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
++The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of transformations.  It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL “Data Set”, which do not correspond one another: as a matter of fact, the VTL “Data Set” maps to the SDMX “Dataflow”, while the SDMX “Dataset” has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL transformations). A SDMX “Dataset”, however, is an instance of a SDMX “Dataflow” and can be the artefact on which the VTL transformations are executed (i.e., the transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets).
--The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
++The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable   class which     is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result.
  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.
--== 10.2 References to SDMX artefacts from VTL statements ==
++== 10.2 References to SDMX artefacts from VTL statements  ==
  === 10.2.1 Introduction ===
--The VTL can manipulate SDMX artefacts (or objects) by referencing them through pre-defined conventional names (aliases).
++The VTL can manipulate SDMX artefacts (or objects) by referencing them through pre-defined conventional names (aliases).
  The alias of a SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name.
--In any case, the aliases used in the VTL transformations have to be mapped to the SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL transformations, rulesets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%) to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
++In any case, the aliases used in the VTL transformations have to be mapped to the
--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.
++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.
++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.
++
  The references through the URN and the abbreviated URN are described in the following paragraphs.
  === 10.2.2 References through the URN ===
@@ -1123,15 +1123,15 @@
  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.
--The SDMX URN[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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:^^ ^^
++The SDMX URN[[^^~[7~]^^>>path:#_ftn7]] is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:^^ ^^
--* SDMXprefix
--* SDMX-IM-package-name
--* class-name
--* agency-id
++* SDMXprefix
++* SDMX-IM-package-name
++* class-name
++* agency-id
  * maintainedobject-id
  * maintainedobject-version
--* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
++* container-object-id [[^^~[8~]^^>>path:#_ftn8]]
  * object-id
  The generic structure of the URN is the following:
@@ -1142,7 +1142,7 @@
  The **SDMX prefix** is “urn:sdmx:org”, always the same for all SDMX artefacts.
--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”.
++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”.
  The **class-name** is the name of the SDMX object class which the SDMX object belongs to (e.g., for referencing a dataflow the class-name is “Dataflow”). The VTL can reference SDMX artefacts that belong to the classes ,,Dataflow, Dimension,,,
@@ -1150,13 +1150,13 @@
  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).
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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:
++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:
--* if the artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the Dataflow name (dataflow-id);
--* 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;
--* if the artefact is a Concept, which is not maintainable and belongs to the ConceptScheme maintainable class, ,, ,,the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id) which the artefact belongs to;
--* if the artefact is a ConceptScheme, which is a maintainable class, ,, ,,the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id);
--* if the artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the Codelist name (codelist-id).
++* if the artefact is a ,,Dataflow,,, which is a maintainable class,  the maintainedobject-id is the Dataflow name (dataflow-id);
++* 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;
++* if the artefact is a ,,Concept,,, which is not maintainable and belongs to the ConceptScheme maintainable class, ,, ,,the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id) which the artefact belongs to;
++* if the artefact is a ,,ConceptScheme,,, which is a maintainable class, ,, ,,the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id);
++* if the artefact is a ,,Codelist, ,,which is a maintainable class,  the maintainedobject-id is the Codelist name (codelist-id).
  The **maintainedobject-version** is the version of the maintained object which the artefact belongs to (for example, possible versions are 1.0, 2.1, 3.1.2).
@@ -1164,13 +1164,18 @@
  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:
--* if the artefact is a Dimension, MeasureDimension, TimeDimension, PrimaryMeasure or DataAttribute (the object-id is the name of one of the artefacts above, which are data structure components)
--* if the artefact is a Concept (the object-id is the name of the Concept)
++* if the artefact is a Dimension, MeasureDimension, TimeDimension, PrimaryMeasure or DataAttribute  (the object-id is the name of one of
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[10~]^^>>path:#_ftn10]](%%):
++the artefacts above, which are data structure components)
++* if the artefact is a ,,Concept ,,(the object-id is the name of the ,,Concept,,)
++
++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]]:
++
  ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  <-
--‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’  +
++
++‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’   +
++
  ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0)’
  === 10.2.3 Abbreviation of the URN ===
@@ -1180,50 +1180,52 @@
  The URN can be abbreviated by omitting the parts that are not essential for the identification of the artefact or that can be deduced from other available information, including the context in which the invocation is made. The possible abbreviations are described below.
  * The **SDMXPrefix** can be omitted for all the SDMX objects, because it is a prefixed string (urn:sdmx:org), always the same for SDMX objects.
--* The **SDMX-IM-package-name **can be omitted as well because it can be deduced from the class-name that follows it (the table of the SDMX-IM packages and classes that allows this deduction is in the SDMX 2.1 Standards - Section 5 - Registry Specifications, paragraph 6.2.3). In particular, considering the object classes of the artefacts that VTL can reference, the package is:
--** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,
--** “conceptscheme” for the classes Concept and ConceptScheme
--** “codelist” for the class Codelist.
--* The **class-name** can be omitted as it can be deduced from the VTL invocation. In particular, starting from the VTL class of the invoked artefact (e.g. dataset, component, identifier, measure, attribute, variable, valuedomain), which is known given the syntax of the invoking VTL operator[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[12~]^^>>path:#_ftn12]](%%).
--* 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 TransformationScheme and cannot be omitted if the artefact comes from another agency.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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).
--* 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;
--** 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 SDMX structural definitions;
--** 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;
--** if the referenced artefact is a ConceptScheme, which is a,, ,,maintainable class,,, ,,the maintained object is the conceptScheme-id and obviously cannot be omitted;
--** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted.
++* 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:
++** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,
++** “conceptscheme” for the classes  Concept and ConceptScheme o “codelist” for the class Codelist.
++* 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]].
++* 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).
++* 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;
++** 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
++
++SDMX structural definitions;  o 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;
++
++*
++** if the referenced artefact is a ,,ConceptScheme, ,,which is a,, ,,maintainable class,,, ,,the maintained object is the ,,conceptScheme-id,, and obviously cannot be omitted;
++** if the referenced artefact is a ,,Codelist, ,,which is a maintainable class, the maintainedobject-id is the ,,codelist-id,, and obviously cannot be omitted.
  * 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.,, ,,
  * 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
--* 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 them the object-id is the main identifier of the artefact
++* 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
++them the object-id is the main identifier of the artefact
++
  The simplified object identifier is obtained by omitting all the first part of the URN, including the special characters, till the first part not omitted.
  For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
--‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  :=
--‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’   +
++‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  := ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’   +
++
  ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0)’
--by omitting all the non-essential parts would become simply:
++by omitting all the non-essential parts would become simply:
--DFR := DF1 + DF2
++DFR  :=  DF1 + DF2
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[14~]^^>>path:#_ftn14]](%%):
++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]]:
  ‘urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0)’
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[15~]^^>>path:#_ftn15]](%%):
++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]]:
  CL_FREQ
--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:
++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:
--‘urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0).SECTOR’
++‘urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0).SECTOR’ The corresponding fully abbreviated reference, if made from a transformation scheme belonging to AG, would become simply:
--The corresponding fully abbreviated reference, if made from a transformation scheme belonging to AG, would become simply:
--
  SECTOR
--For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[16~]^^>>path:#_ftn16]](%%):
++For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[^^~[16~]^^>>path:#_ftn16]]:
  ‘DFR(1.0)’ := ‘DF1(1.0)’ [rename SECTOR to SEC]
@@ -1233,7 +1233,7 @@
  ‘urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0).SECTOR’
--The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
++The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
  CS1(1.0).SECTOR
@@ -1255,13 +1255,13 @@
  VTL operators, like the ones for validation and hierarchical roll-up. A “rule” consists in a relationship between Values belonging to some Value Domains or taken by some Variables, for example: (i) when the Country is USA then the Currency is USD; (ii) the Benelux is composed by Belgium, Luxembourg, Netherlands.
--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.
++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.
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[17~]^^>>path:#_ftn17]](%%).
++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]].
--In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called “valueDomain” and “variable” for the Datapoint Rulesets and “ruleValueDomain”, “ruleVariable”, “condValueDomain” “condVariable” for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific ruleset definition statement and cannot be mapped to SDMX.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[18~]^^>>path:#_ftn18]](%%)
++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]]
--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.
++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.
  == 10.3 Mapping between SDMX and VTL artefacts ==
@@ -1269,59 +1269,62 @@
  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.
++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.
++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.
--In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[19~]^^>>path:#_ftn19]](%%).
++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]].
--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).
++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).
  === 10.3.2 General mapping of VTL and SDMX data structures ===
--This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%).
++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]].
--The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[22~]^^>>path:#_ftn22]](%%)
++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]]
--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.
++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.
  A VTL Data Set is structured by one and just one Data Structure and a VTL Data Structure can structure any number of Data Sets. Correspondingly, in the SDMX context a SDMX Dataflow is structured by one and just one DataStructureDefinition and one DataStructureDefinition can structure any number of Dataflows.
--A VTL Data Set has a Data Structure made of Components, which in turn can be Identifiers, Measures and Attributes. Similarly, a SDMX DataflowDefinition has a DataStructureDefinition made of components that can be DimensionComponents, PrimaryMeasure and DataAttributes. In turn, a 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.
++A VTL Data Set has a Data Structure made of Components, which in turn can be Identifiers, Measures and Attributes. Similarly, a SDMX DataflowDefinition has a DataStructureDefinition made of components that can be DimensionComponents, PrimaryMeasure and DataAttributes. In turn, a
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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.
++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.
--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.
++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.
--Instead VTL allows either the method above (an identifier containing the name of the measure together with just one measure component) or a more generic method that consists in defining more measure components in the data structure, one for each measure.
++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.
++Instead VTL allows either  the method above (an identifier containing the name of the measure together with just one measure component) or a more generic method that consists in defining more measure components in the data structure, one for each measure.
++
  Therefore for multi-measure data more mapping options are possible, as described in more detail in the following sections.
  === 10.3.3 Mapping from SDMX to VTL data structures ===
--==== 10.3.3.1 Basic Mapping** ** ====
++**10.3.3.1 Basic Mapping **
--The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes.
++The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes. 1842 When transforming **from SDMX to VTL**, this method consists in leaving the 1843 components unchanged and maintaining their names and roles, according to the 1844 following table:
--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:
++|SDMX|VTL
++|Dimension|(Simple) Identifier
++|Time Dimension|(Time) Identifier
++|Measure Dimension|(Measure) Identifier
++|Primary Measure|Measure
++|Data Attribute|Attribute
--(% style="width:636.294px" %)
--|(% style="width:286px" %)**SDMX**|(% style="width:347px" %)**VTL**
--|(% style="width:286px" %)Dimension|(% style="width:347px" %)(Simple) Identifier
--|(% style="width:286px" %)Time Dimension|(% style="width:347px" %)(Time) Identifier
--|(% style="width:286px" %)Measure Dimension|(% style="width:347px" %)(Measure) Identifier
--|(% style="width:286px" %)Primary Measure|(% style="width:347px" %)Measure
--|(% style="width:286px" %)Data Attribute|(% style="width:347px" %)Attribute
++According to this method, the resulting VTL structures are always mono-measure
--According to this method, the resulting VTL structures are always mono-measure (i.e., they have just one measure component) and their Measure is the SDMX PrimaryMeasure. Nevertheless, if the SDMX data structure has a MeasureDimension, which can convey the name of one or more measure concepts, such unique measure component can contain the value of more (conceptual) measures (one for each observation).
++(i.e., they have just one measure component) and their Measure is the SDMX
++PrimaryMeasure. Nevertheless, if the SDMX data structure has a MeasureDimension, which can convey the name of one or more measure concepts, such unique measure component can contain the value of more (conceptual) measures (one for each observation).
++
  As for 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).
  With the Basic mapping, one SDMX observation generates one VTL data point.
--==== 10.3.3.2 Pivot Mapping ====
++**10.3.3.2 Pivot Mapping **
--An alternative mapping method from SDMX to VTL is the **Pivot **mapping, which is different from the Basic method only for the SDMX data structures that contain a MeasureDimension, which are mapped to multi-measure VTL data structures.
++An alternative mapping method from SDMX to VTL is the **Pivot **mapping, which is different from the Basic method only for the SDMX data structures that contain a MeasureDimension, which are mapped to multi-measure VTL data structures.
  The SDMX structures that do not contain a MeasureDimension are mapped like in the Basic mapping (see the previous paragraph).
@@ -1332,34 +1332,36 @@
  * The SDMX MeasureDimension is not mapped to VTL (it disappears in the VTL Data Structure);
  * The SDMX PrimaryMeasure is not mapped to VTL as well (it disappears in the VTL Data Structure);
  * A SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
--** 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;
--** 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 Concept 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
++** 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;
++** 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 Concept 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
  Concept of the MeasureDimension separated by underscore; for example, if the SDMX DataAttribute is named DA and the possible concepts 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.
  The summary mapping table of the “pivot” mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
--(% style="width:941.294px" %)
--|(% style="width:441px" %)**SDMX**|(% style="width:497px" %)**VTL**
--|(% style="width:441px" %)Dimension|(% style="width:497px" %)(Simple) Identifier
--|(% style="width:441px" %)TimeDimension|(% style="width:497px" %)(Time) Identifier
--|(% style="width:441px" %)MeasureDimension & PrimaryMeasure|(% style="width:497px" %)One Measure for each Concept of the SDMX Measure Dimension
--|(% style="width:441px" %)DataAttribute not depending on the MeasureDimension|(% style="width:497px" %)Attribute
--|(% style="width:441px" %)DataAttribute depending on the MeasureDimension|(% style="width:497px" %)One Attribute for each Concept of the SDMX Measure Dimension
++|SDMX|VTL
++|Dimension|(Simple) Identifier
++|TimeDimension|(Time) Identifier
++|MeasureDimension & PrimaryMeasure|One Measure for each Concept of the SDMX Measure Dimension
++|DataAttribute not depending on the MeasureDimension|Attribute
++|DataAttribute depending on the MeasureDimension|One Attribute for each Concept of the SDMX Measure Dimension
--Using this mapping method, the components of the data structure can change in the conversion from SDMX to VTL and it must be taken into account that the VTL statements can reference only the components of the resulting VTL data structure.
++Using this mapping method, the components of the data structure can change in the conversion from SDMX to VTL and it must be taken into account that the VTL 1908 statements can reference only the components of the resulting VTL data structure.
--At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Concept of the MeasureDimension:
++At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Concept of the 1911 MeasureDimension:
--* 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 Concept Cj of the SDMX MeasureDimension;
--* 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.
--* The value of the PrimaryMeasure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj
--* 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
++ 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 Concept Cj of the SDMX MeasureDimension;
--==== 10.3.3.3 From SDMX DataAttributes to VTL Measures ====
++*
++** 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.
++** The value of the PrimaryMeasure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj
++** 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
--* 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.
++**10.3.3.3 From SDMX DataAttributes to VTL Measures **
++*
++** 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.
++
  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.
  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.
@@ -1366,27 +1366,28 @@
  === 10.3.4 Mapping from VTL to SDMX data structures ===
--==== 10.3.4.1 Basic Mapping** ** ====
++**10.3.4.1 Basic Mapping **
  The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
--This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes.
++This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes.
  The method consists in leaving the components unchanged and maintaining their names and roles in SDMX, according to the following mapping table, which is the same as the basic mapping from SDMX to VTL, only seen in the opposite direction.
--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 PrimaryMeasure). In this case it becomes mandatory to specify a different mapping method through the VtlMappingScheme and VtlDataflowMapping classes.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)
++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
--Please note that the VTL measures can have any name while in SDMX 2.1 the MeasureComponent has the mandatory name “obs_value”, therefore the name of the VTL measure name must become “obs_value” in SDMX 2.1.
++PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[^^~[24~]^^>>path:#_ftn24]]
++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.
++
  Mapping table:
--(% style="width:592.294px" %)
--|(% style="width:253px" %)**VTL**|(% style="width:336px" %)**SDMX**
--|(% style="width:253px" %)(Simple) Identifier|(% style="width:336px" %)Dimension
--|(% style="width:253px" %)(Time) Identifier|(% style="width:336px" %)TimeDimension
--|(% style="width:253px" %)(Measure) Identifier|(% style="width:336px" %)MeasureDimension
--|(% style="width:253px" %)Measure|(% style="width:336px" %)PrimaryMeasure
--|(% style="width:253px" %)Attribute|(% style="width:336px" %)DataAttribute
++|VTL|SDMX
++|(Simple) Identifier|Dimension
++|(Time) Identifier|TimeDimension
++|(Measure) Identifier|MeasureDimension
++|Measure|PrimaryMeasure
++|Attribute|DataAttribute
  If the distinction between simple identifier, time identifier and measure identifier is not maintained in the VTL environment, the classification between Dimension, TimeDimension and MeasureDimension exists only in SDMX, as declared in the relevant DataStructureDefinition.
@@ -1394,14 +1394,16 @@
  Note that the basic mappings in the two directions (from SDMX 2.1 to VTL 2.0 and vice-versa) are (almost completely) reversible. In fact, if a SDMX 2.1 structure is mapped to a VTL structure and then the latter is mapped back to SDMX 2.1, the resulting data structure is like the original one (apart for the AttributeRelationship, that can be different if the original SDMX 2.1 structure contains DataAttributes that are not at observation level). In reverse order, if a VTL 2.0 mono-measure structure is mapped to SDMX 2.1 and then the latter is mapped back to VTL 2.0, the original data structure is obtained (apart from the name of the VTL measure, that in SDMX 2.1 must become “obs_value”).
--As said, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the assignmentStatus, which does not exist in VTL, the AttributeRelationship for the DataAttributes and so on.
++As  said, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the assignmentStatus,  which does not exist in VTL, the AttributeRelationship for the DataAttributes and so on.
--==== 10.3.4.2 Unpivot Mapping ====
++**10.3.4.2 Unpivot Mapping **
--An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
++An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
--Although this mapping method can be used in any case, it makes major sense in case the VTL data structure has more than one measure component (multi-measures VTL structure). For such VTL structures, in fact, the basic method cannot be applied, given that by maintaining the data structure unchanged the resulting SDMX data structure would have more than one measure component, which is not allowed by SDMX 2.1 (it allows just one measure component, the PrimaryMeasure, called “obs_value”).
++Although this mapping method can be used in any case, it makes major sense in case the VTL data structure has more than one measure component (multi-measures VTL structure). For such VTL structures, in fact, the basic method cannot be applied, given that by maintaining the data structure unchanged the resulting SDMX data structure would have more than one measure component, which is not allowed by SDMX 2.1 (it allows just one measure component, the PrimaryMeasure, called
++“obs_value”).
++
  The multi-measures VTL structures have not a Measure Identifier (because the Measures are separate components) and need to be converted to SDMX dataflows having an added MeasureDimension which disambiguates the multiple measures, and an added PrimaryMeasure, in which the measures’ values are maintained.
  The **unpivot** mapping behaves like follows:
@@ -1408,34 +1408,43 @@
  * like in the basic mapping, a VTL (simple) identifier becomes a SDMX
--Dimension and a VTL (time) identifier becomes a SDMX TimeDimension (as said, a measure identifier cannot exist in multi-measure VTL structures);
++Dimension and a VTL (time) identifier becomes a SDMX TimeDimension (as said, a  measure identifier cannot exist in multi-measure VTL structures);
  * a MeasureDimension component called “measure_name” is added to the SDMX DataStructure;
--* a PrimaryMeasure component called “obs_value” is added to the SDMX DataStructure;
--* each VTL Measure is mapped to a Concept of the SDMX MeasureDimension having the same name as the VTL Measure (therefore all the VTL Measure Components do not originate Components in the SDMX DataStructure);
--* a VTL Attribute becomes a SDMX DataAttribute having AttributeRelationship referred to all the SDMX DimensionComponents including the TimeDimension and except the MeasureDimension.
++* a PrimaryMeasure component called  “obs_value” is added to the SDMX DataStructure;
++* each VTL Measure is mapped to a Concept of the SDMX MeasureDimension  having the same name as the VTL Measure (therefore all the VTL Measure Components do not originate Components in the SDMX DataStructure);
++* a VTL Attribute becomes a SDMX DataAttribute having AttributeRelationship  referred to all the SDMX DimensionComponents including the TimeDimension  and except the MeasureDimension.
  The summary mapping table of the **unpivot** mapping method is the following:
--(% style="width:904.294px" %)
--|(% style="width:291px" %)**VTL**|(% style="width:611px" %)**SDMX**
--|(% style="width:291px" %)(Simple) Identifier|(% style="width:611px" %)Dimension
--|(% style="width:291px" %)(Time) Identifier|(% style="width:611px" %)TimeDimension
--|(% style="width:291px" %)All Measure Components|(% style="width:611px" %)(((
--MeasureDimension (having one Measure Concept for each VTL measure component) & PrimaryMeasure
++
++|VTL|SDMX
++|(Simple) Identifier|Dimension
++|(Time) Identifier|TimeDimension
++|All Measure Components|(((
++MeasureDimension (having one Measure Concept for each VTL measure component) &
++
++PrimaryMeasure
  )))
--|(% style="width:291px" %)Attribute |(% style="width:611px" %)(((
--DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
++|Attribute |(((
++DataAttribute depending on all
++
++SDMX Dimensions including the
++
++TimeDimension and except the MeasureDimension
  )))
  At observation / data point level:
--* a multi-measure VTL Data Point becomes a set of SDMX observations, one for each VTL measure
--* the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above
--* the name of the j^^th^^ VTL measure (e.g. “Cj”) becomes the value of the SDMX MeasureDimension of the j^^th^^ observation of the set (i.e. the Concept Cj)
--* the value of the j^^th^^ VTL measure becomes the value of the SDMX PrimaryMeasure of the j^^th^^ observation of the set
--* the values of the VTL Attributes become the values of the corresponding SDMX DataAttributes (in principle for all the observations of the set above)
++ a multi-measure VTL Data Point becomes a set of SDMX observations, one for each VTL measure
++ the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above
++
++*
++** the name of the j^^th^^ VTL measure (e.g. “Cj”) becomes the value of the SDMX MeasureDimension of the j^^th^^ observation of the set (i.e. the Concept Cj)
++** the value of the j^^th^^ VTL measure becomes the value of the SDMX PrimaryMeasure of the j^^th^^ observation of the set
++** the values of the VTL Attributes become the values of the corresponding SDMX DataAttributes (in principle for all the observations of the set above)
++
  If desired, this method can be applied also to mono-measure VTL structures, provided that none of the VTL components has already the role of measure identifier.
  Like in the general case, a MeasureDimension component called “measure_name” would be added to the SDMX DataStructure and would have just one possible measure concept, corresponding to the unique VTL measure. The original VTL measure component would not become a Component in the SDMX data structure. The value of the VTL measure would be assigned to the SDMX PrimaryMeasure called “obs_value”.
@@ -1442,150 +1442,219 @@
  In any case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the possible Concepts of the SDMX MeasureDimension need to be listed in a SDMX ConceptScheme, with proper id, agency and version; moreover, the SDMX DSD must have the assignmentStatus, which does not exist in VTL, the attributeRelationship for the DataAttributes and so on.
--==== 10.3.4.3 From VTL Measures to SDMX Data Attributes** ** ====
++**10.3.4.3 From VTL Measures to SDMX Data Attributes **
  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 one VTL measure in the SDMX primaryMeasure and all the other VTL Measures in SDMX DataAttributes. This method is called M2A (“M2A” stands for “Measures to DataAttributes”).
  When applied to mono-measure VTL structures (having one Measure component), the M2A method behaves like the Basic mapping (the VTL Measure component becomes the SDMX primary measure “obs_value”, there is no additional VTL measure to be converted to SDMX DataAttribute). Therefore the mapping table is the same as for the Basic method:
--(% style="width:591.294px" %)
--|(% style="width:252px" %)**VTL**|(% style="width:336px" %)**SDMX**
--|(% style="width:252px" %)(Simple) Identifier|(% style="width:336px" %)Dimension
--|(% style="width:252px" %)(Time) Identifier|(% style="width:336px" %)TimeDimension
--|(% style="width:252px" %)(Measure) Identifier (if any)|(% style="width:336px" %)MeasureDimension
--|(% style="width:252px" %)Measure|(% style="width:336px" %)PrimaryMeasure
--|(% style="width:252px" %)Attribute|(% style="width:336px" %)DataAttribute
++|VTL|SDMX
++|(Simple) Identifier|Dimension
++|(Time) Identifier|TimeDimension
++|(Measure) Identifier (if any)|MeasureDimension
++|Measure|PrimaryMeasure
++|Attribute|DataAttribute
--For multi-measure VTL structures (having more than one Measure component), one VTL Measure becomes the SDMX PrimaryMeasure while the other VTL Measures maintain their names and values but assume the role of DataAttribute in SDMX. The choice of the VTL Measure that correspond to the SDMX PrimaryMeasure is left to the definer of the SDMX data structure definition.
++For multi-measure VTL structures (having more than one Measure component), one VTL Measure becomes the SDMX PrimaryMeasure while the other VTL Measures maintain their names and values but assume the role of DataAttribute in SDMX. The choice of the VTL Measure that correspond to the SDMX PrimaryMeasure is  left to the definer of the SDMX data structure definition.
--Taking into account that the multi-measure VTL structures do not have a measure identifier, the mapping table is the following:
++2Taking into account that the multi-measure VTL structures do not have a measure 2073 identifier, the mapping table is the following:
--(% style="width:588.294px" %)
--|(% style="width:259px" %)**VTL**|(% style="width:326px" %)**SDMX**
--|(% style="width:259px" %)(Simple) Identifier|(% style="width:326px" %)Dimension
--|(% style="width:259px" %)(Time) Identifier|(% style="width:326px" %)TimeDimension
--|(% style="width:259px" %)One of the Measures|(% style="width:326px" %)PrimaryMeasure
--|(% style="width:259px" %)Other Measures|(% style="width:326px" %)DataAttribute
--|(% style="width:259px" %)Attribute|(% style="width:326px" %)DataAttribute
++|VTL|SDMX
++|(Simple) Identifier|Dimension
++|(Time) Identifier|TimeDimension
++|One of the Measures|PrimaryMeasure
++|Other Measures|DataAttribute
++|Attribute|DataAttribute
--Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the assignmentStatus, which does not exist in VTL, the attributeRelationship for the DataAttributes and so on. In particular, the primaryMeasure of the SDMX 2.1 DSD must be called “obs_value” and must be one of the VTL Measures, chosen by the DSD definer.
++Even in this case, the resulting SDMX definitions must be compliant with the SDMX consistency rules. For example, the SDMX DSD must have the assignmentStatus,  which does not exist in VTL, the attributeRelationship for the DataAttributes and so on. In particular, the primaryMeasure of the SDMX 2.1 DSD must be called “obs_value” and must be one of the VTL Measures, chosen by the DSD definer.
  === 10.3.5 Declaration of the mapping methods between data structures ===
  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.
++
  A customized mapping can be defined through the VtlMappingScheme and VtlDataflowMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlDataflowMapping allows specifying the mapping methods to be used for a specific dataflow, both in the direction from SDMX to VTL (toVtlMappingMethod) and from VTL to SDMX (fromVtlMappingMethod); in fact a VtlDataflowMapping associates the structured URN that identifies a SDMX dataflow to its VTL alias and its mapping methods.
--It is possible to specify the toVtlMappingMethod and fromVtlMappingMethod also for the conventional dataflow called “generic_dataflow”: in this case the specified mapping methods are intended to become the default ones, overriding the “Basic” methods. In turn, the toVtlMappingMethod and fromVtlMappingMethod declared for a specific Dataflow are intended to override the default ones for such a Dataflow.
++It is possible to specify the toVtlMappingMethod and fromVtlMappingMethod also for the conventional dataflow called “generic_dataflow”: in this case the specified mapping methods are intended to become the default ones, overriding the
++“Basic” methods. In turn, the toVtlMappingMethod and fromVtlMappingMethod declared for a specific Dataflow are intended to override the default ones for such a Dataflow.
++
   The VtlMappingScheme is a container for zero or more VtlDataflowMapping (besides possible mappings to artefacts other than dataflows).
--=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
++=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[^^**~[25~]**^^>>path:#_ftn25]]  ===
--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 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).
++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
--As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[26~]^^>>path:#_ftn26]](%%)
++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).
--Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL data sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[27~]^^>>path:#_ftn27]](%%)
++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]]
--Given a SDMX Dataflow and some predefined Dimensions of its DataStructure, it is allowed to map the subsets of observations that have the same combination of values for such Dimensions to correspondent VTL datasets.
++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]]
--For example, assuming that the SDMX dataflow DF1(1.0) has the Dimensions INDICATOR, TIME_PERIOD and COUNTRY, and that the user declares the Dimensions INDICATOR and COUNTRY as basis for the mapping (i.e. the mapping dimensions): the observations that have the same values for INDICATOR and COUNTRY would be mapped to the same VTL dataset (and vice-versa).
++                   Given    a      SDMX Dataflow      and    some      predefined Dimensions      of    its
++DataStructure, it is allowed to map the subsets of observations that have the same combination of values for such Dimensions to correspondent VTL datasets.
++
++For example, assuming that the SDMX dataflow DF1(1.0) has the Dimensions INDICATOR, TIME_PERIOD and COUNTRY, and that the user declares the
++
++Dimensions INDICATOR and COUNTRY as basis for the mapping (i.e. the mapping dimensions):  the observations that have the same values for INDICATOR and COUNTRY would be mapped to the same VTL dataset (and vice-versa).
++
  In practice, this kind mapping is obtained like follows:
--* 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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
++* 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.
  * The VTL dataset is given a name using a special notation also called “ordered concatenation” and composed of the following parts:
--** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated URN or another alias); for example DF(1.0);
--** a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
--** 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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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.
++** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated
++URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[^^~[29~]^^>>path:#_ftn29]]
++
++*
++** 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.
++
  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.
  Therefore, the generic name of this kind of VTL datasets would be:
--> ‘DF(1.0)///INDICATORvalue//.//COUNTRYvalue//’
++‘DF(1.0)///INDICATORvalue//.//COUNTRYvalue//’
  Where DF(1.0) 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:
--> ‘DF(1.0)/POPULATION.USA’
++‘DF(1.0)/POPULATION.USA’
--In particular, this is the VTL dataset that contains all the observations of the dataflow DF(1.0) for which //INDICATOR// = POPULATION and //COUNTRY// = USA.
++In particular, this is the VTL dataset that contains all the observations of the dataflow DF(1.0) for which  //INDICATOR// = POPULATION and //COUNTRY// = USA.
  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.
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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.
++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.
--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.
++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.
--As already said, each VTL dataset is assumed to contain all the observations of the SDMX dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=//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.
++As already said, each VTL dataset is assumed to contain all the observations of the
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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 …).
++SDMX dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=
--In the example above, for all the datasets of the kind ‘DF1(1.0)///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.
++//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.
++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 …).
++
++In the example above, for all the datasets of the kind
++
++‘DF1(1.0)///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.
++
  It should be noted that the desired VTL datasets (i.e. of the kind ‘DF1(1.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the dataflow DF1(1.0), like in the following VTL expression:
--> ‘DF1(1.0)/POPULATION.USA’ :=
--> DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
--> ‘DF1(1.0)/POPULATION.CANADA’ :=
--> DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
--> …   …   …
++‘DF1(1.0)/POPULATION.USA’ :=
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[33~]^^>>path:#_ftn33]]
++DF1(1.0) [ sub  INDICATOR=“POPULATION”, COUNTRY=“USA” ];
++
++‘DF1(1.0)/POPULATION.CANADA’ :=
++
++DF1(1.0) [ sub  INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
++
++
++…   …   …
++
++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]]
++
  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.
--For example, ‘DF(1.0)/POPULATION.’ (note the dot in the end of the name) is the VTL dataset that contains all the observations of the dataflow DF(1.0) for which //INDICATOR// = POPULATION and COUNTRY = any value.
++For example, ‘DF(1.0)/POPULATION.’ (note the dot in the end of the name) is the VTL dataset that contains all the observations of the dataflow DF(1.0) for which  //INDICATOR// = POPULATION and COUNTRY = any value.
  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
--> ‘DF1(1.0)/POPULATION.’ :=
-->  DF1(1.0) [sub INDICATOR=“POPULATION” ];
++‘DF1(1.0)/POPULATION.’ :=
++DF1(1.0) [ sub  INDICATOR=“POPULATION” ];
++
++
  Therefore the VTL dataset ‘DF1(1.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
  Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
--Let us now analyse the __mapping direction from VTL to SDMX__.
++Let us now analyse the mapping direction from VTL to SDMX.
  In this situation, distinct parts of a SDMX dataflow are calculated as distinct VTL datasets, under the constraint that they must have the same VTL data structure.
  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:
--* each part is calculated as a VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)
--* 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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[35~]^^>>path:#_ftn35]]
++* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[^^~[34~]^^>>path:#_ftn34]]
++* 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]]
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[36~]^^>>path:#_ftn36]](%%).
++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]].
--The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]
++The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[^^~[37~]^^>>path:#_ftn37]]
  ‘DF2(1.0)///INDICATORvalue//.//COUNTRYvalue//’  <-  expression
  Some examples follow, for some specific values of INDICATOR and COUNTRY:
--‘DF2(1.0)/GDPPERCAPITA.USA’           <-   expression11;
++                                            ‘DF2(1.0)/GDPPERCAPITA.USA’             <-   expression11;
++
  ‘DF2(1.0)/GDPPERCAPITA.CANADA’   <-   expression12;
++
  …   …   …
--‘DF2(1.0)/POPGROWTH.USA’               <-   expression21;
--‘DF2(1.0)/POPGROWTH.CANADA’       <-   expression22;
++                                            ‘DF2(1.0)/POPGROWTH.USA’                 <-   expression21;
++
++                                            ‘DF2(1.0)/POPGROWTH.CANADA’         <-   expression22;
++
  …   …   …
--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:
--[[image:1747859458410-183.png||height="170" width="663"]]
++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:
--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)), that can be mapped one-to-one to the homonymous SDMX Dataflow. Following the same example, these VTL transformations would be:
++|(((
++      //VTL dataset                                             //
--[[image:1747859612718-454.png||height="451" width="602"]]
++
++)))|(% colspan="2" %)//INDICATOR value //|(% colspan="2" %)//COUNTRY value//
++|‘DF2(1.0)/GDPPERCAPITA.USA’              |GDPPERCAPITA| | |USA
++|(((
++‘DF2(1.0)/GDPPERCAPITA.CANADA’
--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 wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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.
++…   …   …
++)))|GDPPERCAPITA| | |CANADA
++|‘DF2(1.0)/POPGROWTH.USA’                  |POPGROWTH | | |USA
++|(((
++‘DF2(1.0)/POPGROWTH.CANADA’
--Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
++…   …   …
++)))|POPGROWTH | | |CANADA
++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)), that can be mapped one-to-one to the homonymous SDMX Dataflow.  Following the same example, these VTL transformations would be:
++
++DF2bis_GDPPERCAPITA_USA                        :=   ‘DF2(1.0)/GDPPERCAPITA.USA’
++
++[calc  identifier INDICATOR := ”GDPPERCAPITA”,  identifier  COUNTRY := ”USA”];
++
++DF2bis_GDPPERCAPITA_CANADA :=   ‘DF2(1.0)/GDPPERCAPITA.CANADA’   [calc  identifier INDICATOR:=”GDPPERCAPITA”,  identifier COUNTRY:=”CANADA”]; …   …   …
++
++DF2bis_POPGROWTH_USA                        :=  ‘DF2(1.0)/POPGROWTH.USA’
++
++[calc  identifier INDICATOR := ”POPGROWTH”,  identifier  COUNTRY :=”USA”];
++
++DF2bis_POPGROWTH_CANADA’                    :=  ‘DF2(1.0)/POPGROWTH.CANADA’
++
++[calc  identifier INDICATOR := ”POPGROWTH”,  identifier  COUNTRY := ”CANADA”]; …   …   …
++
++DF2(1.0)     <-                  UNION          (DF2bis_GDPPERCAPITA_USA’,
++
++DF2bis_GDPPERCAPITA_CANADA’,
++
++… ,
++
++DF2bis_POPGROWTH_USA’,
++
++DF2bis_POPGROWTH_CANADA’
++
++…);
++
++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.
++
++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]]
++
  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).
  === 10.3.7 Mapping variables and value domains between VTL and SDMX ===
@@ -1592,41 +1592,58 @@
  With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
--(% style="width:890.835px" %)
--|(% style="width:314px" %)VTL|(% style="width:574px" %)SDMX
--|(% style="width:314px" %)**Data Set Component**|(% style="width:574px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a Dimension or a PrimaryMeasure or a DataAttribute) belonging to one specific Dataflow^^42^^
--|(% style="width:314px" %)**Represented Variable**|(% style="width:574px" %)**Concept** with a definite Representation
--|(% style="width:314px" %)**Value Domain**|(% style="width:574px" %)**Representation** (see the Structure Pattern in the Base Package)
--|(% style="width:314px" %)**Enumerated Value Domain / Code List**|(% style="width:574px" %)(((
--**Codelist** (for enumerated Dimension, PrimaryMeasure, DataAttribute) or **ConceptScheme **(for MeasureDimension)
++|VTL|SDMX
++|**Data Set Component**|Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a Dimension or a PrimaryMeasure or a DataAttribute) belonging to one specific Dataflow^^42^^
++|**Represented Variable**|**Concept** with  a definite Representation
++|**Value Domain**|**Representation** (see the Structure Pattern in the Base Package)
++|**Enumerated Value Domain / Code List**|(((
++**Codelist** (for enumerated
++
++Dimension, PrimaryMeasure,
++
++DataAttribute) or **ConceptScheme**
++
++(for MeasureDimension)
  )))
--|(% style="width:314px" %)**Code**|(% style="width:574px" %)**Code** (for enumerated Dimension, PrimaryMeasure, DataAttribute) or **Concept** (for MeasureDimension)
--|(% style="width:314px" %)**Described Value Domain**|(% style="width:574px" %)(((
--non-enumerated** Representation **(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
++|**Code**|**Code** (for enumerated Dimension, PrimaryMeasure, DataAttribute) or **Concept** (for MeasureDimension)
++|**Described Value Domain**|(((
++non-enumerated** Representation**
++
++(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
  )))
--|(% style="width:314px" %)**Value**|(% style="width:574px" %)(((
--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 to a valid **value **(for non-enumerated** **Representations) or to a **Concept **(for MeasureDimension)
++|**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 to a valid **value **(for non-enumerated** **
++
++Representations) or to a **Concept**
++
++(for MeasureDimension)
  )))
--|(% style="width:314px" %)**Value Domain Subset / Set**|(% style="width:574px" %)This abstraction does not exist in SDMX
--|(% style="width:314px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:574px" %)This abstraction does not exist in SDMX
--|(% style="width:314px" %)**Described Value Domain Subset / Described Set**|(% style="width:574px" %)This abstraction does not exist in SDMX
--|(% style="width:314px" %)**Set list**|(% style="width:574px" %)This abstraction does not exist in SDMX
++|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
++|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
++|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
++|**Set list**|This abstraction does not exist in SDMX
  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).
--Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value Domain) is not identifiable. As a consequence, the definition of the VTL rulesets, which in VTL can refer either to enumerated or non-enumerated value domains, in SDMX can refer only to enumerated Value Domains (i.e. to SDMX Codelists).
++Another difference consists in the fact that all Value Domains are considered as identifiable objects in VTL either if enumerated or not, while in SDMX  the Codelist (corresponding to a VTL enumerated Value Domain) is identifiable, while the SDMX non-enumerated Representation (corresponding to a VTL non-enumerated Value
--As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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.
++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).
--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
++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.
--DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
++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
--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.
++                         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.
++
  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 transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
--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. ISO-alpha-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.
++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. ISO-alpha-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.
  == 10.4 Mapping between SDMX and VTL Data Types ==
@@ -1644,7 +1644,6 @@
  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):
--[[image:1747859722732-549.png||height="283" width="224"]]
  **Figure 13 – VTL Basic Scalar Types**
@@ -1666,252 +1666,303 @@
  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.
--=== 10.4.3 Mapping SDMX data types to VTL basic scalar types ===
++=== 10.4.3 Mapping SDMX data types to VTL basic scalar types  ===
  The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
--(% style="width:653.835px" %)
--|(% style="width:366px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:284px" %)**Default VTL basic scalar type**
--|(% style="width:366px" %)(((
--**String**
++|**SDMX data type (BasicComponentDataType)**|**Default VTL basic scalar type**
++|(((
++**String   **
++
  (string allowing any character)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**Alpha**
++)))|**string**
++|(((
++**Alpha    **
++
  (string which only allows A-z)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**AlphaNumeric**
++)))|**string**
++|(((
++**AlphaNumeric  **
++
  (string which only allows A-z and 0-9)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**Numeric**
++)))|**string**
++|(((
++**Numeric   **
++
  (string which only allows 0-9, but is not numeric so that is can having leading zeros)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**BigInteger**
++)))|**string**
++|(((
++**BigInteger **
++
  (corresponds to XML Schema xs:integer datatype; infinite set of integer values)
--)))|(% style="width:284px" %)**integer**
--|(% style="width:366px" %)(((
--**Integer**
--(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
--)))|(% style="width:284px" %)**integer**
--|(% style="width:366px" %)(((
--**Long**
--(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
--)))|(% style="width:284px" %)**integer**
--|(% style="width:366px" %)(((
--**Short**
++)))|**integer**
++|(((
++**Integer **
++
++(corresponds to XML Schema xs:int datatype; between
++
++-2147483648 and +2147483647 (inclusive))
++)))|**integer**
++|(((
++**Long **
++
++(corresponds to XML Schema xs:long datatype;
++
++between -9223372036854775808 and +9223372036854775807 (inclusive))
++)))|**integer**
++|(((
++**Short **
++
  (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
--)))|(% style="width:284px" %)**integer**
--|(% style="width:366px" %)(((
++)))|**integer**
++|(((
  **Decimal**
++
  (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)
--)))|(% style="width:284px" %)**number**
--|(% style="width:366px" %)(((
--**Float**
++)))|**number**
++|(((
++**Float **
++
  (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
--)))|(% style="width:284px" %)**number**
--|(% style="width:366px" %)(((
--**Double**
++)))|**number**
++|(((
++**Double **
++
  (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
--)))|(% style="width:284px" %)**number**
--|(% style="width:366px" %)(((
--**Boolean**
--(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
--)))|(% style="width:284px" %)**boolean**
--|(% style="width:366px" %)(((
--**URI**
++)))|**number**
++|(((
++**Boolean **
++
++(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
++)))|**boolean**
++|(((
++**URI **
++
  (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**Count**
++)))|**string**
++|(((
++**Count   **
++
  (an integer following a sequential pattern, increasing by 1 for each occurrence)
--)))|(% style="width:284px" %)**integer**
--|(% style="width:366px" %)(((
--**InclusiveValueRange**
++)))|**integer**
++|(((
++**InclusiveValueRange **
++
  (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
--)))|(% style="width:284px" %)**number**
--|(% style="width:366px" %)(((
--**ExclusiveValueRange**
++)))|**number**
++|(((
++**ExclusiveValueRange **
++
  (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
--)))|(% style="width:284px" %)**number**
--|(% style="width:366px" %)(((
--**Incremental **
++)))|**number**
++|(((
++**Incremental  **
++
  (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
--)))|(% style="width:284px" %)**number**
--|(% style="width:366px" %)(((
--**ObservationalTimePeriod**
++)))|**number**
++|(((
++**ObservationalTimePeriod   **
++
  (superset of StandardTimePeriod and TimeRange)
--)))|(% style="width:284px" %)**time**
--|(% style="width:366px" %)(((
--**StandardTimePeriod**
++)))|**time**
++|(((
++**StandardTimePeriod   **
++
  (superset of BasicTimePeriod and ReportingTimePeriod)
--)))|(% style="width:284px" %)**time**
--|(% style="width:366px" %)(((
--**BasicTimePeriod**
++)))|**time**
++|(((
++**BasicTimePeriod  **
++
  (superset of GregorianTimePeriod and DateTime)
--)))|(% style="width:284px" %)**date**
--|(% style="width:366px" %)(((
--**GregorianTimePeriod**
++)))|**date**
++|(((
++**GregorianTimePeriod   **
++
  (superset of GregorianYear, GregorianYearMonth, and GregorianDay)
--)))|(% style="width:284px" %)**date**
--|(% style="width:366px" %)**GregorianYear **(YYYY)|(% style="width:284px" %)**date**
--|(% style="width:366px" %)**GregorianYearMonth** / **GregorianMonth** (YYYY-MM)|(% style="width:284px" %)**date**
--|(% style="width:366px" %)**GregorianDay **(YYYY-MM-DD)|(% style="width:284px" %)**date**
--|(% style="width:366px" %)(((
++)))|**date**
++|**GregorianYear     **(YYYY)  |**date**
++|**GregorianYearMonth** / **GregorianMonth**    (YYYY-MM)|**date**
++|**GregorianDay    **(YYYY-MM-DD)|**date**
++|(((
  **ReportingTimePeriod **
--(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**ReportingYear**
++
++(superset of RepostingYear, ReportingSemester,
++
++ReportingTrimester, ReportingQuarter, ReportingMonth,
++
++ReportingWeek, ReportingDay)
++)))|**time_period**
++|(((
++**ReportingYear   **
++
  (YYYY-A1 – 1 year period)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**ReportingSemester**
++)))|**time_period**
++|(((
++**ReportingSemester  **
++
  (YYYY-Ss – 6 month period)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**ReportingTrimester**
++)))|**time_period**
++|(((
++**ReportingTrimester **
++
  (YYYY-Tt – 4 month period)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**ReportingQuarter**
++)))|**time_period**
++|(((
++**ReportingQuarter   **
++
  (YYYY-Qq – 3 month period)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**ReportingMonth**
++)))|**time_period**
++|(((
++**ReportingMonth   **
++
  (YYYY-Mmm – 1 month period)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**ReportingWeek**
++)))|**time_period**
++|(((
++**ReportingWeek   **
++
  (YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**ReportingDay**
++)))|**time_period**
++|(((
++**ReportingDay   **
++
  (YYYY-Dddd – 1 day period)
--)))|(% style="width:284px" %)**time_period**
--|(% style="width:366px" %)(((
--**DateTime**
++)))|**time_period**
++|(((
++**DateTime  **
++
  (YYYY-MM-DDThh:mm:ss)
--)))|(% style="width:284px" %)**date**
--|(% style="width:366px" %)(((
--**TimeRange**
++)))|**date**
++|(((
++**TimeRange   **
  (YYYY-MM-DD(Thh:mm:ss)?/<duration>)
--)))|(% style="width:284px" %)**time**
--|(% style="width:366px" %)(((
--**Month**
--(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**MonthDay**
--(~-~-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)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**Day**
++)))|**time**
++|(((
++**Month   **
++
++(~-~-MM; speicifies a month independent of a year; e.g.
++
++February is black history month in the United States)
++)))|**string**
++|(((
++**MonthDay   **
++
++(~-~-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)
++)))|**string**
++|(((
++**Day   **
++
  (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**Time**
++)))|**string**
++|(((
++**Time   **
++
  (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
--)))|(% style="width:284px" %)**string**
--|(% style="width:366px" %)(((
--**Duration**
++)))|**string**
++|(((
++**Duration **
++
  (corresponds to XML Schema xs:duration datatype)
--)))|(% style="width:284px" %)**duration**
--|(% style="width:366px" %)XHTML|(% style="width:284px" %)Metadata type – not applicable
--|(% style="width:366px" %)KeyValues|(% style="width:284px" %)Metadata type – not applicable
--|(% style="width:366px" %)IdentifiableReference|(% style="width:284px" %)Metadata type – not applicable
--|(% style="width:366px" %)DataSetReference|(% style="width:284px" %)Metadata type – not applicable
--|(% style="width:366px" %)AttachmentConstraintReference|(% style="width:284px" %)Metadata type – not applicable
++)))|**duration**
++|XHTML|Metadata type – not applicable
++|KeyValues|Metadata type – not applicable
++|IdentifiableReference|Metadata type – not applicable
++|DataSetReference|Metadata type – not applicable
++|AttachmentConstraintReference|Metadata type – not applicable
++
++
  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
  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).
--=== 10.4.4 Mapping VTL basic scalar types to SDMX data types ===
++=== 10.4.4 Mapping VTL basic scalar types to SDMX data types  ===
  The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
--(% style="width:923.835px" %)
--|(% style="width:191px" %)**VTL basic scalar type**|(% style="width:419px" %)**Default SDMX data type (BasicComponentDataType)**|(% style="width:311px" %)**Default output format**
--|(% style="width:191px" %)**String**|(% style="width:419px" %)**String **|(% style="width:311px" %)Like XML (xs:string)
--|(% style="width:191px" %)**Number**|(% style="width:419px" %)**Float **|(% style="width:311px" %)Like XML (xs:float)
--|(% style="width:191px" %)**Integer**|(% style="width:419px" %)**Integer **|(% style="width:311px" %)Like XML (xs:int)
--|(% style="width:191px" %)**Date**|(% style="width:419px" %)**DateTime**|(% style="width:311px" %)YYYY-MM-DDT00:00:00Z
--|(% style="width:191px" %)**Time**|(% style="width:419px" %)**StandardTimePeriod**|(% style="width:311px" %)<date>/<date> (as defined above)
--|(% style="width:191px" %)**time_period**|(% style="width:419px" %)(((
--**ReportingTimePeriod
--(StandardReportingPeriod)**
--)))|(% style="width:311px" %)(((
++|**VTL basic scalar type**|**Default SDMX data type (BasicComponentDataType)**|**Default output format**
++|**String**|**String **|Like XML (xs:string)
++|**Number**|**Float **|Like XML (xs:float)
++|**Integer**|**Integer **|Like XML (xs:int)
++|**Date**|**DateTime**|YYYY-MM-DDT00:00:00Z
++|**Time**|**StandardTimePeriod**|<date>/<date> (as defined above)
++|**time_period**|(((
++**ReportingTimePeriod**
++
++**(StandardReportingPeriod)**
++)))|(((
   YYYY-Pppp
++
  (according to SDMX )
  )))
--|(% style="width:191px" %)**Duration**|(% style="width:419px" %)**Duration **|(% style="width:311px" %)(((
++|**Duration**|**Duration **|(((
  Like XML (xs:duration)
++
  PnYnMnDTnHnMnS
  )))
--|(% style="width:191px" %)**Boolean**|(% style="width:419px" %)**Boolean **|(% style="width:311px" %)(((
--Like XML (xs:boolean) with the values “true” or “false”
++|**Boolean**|**Boolean **|(((
++Like XML (xs:boolean) with the values
++
++“true” or “false”
  )))
  **Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
--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).
++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).
++
  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.
--(% style="width:671.835px" %)
--|(% colspan="2" style="width:669px" %)**VTL special characters for the formatting masks**
--|(% colspan="2" style="width:669px" %)** **
--|(% colspan="2" style="width:669px" %)**Number **
--|(% style="width:141px" %)D|(% style="width:528px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
--|(% style="width:141px" %)E|(% style="width:528px" %)one numeric digit (for the exponent of the scientific notation)
--|(% style="width:141px" %).(dot)|(% style="width:528px" %)possible separator between the integer and the decimal parts.
--|(% style="width:141px" %),(comma)|(% style="width:528px" %)possible separator between the integer and the decimal parts.
--|(% style="width:141px" %) |(% style="width:528px" %)
--|(% colspan="2" style="width:669px" %)**Time and duration**
--|(% style="width:141px" %)C |(% style="width:528px" %)century
--|(% style="width:141px" %)Y|(% style="width:528px" %)year
--|(% style="width:141px" %)S|(% style="width:528px" %)semester
--|(% style="width:141px" %)Q|(% style="width:528px" %)quarter
--|(% style="width:141px" %)M|(% style="width:528px" %)month
--|(% style="width:141px" %)W|(% style="width:528px" %)week
--|(% style="width:141px" %)D|(% style="width:528px" %)day
--|(% style="width:141px" %)h |(% style="width:528px" %)hour digit (by default on 24 hours)
--|(% style="width:141px" %)M|(% style="width:528px" %)minute
--|(% style="width:141px" %)S|(% style="width:528px" %)second
--|(% style="width:141px" %)D|(% style="width:528px" %)decimal of second
--|(% style="width:141px" %)P|(% style="width:528px" %)period indicator (representation in one digit for the duration)
--|(% style="width:141px" %)P|(% style="width:528px" %)number of the periods specified in the period indicator
--|(% style="width:141px" %)AM/PM |(% style="width:528px" %)indicator of AM / PM (e.g. am/pm for “am” or “pm”)
--|(% style="width:141px" %)MONTH|(% style="width:528px" %)uppercase textual representation of the month (e.g., JANUARY for January)
--|(% style="width:141px" %)DAY|(% style="width:528px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
--|(% style="width:141px" %)Month|(% style="width:528px" %)lowercase textual representation of the month (e.g., january)
--|(% style="width:141px" %)Day|(% style="width:528px" %)lowercase textual representation of the month (e.g., monday)
--|(% style="width:141px" %)Month|(% style="width:528px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
--|(% style="width:141px" %)Day|(% style="width:528px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
--|(% style="width:141px" %) |(% style="width:528px" %)
--|(% colspan="2" style="width:669px" %)**String**
--|(% style="width:141px" %)X|(% style="width:528px" %)any string character
--|(% style="width:141px" %)Z|(% style="width:528px" %)any string character from “A” to “z”
--|(% style="width:141px" %)9|(% style="width:528px" %)any string character from “0” to “9”
--|(% style="width:141px" %) |(% style="width:528px" %)
--|(% colspan="2" style="width:669px" %)**Boolean **
--|(% style="width:141px" %)B|(% style="width:528px" %)Boolean using “true” for True and “false” for False
--|(% style="width:141px" %)1|(% style="width:528px" %)Boolean using “1” for True and “0” for False
--|(% style="width:141px" %)0|(% style="width:528px" %)Boolean using “0” for True and “1” for False
--|(% style="width:141px" %) |(% style="width:528px" %)
--|(% colspan="2" style="width:669px" %)Other qualifiers
--|(% style="width:141px" %)*|(% style="width:528px" %)an arbitrary number of digits (of the preceding type)
--|(% style="width:141px" %)+|(% style="width:528px" %)at least one digit (of the preceding type)
--|(% style="width:141px" %)( )|(% style="width:528px" %)optional digits (specified within the brackets)
--|(% style="width:141px" %)\|(% style="width:528px" %)prefix for the special characters that must appear in the mask
--|(% style="width:141px" %)N|(% style="width:528px" %)fixed number of digits used in the preceding textual representation of the month or the day
--|(% style="width:141px" %) |(% style="width:528px" %)
++|(% colspan="2" %)**VTL special characters for the formatting masks**
++|(% colspan="2" %)** **
++|(% colspan="2" %)**Number **
++|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
++|E|one numeric digit (for the exponent of the scientific notation)
++|.    (dot)|possible separator between the integer and the decimal parts.
++|,   (comma)|possible separator between the integer and the decimal parts.
++| |
++|(% colspan="2" %)**Time and duration**
++|C |century
++|Y|year
++|S|semester
++|Q|quarter
++|M|month
++|W|week
++|D|day
++|h |hour digit (by default on 24 hours)
++|M|minute
++|S|second
++|D|decimal of second
++|P|period indicator (representation in one digit for the duration)
++|P|number of the periods specified in the period indicator
++|AM/PM |indicator of AM / PM (e.g. am/pm for “am” or “pm”)
++|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
++|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
++|Month|lowercase textual representation of the month (e.g., january)
++|Day|lowercase textual representation of the month (e.g., monday)
++|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
++|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
++| |
++|(% colspan="2" %)**String  **
++|X|any string character
++|Z|any string character from “A” to “z”
++|9|any string character from “0” to “9”
++| |
++|(% colspan="2" %)**Boolean **
++|B|Boolean using “true” for True and “false” for False
++|1|Boolean using “1” for True and “0” for False
++|0|Boolean using “0” for True and “1” for False
++| |
++|(% colspan="2" %)Other qualifiers
++|*|an arbitrary number of digits (of the preceding type)
++|+|at least one digit (of the preceding type)
++|( )|optional digits (specified within the brackets)
++|\|prefix for the special characters that must appear in the mask
++|N|fixed number of digits used in the preceding  textual representation of the month or the day
++| |
--The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[43~]^^>>path:#_ftn43]](%%).
++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]].
  === 10.4.5 Null Values ===
@@ -1919,20 +1919,22 @@
  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.
++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.
  === 10.4.6 Format of the literals used in VTL transformations ===
  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.
--Given this discretion, it is essential to know which are the external representations adopted for the literals in a VTL program, in order to interpret them correctly. For example, if the external format for the dates is YYYY-MM-DD the date literal 201001-02 has the meaning of 2^^nd^^ January 2010, instead if the external format for the dates is YYYY-DD-MM the same literal has the meaning of 1^^st^^ February 2010.
++Given this discretion, it is essential to know which are the external representations adopted for the literals in a VTL program, in order to interpret them correctly.  For example, if the external format for the dates is YYYY-MM-DD the date literal 201001-02 has the meaning of 2^^nd^^ January 2010, instead if the external format for the dates is YYYY-DD-MM the same literal has the meaning of 1^^st^^ February 2010.
  Hereinafter, i.e. in the SDMX implementation of the VTL, it is assumed that the literals are expressed according to the “default output format” of the table of the previous paragraph (“Mapping VTL basic scalar types to SDMX data types”) unless otherwise specified.
  A different format can be specified in the attribute “vtlLiteralFormat” of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model).
--Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL TransformationScheme.
++Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL
++TransformationScheme.
++
  In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
  = 11 Annex I: How to eliminate extra element in the .NET SDMX Web Service =
@@ -1941,18 +1941,12 @@
  For implementing an SDMX compliant Web Service the standardised WSDL file should be used that describes the expected request/response structure. The request message of the operation contains a wrapper element (e.g. “GetGenericData”) that wraps a tag called “GenericDataQuery”, which is the actual SDMX query XML message that contains the query to be processed by the Web Service. In the same way the response is formulated in a wrapper element “GetGenericDataResponse”.
--As defined in the SOAP specification, the root element of a SOAP message is the Envelope, which contains an optional Header and a mandatory Body. These are illustrated below along with the Body contents according to the WSDL:
++As defined in the SOAP specification, the root element of a SOAP message is the Envelope, which contains an optional Header and a mandatory Body. These are illustrated below along with the Body contents according to the WSDL:
--[[image:1747854006117-843.png]]
--
  The problem that initiated the present analysis refers to the difference in the way SOAP requests are when trying to implement the aforementioned Web Service in .NET framework.
  Building such a Web Service using the .NET framework is done by exposing a method (i.e. the getGenericData in the example) with an XML document argument (lets name it “Query”). **The difference that appears in Microsoft .Net implementations is that there is a need for an extra XML container around the SDMX GenericDataQuery.** This is the expected behavior since the framework is let to publish automatically the Web Service as a remote procedure call, thus wraps each parameter into an extra element. The .NET request is illustrated below:
--[[image:1747854039499-443.png]]
--
--[[image:1747854067769-691.png]]
--
  Furthermore this extra element is also inserted in the automatically generated WSDL from the framework. Therefore this particularity requires custom clients for the .NET Web Services that is not an interoperable solution.
  == 11.2 Solution ==
@@ -1973,30 +1973,20 @@
  To understand how the **XmlAnyElement** attribute works we present the following two web methods:
--[[image:1747854096778-844.png]]
++In this method the **input** parameter is decorated with the **XmlAnyElement** parameter. This is a hint that this parameter will be de-serialized from an **xsd:any** element. Since the attribute is not passed any parameters, it means that the entire XML element for this parameter in the SOAP message will be in the Infoset that is represented by this **XmlElement** parameter.
--In this method the **input** parameter is decorated with the **XmlAnyElement** parameter. This is a hint that this parameter will be de-serialized from an **xsd:any** element. Since the attribute is not passed any parameters, it means that the entire XML element for this parameter in the SOAP message will be in the Infoset that is represented by this **XmlElement** parameter.
++The difference between the two is that for the first method, **SubmitXml**, the
--[[image:1747854127303-270.png]]
++XmlSerializer will expect an element named **input** to be an immediate child of the **SubmitXml** element in the SOAP body. The second method, **SubmitXmlAny**, will not care what the name of the child of the **SubmitXmlAny** element is. It will plug whatever XML is included into the input parameter. The message style from ASP.NET Help for the two methods is shown below. First we look at the message for the method without the **XmlAnyElement** attribute.
--The difference between the two is that for the first method, **SubmitXml**, the XmlSerializer will expect an element named **input** to be an immediate child of the **SubmitXml** element in the SOAP body. The second method, **SubmitXmlAny**, will not care what the name of the child of the **SubmitXmlAny** element is. It will plug whatever XML is included into the input parameter. The message style from ASP.NET Help for the two methods is shown below. First we look at the message for the method without the **XmlAnyElement** attribute.
--
--[[image:1747854163928-581.png]]
--
  Now we look at the message for the method that uses the **XmlAnyElement** attribute.
--[[image:1747854190641-364.png]]
--
--[[image:1747854236732-512.png]]
--
  The method decorated with the **XmlAnyElement** attribute has one fewer wrapping elements. Only an element with the name of the method wraps what is passed to the **input** parameter.
--For more information please consult: [[http:~~/~~/msdn.microsoft.com/en-us/library/aa480498.aspx>>http://msdn.microsoft.com/en-us/library/aa480498.aspx]]
++For more information please consult:  [[http:~~/~~/msdn.microsoft.com/en>>url:http://msdn.microsoft.com/en-us/library/aa480498.aspx]][[->>url:http://msdn.microsoft.com/en-us/library/aa480498.aspx]][[us/library/aa480498.aspx>>url:http://msdn.microsoft.com/en-us/library/aa480498.aspx]][[url:http://msdn.microsoft.com/en-us/library/aa480498.aspx]]
  Furthermore at this point the problem with the different requests has been solved. However there is still the difference in the produced WSDL that has to be taken care. The automatic generated WSDL now doesn’t insert the extra element, but defines the content of the operation wrapper element as “xsd:any” type.
--[[image:1747854286398-614.png]]
--
  Without a common WSDL still the solution doesn’t enforce interoperability. In order to
  “fix” the WSDL, there two approaches. The first is to intervene in the generation process. This is a complicated approach, compared to the second approach, which overrides the generation process and returns the envisioned WSDL for the SDMX Web Service.
@@ -2009,27 +2009,16 @@
  In the context of the SDMX Web Service, applying the above solution translates into the following:
--[[image:1747854385465-132.png]]
--
  The SOAP request/response will then be as follows:
  **GenericData Request**
--[[image:1747854406014-782.png]]
--
  **GenericData Response**
--[[image:1747854424488-855.png]]
--
  For overriding the automatically produced WSDL, in the solution explorer right click the project and select “Add” -> “New item…”. Then select the “Global Application Class”. This will create “.asax” class file in which the following code should replace the existing empty method:
--[[image:1747854453895-524.png]]
--
--[[image:1747854476631-125.png]]
--
  The SDMX_WSDL.wsdl should reside in the in the root directory of the application. After applying this solution the returned WSDL is the envisioned. Thus in the request message definition contains:
--[[image:1747854493363-776.png]]
  ----
@@ -2057,15 +2057,15 @@
  [[~[12~]>>path:#_ftnref12]] 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, MeasureDimension, TimeDimension, PrimaryMeasure or DataAttribute) can be deduced from the data structure of the SDMX Dataflow which the component belongs to.
++VTL data set (SDMX dataflow), the specific SDMX class-name (e.g. Dimension, MeasureDimension, TimeDimension, PrimaryMeasure or DataAttribute) can be deduced from the data structure of the SDMX Dataflow which the component belongs to.
--[[~[13~]>>path:#_ftnref13]] 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)
++[[~[13~]>>path:#_ftnref13]] 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)
  [[~[14~]>>path:#_ftnref14]] Single quotes are needed because this reference is not a VTL regular name.
  [[~[15~]>>path:#_ftnref15]] Single quotes are not needed in this case because CL_FREQ is a VTL regular name.
--[[~[16~]>>path:#_ftnref16]] The result DFR(1.0) is be equal to DF1(1.0) save that the component SECTOR is called SEC
++[[~[16~]>>path:#_ftnref16]] The result DFR(1.0)  is be equal to DF1(1.0) save that the component SECTOR is called SEC
  [[~[17~]>>path:#_ftnref17]] Rulesets of this kind cannot be reused when the referenced Concept has a different representation.
@@ -2081,7 +2081,7 @@
  [[~[23~]>>path:#_ftnref23]] The SDMX community is evaluating the opportunity of allowing more than one measure component in a DataStructureDefinition in the next SDMX major version.
--[[~[24~]>>path:#_ftnref24]] If future SDMX major versions will allow multi-measures data structures, this method is expected to become applicable even if the VTL data structure has more than one measure
++[[~[24~]>>path:#_ftnref24]] If future SDMX major versions will allow multi-measures data structures, this method is expected to  become applicable even if the VTL data structure has more than one measure
  [[~[25~]>>path:#_ftnref25]] The kind of mapping explained here works in combination with a SDMX specific naming convention that requires pre-processing before parsing the VTL expressions. As highlighted below, the identifiers of the VTL datasets are a shortcut of some specific VTL operators applied to the SDMX Dataflows. This is not safe to use outside an SDMX context, as the naming convention may have no meaning there.
@@ -2089,7 +2089,7 @@
  [[~[27~]>>path:#_ftnref27]] 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 datasets.
--[[~[28~]>>path:#_ftnref28]] This definition is made through the ToVtlSubspace and ToVtlSpaceKey classes and/or the FromVtlSuperspace and FromVtlSpaceKey classes, depending on the direction of the mapping (“key” means “dimension”). The mapping of Dataflow subsets can be applied independently in the two directions, also according to different Dimensions. When no Dimension is declared for a given direction, it is assumed that the option of mapping different parts of a SDMX Dataflow to different VTL datasets is not used.
++[[~[28~]>>path:#_ftnref28]] This definition is made through the ToVtlSubspace and ToVtlSpaceKey classes and/or the FromVtlSuperspace  and FromVtlSpaceKey classes, depending on the direction of the mapping (“key” means “dimension”). The mapping of Dataflow subsets can be applied independently in the two directions, also according to different Dimensions.  When no Dimension is declared for a given direction, it is assumed that the option of mapping different parts of a SDMX Dataflow to different VTL datasets is not used.
  [[~[29~]>>path:#_ftnref29]] As a consequence of this formalism, a slash in the name of the VTL dataset assumes the specific meaning of separator between the name of the Dataflow and the values of some of its Dimensions.
@@ -2097,13 +2097,13 @@
  [[~[31~]>>path:#_ftnref31]] It should be remembered that, according to the VTL consistency rules, a given VTL dataset cannot be the result of more than one VTL transformation.
--[[~[32~]>>path:#_ftnref32]] If these dimensions would not be dropped, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching identifiers, the VTL datasets resulting from this kind of mapping would have non-matching values for the mapping dimensions (e.g. POPULATION and COUNTRY), therefore 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). ^^ ^^
++[[~[32~]>>path:#_ftnref32]] If these dimensions would not be dropped, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching identifiers, the VTL datasets resulting from this kind of mapping would have non-matching values for the mapping dimensions (e.g. POPULATION and COUNTRY), therefore 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). ^^ ^^
--[[~[33~]>>path:#_ftnref33]] In case the ordered concatenation notation is used, the VTL Transformation described above, e.g.
++[[~[33~]>>path:#_ftnref33]] 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 and, 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.
++‘DF1(1.0)/POPULATION.USA’ :=  DF1(1.0) [ sub  INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed and, 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.
--[[~[34~]>>path:#_ftnref34]] If the whole DF2(1.0) is calculated by means of just one VTL transformation, then the mapping between the SDMX dataflow and the corresponding VTL dataset is one-to-one and this kind of mapping (one SDMX Dataflow to many VTL datasets) does not apply..
++[[~[34~]>>path:#_ftnref34]] If the whole DF2(1.0) is calculated by means of just one VTL transformation,  then the mapping between the SDMX dataflow and the corresponding VTL dataset is one-to-one and this kind of mapping (one SDMX Dataflow to many VTL datasets) does not apply..
  [[~[35~]>>path:#_ftnref35]] This is possible as each VTL dataset corresponds to one particular combination of values of INDICATOR and COUNTRY
@@ -2122,5 +2122,3 @@
  [[~[42~]>>path:#_ftnref42]] A Concept becomes a Component in a DataStructureDefinition, and Components can have different LocalRepresentations in different DataStructureDefinitions, also overriding the (possible) base representation of the Concept.
  [[~[43~]>>path:#_ftnref43]] The representation given in the DSD should obviously be compatible with the VTL data type.
--
--{{putFootnotes/}}

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