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

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...	...	@@ -41,7 +41,7 @@
41	41
42	42	=== 3.2.1 Introduction ===
43	43
44		-The purpose of this sub-section is to provide an introduction to the SDMX-IM relating to Data Structure Definitions and Data Sets for those whose primary interest is in the use of the XML or EDI formats.  For those wishing to have a deeper understanding of the Information Model, the full SDMX-IM document, and other sections in this guide provide a more in-depth view, along with UML diagrams and supporting explanation. For those who are unfamiliar with DSDs, an appendix to the SDMX-IM provides a tutorial which may serve as a useful introduction.
	44	+The purpose of this sub-section is to provide an introduction to the SDMX-IM relating to Data Structure Definitions and Data Sets for those whose primary interest is in the use of the XML or EDI formats. For those wishing to have a deeper understanding of the Information Model, the full SDMX-IM document, and other sections in this guide provide a more in-depth view, along with UML diagrams and supporting explanation. For those who are unfamiliar with DSDs, an appendix to the SDMX-IM provides a tutorial which may serve as a useful introduction.
45	45
46	46	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.
47	47
...	...	@@ -69,13 +69,13 @@
69	69
70	70	To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages; //GenericTimeSeriesData// and //StructureSpecificTimeSeriesData//. It is important to note that these variations are built on the same root structure and can be processed in the same manner as the base format so that they do NOT introduce additional processing requirements.
71	71
72		-=== //Structure Definition// ===
	72	+**//Structure Definition//**
73	73
74	74	The SDMX-ML Structure Message supports the use of annotations to the structure, which is not supported by the SDMX-EDI syntax.
75	75
76	76	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.
77	77
78		-=== //Validation// ===
	78	+**//Validation//**
79	79
80	80	SDMX-EDI – as is typical of EDIFACT syntax messages – leaves validation to dedicated applications (“validation” being the checking of syntax, data typing, and adherence of the data message to the structure as described in the structural definition.)
81	81
...	...	@@ -83,19 +83,19 @@
83	83
84	84	The SDMX-ML DSD-specific messages will allow validation of XML syntax and datatyping to be performed with a generic XML parser, and enforce agreement between the structural definition and the data to a moderate degree with the same tool.
85	85
86		-=== //Update and Delete Messages and Documentation Messages// ===
	86	+//Update and Delete Messages and Documentation Messages//
87	87
88	88	All SDMX data messages allow for both delete messages and messages consisting of only data or only documentation.
89	89
90		-=== //Character Encodings// ===
	90	+**//Character Encodings//**
91	91
92	92	All SDMX-ML messages use the UTF-8 encoding, while SDMX-EDI uses the ISO 8879-1 character encoding. There is a greater capacity with UTF-8 to express some character sets (see the “APPENDIX: MAP OF ISO 8859-1 (UNOC) CHARACTER SET (LATIN 1 OR “WESTERN”) in the document “SYNTAX AND DOCUMENTATION VERSION 2.0”.) Many transformation tools are available which allow XML instances with UTF-8 encodings to be expressed as ISO 8879-1-encoded characters, and to transform UTF-8 into ISO 8879-1. Such tools should be used when transforming SDMX-ML messages into SDMX-EDI messages and vice-versa.
93	93
94		-=== //Data Typing// ===
	94	+**//Data Typing//**
95	95
96	96	The XML syntax and EDIFACT syntax have different data-typing mechanisms. The section below provides a set of conventions to be observed when support for messages in both syntaxes is required. For more information on the SDMX-ML representations of data, see below.
97	97
98		-==== 3.3.2 Data Types ====
	98	+=== 3.3.2 Data Types ===
99	99
100	100	The XML syntax has a very different mechanism for data-typing than the EDIFACT syntax, and this difference may create some difficulties for applications which support both EDIFACT-based and XML-based SDMX data formats. This section provides a set of conventions for the expression in data in all formats, to allow for clean interoperability between them.
101	101
...	...	@@ -145,7 +145,7 @@
145	145
146	146	==== 3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges ====
147	147
148		-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.
	148	+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.
149	149
150	150	Central institutions can play a double role:
151	151
...	...	@@ -159,13 +159,13 @@
159	159	(% class="wikigeneratedid" id="HDimensions2CAttributesandCodeLists" %)
160	160	__Dimensions, Attributes and Code Lists__
161	161
162		-**//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.
	162	+**//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.
163	163
164	164	**//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.
165	165
166		-**//Avoid composite dimensions.//**  Each dimension should correspond to a single characteristic of the data, not to a combination of characteristics.
	166	+**//Avoid composite dimensions.//** Each dimension should correspond to a single characteristic of the data, not to a combination of characteristics.
167	167
168		-**//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:
	168	+**//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:
169	169
170	170	* A descriptive title for the series (this is most useful for dissemination of data for viewing e.g. on the web)
171	171	* Collection (e.g. end of period, averaged or summed over period)
...	...	@@ -187,7 +187,6 @@
187	187
188	188	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.
189	189
190		-(% class="wikigeneratedid" id="HDataStructureDefinitionStructure" %)
191	191	__Data Structure Definition Structure__
192	192
193	193	The following items have to be specified by a structural definitions maintenance agency when defining a new data structure definition:
...	...	@@ -231,7 +231,7 @@
231	231
232	232	//Static properties//.
233	233
234		-* 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.
	233	+* 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.
235	235	* A centre may agree with its data exchange partners special procedures for authorising the setting of attributes' initial values.
236	236	* Attribute values at a data set level are set and maintained exclusively by the centre administrating the exchanged data set.
237	237
...	...	@@ -238,7 +238,7 @@
238	238	//Communication of changes// to the centre.
239	239
240	240	* 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.
241		-* 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.
	240	+* 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.
242	242	* A centre may agree with its data exchange partners special procedures for authorising modifications in the attribute values.
243	243
244	244	Communication of observation level attributes “observation status”, "observation confidentiality", "observation pre-break".
...	...	@@ -282,7 +282,7 @@
282	282
283	283	= 4 General Notes for Implementers =
284	284
285		-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.
	284	+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.
286	286
287	287	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.
288	288
...	...	@@ -325,7 +325,7 @@
325	325	* ExclusiveValueRange (xs:decimal with the minValue and maxValue facets supplying the bounds)
326	326	* Incremental (xs:decimal with a specified interval; the interval is typically enforced outside of the XML validation)
327	327	* TimeRange (common:TimeRangeType, start DateTime + Duration,)
328		-* ObservationalTimePeriod (common: ObservationalTimePeriodType,  a union of StandardTimePeriod and TimeRange).
	327	+* ObservationalTimePeriod (common: ObservationalTimePeriodType, a union of StandardTimePeriod and TimeRange).
329	329	* StandardTimePeriod (common: StandardTimePeriodType, a union of BasicTimePeriod and TimeRange).
330	330	* BasicTimePeriod (common: BasicTimePeriodType, a union of GregorianTimePeriod and DateTime)
331	331	* GregorianTimePeriod (common:GregorianTimePeriodType, a union of GregorianYear, GregorianMonth, and GregorianDay)
...	...	@@ -409,7 +409,7 @@
409	409
410	410	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.
411	411
412		-Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
	411	+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" %)^^~[1~]^^>>path:#_ftn1]]
413	413
414	414	=== 4.2.6 Standard Reporting Period ===
415	415
...	...	@@ -458,7 +458,7 @@
458	458	Period Duration: P7D (seven days)
459	459	Limit per year: 53
460	460	Representation: common:ReportingWeekType (YYYY-Www, e.g. 2000-W53)
461		-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" %)^^~[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.
	460	+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" %)^^~[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.
462	462
463	463	**Reporting Day**:
464	464	Period Indicator: D
...	...	@@ -481,7 +481,7 @@
481	481	~1. If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
482	482	Add^^3^^ (P3D, P2D, or P1D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE].
483	483
484		-​​​​​​​2. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
	483	+2. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
485	485	Add^^3^^ (P0D, -P1D, -P2D, or -P3D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE].
486	486	b) **Else:**
487	487	The [REPORTING_YEAR_START_DATE] is the [REPORTING_YEAR_BASE]
...	...	@@ -497,106 +497,86 @@
497	497	g) If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D.
498	498
499	499	**3. Determine [PERIOD_START]:**
500		-Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
	499	+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" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
501	501
502		-1. **Determine the [PERIOD_END]:**
503		-
	501	+**4. Determine the [PERIOD_END]:**
504	504	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].
505	505
506	506	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).
507	507
508		-**Examples: **
	506	+**Examples:**
509	509
510	510	**2010-Q2, REPORTING_YEAR_START_DAY = ~-~-07-01 (July 1)**
511		-
512	512	~1. [REPORTING_YEAR_START_DATE] = 2010-07-01
513		-
514	514	b) [REPORTING_YEAR_BASE] = 2010-07-01
515		-
516		-1. [PERIOD_DURATION] = P3M
517		-1. (2-1) * P3M = P3M
518		-
	511	+[PERIOD_DURATION] = P3M
	512	+(2-1) * P3M = P3M
519	519	2010-07-01 + P3M = 2010-10-01
520		-
521	521	[PERIOD_START] = 2010-10-01
522		-
523	523	4. 2 * P3M = P6M
524		-
525	525	2010-07-01 + P6M = 2010-13-01 = 2011-01-01
526		-
527	527	2011-01-01 + -P1D = 2010-12-31
528		-
529	529	[PERIOD_END] = 2011-12-31
530	530
531	531	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
532	532
533	533	**2011-W36, REPORTING_YEAR_START_DAY = ~-~-07-01 (July 1)**
534		-
535	535	~1. [REPORTING_YEAR_START_DATE] = 2010-07-01
536		-
537	537	a) 2011-07-01 = Friday
538		-
539	539	2011-07-01 + P3D = 2011-07-04
540		-
541	541	[REPORTING_YEAR_BASE] = 2011-07-04
542		-
543		-1. [PERIOD_DURATION] = P7D
544		-1. (36-1) * P7D = P245D
545		-
	527	+2. [PERIOD_DURATION] = P7D
	528	+3. (36-1) * P7D = P245D
546	546	2011-07-04 + P245D = 2012-03-05
547		-
548	548	[PERIOD_START] = 2012-03-05
549		-
550	550	4. 36 * P7D = P252D
551		-
552	552	2011-07-04 + P252D =2012-03-12
553		-
554	554	2012-03-12 + -P1D = 2012-03-11
555		-
556	556	[PERIOD_END] = 2012-03-11
557	557
558	558	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
559	559
560		-==== 4.2.7 Distinct Range ====
	538	+=== 4.2.7 Distinct Range ===
561	561
562	562	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.
563	563
564		-==== 4.2.8 Time Format ====
	542	+=== 4.2.8 Time Format ===
565	565
566		-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.
	544	+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.
567	567
568		-|**Code**|**Format**
569		-|**OTP**|Observational Time Period: Superset of all SDMX time formats (Gregorian Time Period, Reporting Time Period, and Time Range)
570		-|**STP**|Standard Time Period: Superset of Gregorian and Reporting Time Periods
571		-|**GTP**|Superset of all Gregorian Time Periods and date-time
572		-|**RTP**|Superset of all Reporting Time Periods
573		-|**TR**|Time Range: Start time and duration (YYYY-MMDD(Thh:mm:ss)?/<duration>)
574		-|**GY**|Gregorian Year (YYYY)
575		-|**GTM**|Gregorian Year Month (YYYY-MM)
576		-|**GD**|Gregorian Day (YYYY-MM-DD)
577		-|**DT**|Distinct Point: date-time (YYYY-MM-DDThh:mm:ss)
578		-|**RY**|Reporting Year (YYYY-A1)
579		-|**RS**|Reporting Semester (YYYY-Ss)
580		-|**RT**|Reporting Trimester (YYYY-Tt)
581		-|**RQ**|Reporting Quarter (YYYY-Qq)
582		-|**RM**|Reporting Month (YYYY-Mmm)
583		-|**Code**|**Format**
584		-|**RW**|Reporting Week (YYYY-Www)
585		-|**RD**|Reporting Day (YYYY-Dddd)
	546	+(% style="width:716.835px" %)
	547	+|(% style="width:197px" %)**Code**|(% style="width:517px" %)**Format**
	548	+|(% 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)
	549	+|(% style="width:197px" %)**STP**|(% style="width:517px" %)Standard Time Period: Superset of Gregorian and Reporting Time Periods
	550	+|(% style="width:197px" %)**GTP**|(% style="width:517px" %)Superset of all Gregorian Time Periods and date-time
	551	+|(% style="width:197px" %)**RTP**|(% style="width:517px" %)Superset of all Reporting Time Periods
	552	+|(% style="width:197px" %)**TR**|(% style="width:517px" %)Time Range: Start time and duration (YYYY-MMDD(Thh:mm:ss)?/<duration>)
	553	+|(% style="width:197px" %)**GY**|(% style="width:517px" %)Gregorian Year (YYYY)
	554	+|(% style="width:197px" %)**GTM**|(% style="width:517px" %)Gregorian Year Month (YYYY-MM)
	555	+|(% style="width:197px" %)**GD**|(% style="width:517px" %)Gregorian Day (YYYY-MM-DD)
	556	+|(% style="width:197px" %)**DT**|(% style="width:517px" %)Distinct Point: date-time (YYYY-MM-DDThh:mm:ss)
	557	+|(% style="width:197px" %)**RY**|(% style="width:517px" %)Reporting Year (YYYY-A1)
	558	+|(% style="width:197px" %)**RS**|(% style="width:517px" %)Reporting Semester (YYYY-Ss)
	559	+|(% style="width:197px" %)**RT**|(% style="width:517px" %)Reporting Trimester (YYYY-Tt)
	560	+|(% style="width:197px" %)**RQ**|(% style="width:517px" %)Reporting Quarter (YYYY-Qq)
	561	+|(% style="width:197px" %)**RM**|(% style="width:517px" %)Reporting Month (YYYY-Mmm)
	562	+|(% style="width:197px" %)**Code**|(% style="width:517px" %)**Format**
	563	+|(% style="width:197px" %)**RW**|(% style="width:517px" %)Reporting Week (YYYY-Www)
	564	+|(% style="width:197px" %)**RD**|(% style="width:517px" %)Reporting Day (YYYY-Dddd)
586	586
587		- **Table 1: SDMX-ML Time Format Codes**
	566	+**Table 1: SDMX-ML Time Format Codes**
588	588
589		-==== 4.2.9 Transformation between SDMX-ML and SDMX-EDI ====
	568	+=== 4.2.9 Transformation between SDMX-ML and SDMX-EDI ===
590	590
591	591	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".
592	592
593		-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)
	572	+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).
594	594
595	595	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.
596	596
597	597	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.
598	598
599		-==== 4.2.10 Time Zones ====
	578	+=== 4.2.10 Time Zones ===
600	600
601	601	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):
602	602
...	...	@@ -617,40 +617,39 @@
617	617
618	618	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.
619	619
620		-==== 4.2.11 Representing Time Spans Elsewhere ====
	599	+=== 4.2.11 Representing Time Spans Elsewhere ===
621	621
622	622	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:
623	623
624		- <Series REF_PERIODStartTime="2000-01-01T00:00:00" REF_PERIOD="P2M"/>
	603	+<Series REF_PERIODStartTime="2000-01-01T00:00:00" REF_PERIOD="P2M"/>
625	625
626	626	can now be represented with this:
627	627
628	628	<Series REF_PERIOD="2000-01-01T00:00:00/P2M"/>
629	629
630		-==== 4.2.12 Notes on Formats ====
	609	+=== 4.2.12 Notes on Formats ===
631	631
632	632	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.
633	633
634		-==== 4.2.13 Effect on Time Ranges ====
	613	+=== 4.2.13 Effect on Time Ranges ===
635	635
636	636	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.
637	637
638		-==== 4.2.14 Time in Query Messages ====
	617	+=== 4.2.14 Time in Query Messages ===
639	639
640	640	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.
641	641
642	642	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.
643	643
644		-|**Operator**|**Rule**
645		-|Greater Than|Any data after the last moment of the period
646		-|Less Than|Any data before the first moment of the period
647		-|Greater Than or Equal To|(((
648		-Any data on or after the first moment of
649		-
650		-the period
	623	+(% style="width:1024.29px" %)
	624	+|(% style="width:238px" %)**Operator**|(% style="width:782px" %)**Rule**
	625	+|(% style="width:238px" %)Greater Than|(% style="width:782px" %)Any data after the last moment of the period
	626	+|(% style="width:238px" %)Less Than|(% style="width:782px" %)Any data before the first moment of the period
	627	+|(% style="width:238px" %)Greater Than or Equal To|(% style="width:782px" %)(((
	628	+Any data on or after the first moment of the period
651	651	)))
652		-|Less Than or Equal To|Any data on or before the last moment of the period
653		-|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
	630	+|(% style="width:238px" %)Less Than or Equal To|(% style="width:782px" %)Any data on or before the last moment of the period
	631	+|(% 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
654	654
655	655	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":
656	656
...	...	@@ -663,9 +663,7 @@
663	663	**Examples:**
664	664
665	665	**Gregorian Period**
666		-
667	667	Query Parameter: Greater than 2010
668		-
669	669	Literal Interpretation: Any data where the start period occurs after 2010-1231T23:59:59.
670	670
671	671	Example Matches:
...	...	@@ -683,15 +683,11 @@
683	683	* 2010-D185 or later (reporting year start day ~-~-07-01 or later)
684	684
685	685	**Reporting Period with explicit start day**
686		-
687	687	Query Parameter: Greater than or equal to 2009-Q3, reporting year start day = "-07-01"
688		-
689	689	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
690	690
691	691	**Reporting Period with "Any" start day**
692		-
693	693	Query Parameter: Greater than or equal to 2010-Q3, reporting year start day = "Any"
694		-
695	695	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:
696	696
697	697	* 2011 or later
...	...	@@ -703,13 +703,10 @@
703	703	* 2010-T3 (any reporting year start day)
704	704	* 2010-Q3 or later (any reporting year start day)
705	705	* 2010-M07 or later (any reporting year start day)
706		-* 2010-W27 or later (reporting year start day ~-~-01-01)^^4^^  2010-D182 or later (reporting year start day ~-~-01-01)
707		-* 2010-W28 or later (reporting year start day ~-~-07-01)^^5^^
	678	+* 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)
	679	+* 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}}
	680	+* 2010-D185 or later (reporting year start day ~-~-07-01)
708	708
709		-^^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.
710		-
711		- 2010-D185 or later (reporting year start day ~-~-07-01)
712		-
713	713	== 4.3 Structural Metadata Querying Best Practices ==
714	714
715	715	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.
...	...	@@ -726,8 +726,6 @@
726	726
727	727	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.
728	728
729		-^^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.
730		-
731	731	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.
732	732
733	733	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.
...	...	@@ -750,13 +750,13 @@
750	750
751	751	[[image:1747836776649-282.jpeg]]
752	752
753		-1. **1: Schematic of the Metadata Structure Definition**
	720	+**Figure 1: Schematic of the Metadata Structure Definition**
754	754
755	755	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.
756	756
757	757	[[image:1747836776655-364.jpeg]]
758	758
759		-1. **2: Example MSD showing Metadata Targets**
	726	+**Figure 2: Example MSD showing Metadata Targets**
760	760
761	761	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.
762	762
...	...	@@ -766,8 +766,10 @@
766	766
767	767	[[image:1747836776658-510.jpeg]]
768	768
769		-**Figure 3: Example MSD showing specification of three Metadata Attributes **This example shows the following hierarchy of Metadata Attributes:
	736	+**Figure 3: Example MSD showing specification of three Metadata Attributes**
770	770
	738	+This example shows the following hierarchy of Metadata Attributes:
	739	+
771	771	Source – this is presentational and no metadata is expected to be reported at this level
772	772
773	773	* Source Type
...	...	@@ -779,12 +779,9 @@
779	779
780	780	[[image:1747836776677-246.jpeg]]
781	781
782		- **Figure 4: Example Metadata Set **This example shows:
	751	+**Figure 4: Example Metadata Set **This example shows:
783	783
784		-1. The reference to the MSD, Metadata Report, and Metadata Target
785		-
786		-(MetadataTargetValue)
787		-
	753	+1. The reference to the MSD, Metadata Report, and Metadata Target (MetadataTargetValue)
788	788	1. The reported metadata attributes (AttributeValueSet)
789	789
790	790	= 6 Maintenance Agencies =
...	...	@@ -805,7 +805,7 @@
805	805
806	806	[[image:1747836776680-229.jpeg]]
807	807
808		- **Figure 5: Example of Hierarchic Structure of Agencies**
	774	+**Figure 5: Example of Hierarchic Structure of Agencies**
809	809
810	810	Each agency is identified by its full hierarchy excluding SDMX.
811	811
...	...	@@ -841,10 +841,11 @@
841	841
842	842	The Information Model for this is shown below:
843	843
	810	+[[image:1747855024745-946.png]]
844	844
845		- **Figure 8: Information Model Extract for Concept Role**
	812	+**Figure 8: Information Model Extract for Concept Role**
846	846
847		-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.
	814	+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.
848	848
849	849	== 7.3 Technical Mechanism ==
850	850
...	...	@@ -862,15 +862,14 @@
862	862
863	863	The Cross-Domain Concept Scheme maintained by SDMX contains concept role concepts (FREQ chosen as an example).
864	864
865		-[[image:1747836776691-440.jpeg]]
	832	+[[image:1747855054559-410.png]]
866	866
867	867	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.
868	868
869	869	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.
870	870
871		-[[image:1747836776693-898.jpeg]]
	838	+[[image:1747855075263-887.png]]
872	872
873		-
874	874	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.
875	875
876	876	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.
...	...	@@ -918,7 +918,7 @@
918	918
919	919	== 8.3 Rules for a Content Constraint ==
920	920
921		-=== 8.3.1 Scope of a Content Constraint ===
	887	+=== 8.3.1 Scope of a Content Constraint ===
922	922
923	923	A Content Constraint is used specify the content of a data or metadata source in terms of the component values or the keys.
924	924
...	...	@@ -939,7 +939,7 @@
939	939	** IdentifiableObject
940	940	* Metadata Attribute
941	941
942		-The “key” is therefore the combination of the Target Objects that are defined for the  Metadata Target.
	908	+The “key” is therefore the combination of the Target Objects that are defined for the Metadata Target.
943	943
944	944	For a Constraint based on a DSD the Content Constraint can reference one or more of:
945	945
...	...	@@ -957,60 +957,60 @@
957	957
958	958	In view of the flexibility of constraints attachment, clear rules on their usage are required. These are elaborated below.
959	959
960		-=== 8.3.2 Multiple Content Constraints ===
	926	+=== 8.3.2 Multiple Content Constraints ===
961	961
962	962	There can be many Content Constraints for any Constrainable Artefact (e.g. DSD), subject to the following restrictions:
963	963
964		-**8.3.2.1 Cube Region**
	930	+==== 8.3.2.1 Cube Region ====
965	965
966	966	1. The constraint can contain multiple Member Selections (e.g. Dimension) but:
967		-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)
	933	+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)
968	968
969		-**8.3.2.2 Key Set**
	935	+==== 8.3.2.2 Key Set ====
970	970
971		-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.
	937	+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.
972	972
973		-=== 8.3.3 Inheritance of a Content Constraint ===
	939	+=== 8.3.3 Inheritance of a Content Constraint ===
974	974
975		-**8.3.3.1 Attachment levels of a Content Constraint**
	941	+==== 8.3.3.1 Attachment levels of a Content Constraint ====
976	976
977	977	There are three levels of constraint attachment for which these inheritance rules apply:
978	978
979		- DSD/MSD – top level o Dataflow/Metadataflow – second level
	945	+* DSD/MSD – top level
	946	+** Dataflow/Metadataflow – second level
	947	+*** Provision Agreement – third level
980	980
981		-§ Provision Agreement – third level
982		-
983	983	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).
984	984
985	985	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.
986	986
987		-**8.3.3.2 Cascade rules for processing Constraints**
	953	+==== 8.3.3.2 Cascade rules for processing Constraints ====
988	988
989	989	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.
990	990
991	991	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.
992	992
993		-**8.3.3.3 Cube Region**
	959	+==== 8.3.3.3 Cube Region ====
994	994
995	995	1. 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:
996		-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).
997		-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).
	962	+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).
	963	+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).
998	998	1. 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.
999	999	1. 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.
1000	1000
1001	1001	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.
1002	1002
1003		-**8.3.3.4 Key Set**
	969	+==== 8.3.3.4 Key Set ====
1004	1004
1005	1005	1. 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:
1006		-11. The lower level constraint cannot be less restrictive than the constraint specified at the higher level.
1007		-11. The constraint at the lower level for any one Member Selection further constrains the keys specified at the higher level(s).
	972	+a. The lower level constraint cannot be less restrictive than the constraint specified at the higher level.
	973	+b. The constraint at the lower level for any one Member Selection further constrains the keys specified at the higher level(s).
1008	1008	1. 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.
1009	1009	1. 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.
1010	1010
1011	1011	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.
1012	1012
1013		-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.
	979	+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.
1014	1014
1015	1015	1. Determine all possible keys that are valid at the higher level.
1016	1016	1. These keys are deemed to be inherited by the lower level constrained object, subject to the constraints specified at the lower level.
...	...	@@ -1018,11 +1018,11 @@
1018	1018	1. At the lower level inherit all keys that match with the higher level constraint.
1019	1019	1. If there are keys in the lower level constraint that are not inherited then the key is invalid (i.e. it is less restrictive).
1020	1020
1021		-**8.3.4 Constraints Examples**
	987	+=== 8.3.4 Constraints Examples ===
1022	1022
1023	1023	The following scenario is used.
1024	1024
1025		-=== DSD ===
	991	+__DSD__
1026	1026
1027	1027	This contains the following Dimensions:
1028	1028
...	...	@@ -1031,114 +1031,45 @@
1031	1031	* AGE – Age
1032	1032	* CAS – Current Activity Status
1033	1033
1034		-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.
	1000	+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.
1035	1035
	1002	+[[image:1747855493531-357.png]]
1036	1036
1037		-|(((
1038		-
1039		-)))
	1004	+**Figure 10: Example Scenario for Constraints**
1040	1040
1041		-|(((
1042		-
1043		-)))
1044		-
1045		-|(((
1046		-
1047		-)))
1048		-
1049		-|(((
1050		-**Figure**
1051		-)))
1052		-
1053		-|(((
1054		-**10**
1055		-)))
1056		-
1057		-|(((
1058		-**:**
1059		-)))
1060		-
1061		-|(((
1062		-**~ Example Sce**
1063		-)))
1064		-
1065		-|(((
1066		-**nario for Constraints**
1067		-)))
1068		-
1069		-|(((
1070		-**~ **
1071		-)))
1072		-
1073		-
1074		-
1075	1075	Constraints are declared as follows:
1076	1076
	1008	+[[image:1747855462293-368.png]]
1077	1077
1078		-|(((
1079		-
1080		-)))
	1010	+**Figure 11: Example Content Constraints**
1081	1081
1082		-|(((
1083		-
1084		-)))
1085		-
1086		-|(((
1087		-
1088		-)))
1089		-
1090		-|(((
1091		-**Figure**
1092		-)))
1093		-
1094		-|(((
1095		-**11**
1096		-)))
1097		-
1098		-|(((
1099		-**:**
1100		-)))
1101		-
1102		-|(((
1103		-**~ Example Content Constraints**
1104		-)))
1105		-
1106		-|(((
1107		-**~ **
1108		-)))
1109		-
1110		-
1111		-
1112	1112	**Notes:**
1113	1113
1114		-1. AGE is constrained for the DSD and is further restricted for the Dataflow
1115		-
1116		-CENSUS_CUBE1.
1117		-
	1014	+1. AGE is constrained for the DSD and is further restricted for the Dataflow CENSUS_CUBE1.
1118	1118	1. The same Constraint applies to both Provision Agreements.
1119	1119
1120	1120	The cascade rules elaborated above result as follows:
1121	1121
1122		-DSD
	1019	+__DSD__
1123	1123
1124	1124	~1. Constrained by eliminating code 001 from the code list for the AGE Dimension.
1125	1125
1126		-=== Dataflow CENSUS_CUBE1 ===
	1023	+__Dataflow CENSUS_CUBE1__
1127	1127
1128	1128	1. 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).
1129	1129	1. Restricts the CAS codes to 003 and 004.
1130	1130
1131		-=== Dataflow CENSUS_CUBE2 ===
	1028	+__Dataflow CENSUS_CUBE2__
1132	1132
1133	1133	1. Restricts the code list for the CAS Dimension to codes TOT and NAP.
1134	1134	1. Inherits the AGE constraint applied at the level of the DSD.
1135	1135
1136		-=== Provision Agreements CENSUS_CUBE1_IT ===
	1033	+__Provision Agreements CENSUS_CUBE1_IT__
1137	1137
1138	1138	1. Restricts the codes for the GEO Dimension to IT and its children.
1139		-1. Inherits the constraints from Dataflow CENSUS_CUBE1  for the AGE and CAS Dimensions.
	1036	+1. Inherits the constraints from Dataflow CENSUS_CUBE1 for the AGE and CAS Dimensions.
1140	1140
1141		-=== Provision Agreements CENSUS_CUBE2_IT ===
	1038	+__Provision Agreements CENSUS_CUBE2_IT__
1142	1142
1143	1143	1. Restricts the codes for the GEO Dimension to IT and its children.
1144	1144	1. Inherits the constraints from Dataflow CENSUS_CUBE2 for the CAS Dimension.
...	...	@@ -1146,17 +1146,17 @@
1146	1146
1147	1147	The constraints are defined as follows:
1148	1148
1149		-=== DSD Constraint ===
	1046	+__DSD Constraint__
1150	1150
1151	1151	[[image:1747836776698-720.jpeg]]
1152	1152
1153		-=== Dataflow Constraints ===
	1050	+__Dataflow Constraints__
1154	1154
1155	1155	[[image:1747836776701-360.jpeg]]
1156	1156
1157		-=== [[image:1747836776707-834.jpeg]] ===
	1054	+[[image:1747836776707-834.jpeg]]
1158	1158
1159		-=== Provision Agreement Constraint ===
	1056	+__Provision Agreement Constraint__
1160	1160
1161	1161	[[image:1747836776710-262.jpeg]]
1162	1162
...	...	@@ -1168,7 +1168,7 @@
1168	1168
1169	1169	== 9.2 Groups and Dimension Groups ==
1170	1170
1171		-=== 9.2.1 Issue ===
	1068	+=== 9.2.1 Issue ===
1172	1172
1173	1173	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.
1174	1174
...	...	@@ -1181,7 +1181,7 @@
1181	1181
1182	1182	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.
1183	1183
1184		-=== 9.2.3 Data ===
	1081	+=== 9.2.3 Data ===
1185	1185
1186	1186	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>.
1187	1187
...	...	@@ -1193,17 +1193,17 @@
1193	1193
1194	1194	== 10.1 Introduction ==
1195	1195
1196		-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" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
	1093	+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" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
1197	1197
1198		-* definition of validation and transformation algorithms, in order to specify how to calculate new data  from existing ones;
	1095	+* definition of validation and transformation algorithms, in order to specify how to calculate new data from existing ones;
1199	1199	* 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);
1200	1200	* compilation and execution of VTL algorithms, either interpreting the VTL transformations or translating them in whatever other computer language is deemed as appropriate.
1201	1201
1202		-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”).
	1099	+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”).
1203	1203
1204		-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).
	1101	+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).
1205	1205
1206		-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.
	1103	+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.
1207	1207
1208	1208	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.
1209	1209
...	...	@@ -1211,16 +1211,14 @@
1211	1211
1212	1212	=== 10.2.1 Introduction ===
1213	1213
1214		-The VTL can manipulate SDMX artefacts (or objects) by referencing them through pre-defined conventional names (aliases).
	1111	+The VTL can manipulate SDMX artefacts (or objects) by referencing them through pre-defined conventional names (aliases).
1215	1215
1216	1216	The alias of a SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name.
1217	1217
1218		-In any case, the aliases used in the VTL transformations have to be mapped to the
	1115	+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" %)^^~[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" %)^^~[6~]^^>>path:#_ftn6]](%%) to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
1219	1219
1220		-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" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%)  to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
	1117	+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.
1221	1221
1222		-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.
1223		-
1224	1224	The references through the URN and the abbreviated URN are described in the following paragraphs.
1225	1225
1226	1226	=== 10.2.2 References through the URN ===
...	...	@@ -1227,15 +1227,15 @@
1227	1227
1228	1228	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.
1229	1229
1230		-The SDMX URN[[(% class="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:^^ ^^
	1125	+The SDMX URN[[(% class="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:^^ ^^
1231	1231
1232		-* SDMXprefix
1233		-* SDMX-IM-package-name
1234		-* class-name
1235		-* agency-id
	1127	+* SDMXprefix
	1128	+* SDMX-IM-package-name
	1129	+* class-name
	1130	+* agency-id
1236	1236	* maintainedobject-id
1237	1237	* maintainedobject-version
1238		-* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
	1133	+* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
1239	1239	* object-id
1240	1240
1241	1241	The generic structure of the URN is the following:
...	...	@@ -1246,7 +1246,7 @@
1246	1246
1247	1247	The **SDMX prefix** is “urn:sdmx:org”, always the same for all SDMX artefacts.
1248	1248
1249		-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”.
	1144	+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”.
1250	1250
1251	1251	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,,,
1252	1252
...	...	@@ -1254,13 +1254,13 @@
1254	1254
1255	1255	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).
1256	1256
1257		-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" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
	1152	+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" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
1258	1258
1259		-* if the artefact is a ,,Dataflow,,, which is a maintainable class,  the maintainedobject-id is the Dataflow name (dataflow-id);
1260		-* 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;
1261		-* 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;
1262		-* if the artefact is a ,,ConceptScheme,,, which is a maintainable class, ,, ,,the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id);
1263		-* if the artefact is a ,,Codelist, ,,which is a maintainable class,  the maintainedobject-id is the Codelist name (codelist-id).
	1154	+* if the artefact is a Dataflow, which is a maintainable class, the maintainedobject-id is the Dataflow name (dataflow-id);
	1155	+* 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;
	1156	+* 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;
	1157	+* if the artefact is a ConceptScheme, which is a maintainable class, ,, ,,the maintainedobject-id is the name of the ConceptScheme (conceptScheme-id);
	1158	+* if the artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the Codelist name (codelist-id).
1264	1264
1265	1265	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).
1266	1266
...	...	@@ -1268,18 +1268,13 @@
1268	1268
1269	1269	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:
1270	1270
1271		-* if the artefact is a Dimension, MeasureDimension, TimeDimension, PrimaryMeasure or DataAttribute  (the object-id is the name of one of
	1166	+* 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)
	1167	+* if the artefact is a Concept (the object-id is the name of the Concept)
1272	1272
1273		-the artefacts above, which are data structure components)
	1169	+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" %)^^~[10~]^^>>path:#_ftn10]](%%):
1274	1274
1275		-* if the artefact is a ,,Concept ,,(the object-id is the name of the ,,Concept,,)
1276		-
1277		-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" %)^^~[10~]^^>>path:#_ftn10]](%%):
1278		-
1279	1279	‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  <-
1280		-
1281		-‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’   +
1282		-
	1172	+‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’  +
1283	1283	‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0)’
1284	1284
1285	1285	=== 10.2.3 Abbreviation of the URN ===
...	...	@@ -1289,52 +1289,50 @@
1289	1289	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.
1290	1290
1291	1291	* 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.
1292		-* 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:
1293		-** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,
1294		-** “conceptscheme” for the classes Concept and ConceptScheme o “codelist” for the class Codelist.
1295		-* 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" %)^^~[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" %)^^~[12~]^^>>path:#_ftn12]](%%).
1296		-* If the **agency-id** is not specified, it is assumed by default equal to the agency-id of the TransformationScheme, UserDefinedOperatorScheme or RulesetScheme from which the artefact is invoked. For example, the agency-id can be omitted if it is the same as the invoking T,,ransformationScheme,, and cannot be omitted if the artefact comes from another agency.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink 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).
1297		-* 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;
1298		-** 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
1299		-
1300		-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;
1301		-
1302		-*
1303		-** if the referenced artefact is a ,,ConceptScheme, ,,which is a,, ,,maintainable class,,, ,,the maintained object is the ,,conceptScheme-id,, and obviously cannot be omitted;
1304		-** if the referenced artefact is a ,,Codelist, ,,which is a maintainable class, the maintainedobject-id is the ,,codelist-id,, and obviously cannot be omitted.
	1182	+* 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:
	1183	+** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,
	1184	+** “conceptscheme” for the classes Concept and ConceptScheme
	1185	+** “codelist” for the class Codelist.
	1186	+* 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" %)^^~[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" %)^^~[12~]^^>>path:#_ftn12]](%%).
	1187	+* 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" %)^^~[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).
	1188	+* 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;
	1189	+** 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;
	1190	+** 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;
	1191	+** if the referenced artefact is a ConceptScheme, which is a,, ,,maintainable class,,, ,,the maintained object is the conceptScheme-id and obviously cannot be omitted;
	1192	+** if the referenced artefact is a Codelist, which is a maintainable class, the maintainedobject-id is the codelist-id and obviously cannot be omitted.
1305	1305	* 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.,, ,,
1306	1306	* 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
1307		-* 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
	1195	+* 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
1308	1308
1309		-them the object-id is the main identifier of the artefact
1310		-
1311	1311	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.
1312	1312
1313	1313	For example, the full formulation that uses the complete URN shown at the end of the previous paragraph:
1314	1314
1315		-‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  := ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’   +
1316		-
	1201	+‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  :=
	1202	+‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF1(1.0)’   +
1317	1317	‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DF2(1.0)’
1318	1318
1319		-by omitting all the non-essential parts would become simply:
	1205	+by omitting all the non-essential parts would become simply:
1320	1320
1321		-DFR  :=  DF1 + DF2
	1207	+DFR := DF1 + DF2
1322	1322
1323		-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" %)^^~[14~]^^>>path:#_ftn14]](%%):
	1209	+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" %)^^~[14~]^^>>path:#_ftn14]](%%):
1324	1324
1325	1325	‘urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0)’
1326	1326
1327		-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" %)^^~[15~]^^>>path:#_ftn15]](%%):
	1213	+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" %)^^~[15~]^^>>path:#_ftn15]](%%):
1328	1328
1329	1329	CL_FREQ
1330	1330
1331		-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:
	1217	+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:
1332	1332
1333		-‘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:
	1219	+‘urn:sdmx:org.sdmx.infomodel.datastructure.DataStructure=AG:DST1(1.0).SECTOR’
1334	1334
	1221	+The corresponding fully abbreviated reference, if made from a transformation scheme belonging to AG, would become simply:
	1222	+
1335	1335	SECTOR
1336	1336
1337		-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" %)^^~[16~]^^>>path:#_ftn16]](%%):
	1225	+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" %)^^~[16~]^^>>path:#_ftn16]](%%):
1338	1338
1339	1339	‘DFR(1.0)’ := ‘DF1(1.0)’ [rename SECTOR to SEC]
1340	1340
...	...	@@ -1344,7 +1344,7 @@
1344	1344
1345	1345	‘urn:sdmx:org.sdmx.infomodel.conceptscheme.Concept=AG:CS1(1.0).SECTOR’
1346	1346
1347		-The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
	1235	+The corresponding fully abbreviated reference, if made from a RulesetScheme belonging to AG, would become simply:
1348	1348
1349	1349	CS1(1.0).SECTOR
1350	1350
...	...	@@ -1366,13 +1366,13 @@
1366	1366
1367	1367	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.
1368	1368
1369		-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.
	1257	+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.
1370	1370
1371		-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" %)^^~[17~]^^>>path:#_ftn17]](%%).
	1259	+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" %)^^~[17~]^^>>path:#_ftn17]](%%).
1372	1372
1373		-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" %)^^~[18~]^^>>path:#_ftn18]](%%)
	1261	+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" %)^^~[18~]^^>>path:#_ftn18]](%%)
1374	1374
1375		-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.
	1263	+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.
1376	1376
1377	1377	== 10.3 Mapping between SDMX and VTL artefacts ==
1378	1378
...	...	@@ -1380,62 +1380,59 @@
1380	1380
1381	1381	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.
1382	1382
1383		-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.
	1271	+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.
1384	1384
1385		-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.
	1273	+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.
1386	1386
1387		-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" %)^^~[19~]^^>>path:#_ftn19]](%%).
	1275	+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" %)^^~[19~]^^>>path:#_ftn19]](%%).
1388	1388
1389		-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).
	1277	+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).
1390	1390
1391	1391	=== 10.3.2 General mapping of VTL and SDMX data structures ===
1392	1392
1393		-This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%).
	1281	+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" %)^^~[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" %)^^~[21~]^^>>path:#_ftn21]](%%).
1394	1394
1395		-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" %)^^~[22~]^^>>path:#_ftn22]](%%)
	1283	+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" %)^^~[22~]^^>>path:#_ftn22]](%%)
1396	1396
1397		-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.
	1285	+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.
1398	1398
1399	1399	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.
1400	1400
1401		-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
	1289	+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.
1402	1402
1403		-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.
	1291	+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" %)^^~[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.
1404	1404
1405		-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" %)^^~[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.
	1293	+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.
1406	1406
1407		-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.
	1295	+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.
1408	1408
1409		-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.
1410		-
1411	1411	Therefore for multi-measure data more mapping options are possible, as described in more detail in the following sections.
1412	1412
1413	1413	=== 10.3.3 Mapping from SDMX to VTL data structures ===
1414	1414
1415		-**10.3.3.1 Basic Mapping **
	1301	+==== 10.3.3.1 Basic Mapping** ** ====
1416	1416
1417		-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:
	1303	+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.
1418	1418
1419		-|SDMX|VTL
1420		-|Dimension|(Simple) Identifier
1421		-|Time Dimension|(Time) Identifier
1422		-|Measure Dimension|(Measure) Identifier
1423		-|Primary Measure|Measure
1424		-|Data Attribute|Attribute
	1305	+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:
1425	1425
1426		-According to this method, the resulting VTL structures are always mono-measure
	1307	+(% style="width:636.294px" %)
	1308	+|(% style="width:286px" %)**SDMX**|(% style="width:347px" %)**VTL**
	1309	+|(% style="width:286px" %)Dimension|(% style="width:347px" %)(Simple) Identifier
	1310	+|(% style="width:286px" %)Time Dimension|(% style="width:347px" %)(Time) Identifier
	1311	+|(% style="width:286px" %)Measure Dimension|(% style="width:347px" %)(Measure) Identifier
	1312	+|(% style="width:286px" %)Primary Measure|(% style="width:347px" %)Measure
	1313	+|(% style="width:286px" %)Data Attribute|(% style="width:347px" %)Attribute
1427	1427
1428		-(i.e., they have just one measure component) and their Measure is the SDMX
	1315	+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).
1429	1429
1430		-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).
1431		-
1432	1432	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).
1433	1433
1434	1434	With the Basic mapping, one SDMX observation generates one VTL data point.
1435	1435
1436		-**10.3.3.2 Pivot Mapping **
	1321	+==== 10.3.3.2 Pivot Mapping ====
1437	1437
1438		-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.
	1323	+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.
1439	1439
1440	1440	The SDMX structures that do not contain a MeasureDimension are mapped like in the Basic mapping (see the previous paragraph).
1441	1441
...	...	@@ -1446,36 +1446,34 @@
1446	1446	* The SDMX MeasureDimension is not mapped to VTL (it disappears in the VTL Data Structure);
1447	1447	* The SDMX PrimaryMeasure is not mapped to VTL as well (it disappears in the VTL Data Structure);
1448	1448	* A SDMX DataAttribute is mapped in different ways according to its AttributeRelationship:
1449		-** 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;
1450		-** 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
	1334	+** 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;
	1335	+** 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
1451	1451
1452	1452	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.
1453	1453
1454	1454	The summary mapping table of the “pivot” mapping from SDMX to VTL for the SDMX data structures that contain a MeasureDimension is the following:
1455	1455
1456		-|SDMX|VTL
1457		-|Dimension|(Simple) Identifier
1458		-|TimeDimension|(Time) Identifier
1459		-|MeasureDimension & PrimaryMeasure|One Measure for each Concept of the SDMX Measure Dimension
1460		-|DataAttribute not depending on the MeasureDimension|Attribute
1461		-|DataAttribute depending on the MeasureDimension|One Attribute for each Concept of the SDMX Measure Dimension
	1341	+(% style="width:941.294px" %)
	1342	+|(% style="width:441px" %)**SDMX**|(% style="width:497px" %)**VTL**
	1343	+|(% style="width:441px" %)Dimension|(% style="width:497px" %)(Simple) Identifier
	1344	+|(% style="width:441px" %)TimeDimension|(% style="width:497px" %)(Time) Identifier
	1345	+|(% style="width:441px" %)MeasureDimension & PrimaryMeasure|(% style="width:497px" %)One Measure for each Concept of the SDMX Measure Dimension
	1346	+|(% style="width:441px" %)DataAttribute not depending on the MeasureDimension|(% style="width:497px" %)Attribute
	1347	+|(% style="width:441px" %)DataAttribute depending on the MeasureDimension|(% style="width:497px" %)One Attribute for each Concept of the SDMX Measure Dimension
1462	1462
1463		-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.
	1349	+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.
1464	1464
1465		-At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Concept of the 1911 MeasureDimension:
	1351	+At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Concept of the MeasureDimension:
1466	1466
1467		- 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;
	1353	+* 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;
	1354	+* 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.
	1355	+* 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
	1356	+* 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
1468	1468
1469		-*
1470		-** 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.
1471		-** 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
1472		-** 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
	1358	+==== 10.3.3.3 From SDMX DataAttributes to VTL Measures ====
1473	1473
1474		-**10.3.3.3 From SDMX DataAttributes to VTL Measures **
	1360	+* 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.
1475	1475
1476		-*
1477		-** 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.
1478		-
1479	1479	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.
1480	1480
1481	1481	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.
...	...	@@ -1482,28 +1482,27 @@
1482	1482
1483	1483	=== 10.3.4 Mapping from VTL to SDMX data structures ===
1484	1484
1485		-**10.3.4.1 Basic Mapping **
	1368	+==== 10.3.4.1 Basic Mapping** ** ====
1486	1486
1487	1487	The main mapping method **from VTL to SDMX** is called **Basic **mapping as well.
1488	1488
1489		-This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes.
	1372	+This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes.
1490	1490
1491	1491	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.
1492	1492
1493		-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
	1376	+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" %)^^~[24~]^^>>path:#_ftn24]](%%)
1494	1494
1495		-PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)
	1378	+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.
1496	1496
1497		-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.
1498		-
1499	1499	Mapping table:
1500	1500
1501		-|VTL|SDMX
1502		-|(Simple) Identifier|Dimension
1503		-|(Time) Identifier|TimeDimension
1504		-|(Measure) Identifier|MeasureDimension
1505		-|Measure|PrimaryMeasure
1506		-|Attribute|DataAttribute
	1382	+(% style="width:592.294px" %)
	1383	+|(% style="width:253px" %)**VTL**|(% style="width:336px" %)**SDMX**
	1384	+|(% style="width:253px" %)(Simple) Identifier|(% style="width:336px" %)Dimension
	1385	+|(% style="width:253px" %)(Time) Identifier|(% style="width:336px" %)TimeDimension
	1386	+|(% style="width:253px" %)(Measure) Identifier|(% style="width:336px" %)MeasureDimension
	1387	+|(% style="width:253px" %)Measure|(% style="width:336px" %)PrimaryMeasure
	1388	+|(% style="width:253px" %)Attribute|(% style="width:336px" %)DataAttribute
1507	1507
1508	1508	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.
1509	1509
...	...	@@ -1511,16 +1511,14 @@
1511	1511
1512	1512	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”).
1513	1513
1514		-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.
	1396	+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.
1515	1515
1516		-**10.3.4.2 Unpivot Mapping **
	1398	+==== 10.3.4.2 Unpivot Mapping ====
1517	1517
1518		-An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
	1400	+An alternative mapping method from VTL to SDMX is the **Unpivot **mapping.
1519	1519
1520		-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
	1402	+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”).
1521	1521
1522		-“obs_value”).
1523		-
1524	1524	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.
1525	1525
1526	1526	The **unpivot** mapping behaves like follows:
...	...	@@ -1527,43 +1527,34 @@
1527	1527
1528	1528	* like in the basic mapping, a VTL (simple) identifier becomes a SDMX
1529	1529
1530		-Dimension and a VTL (time) identifier becomes a SDMX TimeDimension (as said, a  measure identifier cannot exist in multi-measure VTL structures);
	1410	+Dimension and a VTL (time) identifier becomes a SDMX TimeDimension (as said, a measure identifier cannot exist in multi-measure VTL structures);
1531	1531
1532	1532	* a MeasureDimension component called “measure_name” is added to the SDMX DataStructure;
1533		-* a PrimaryMeasure component called  “obs_value” is added to the SDMX DataStructure;
1534		-* 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);
1535		-* a VTL Attribute becomes a SDMX DataAttribute having AttributeRelationship  referred to all the SDMX DimensionComponents including the TimeDimension  and except the MeasureDimension.
	1413	+* a PrimaryMeasure component called “obs_value” is added to the SDMX DataStructure;
	1414	+* 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);
	1415	+* a VTL Attribute becomes a SDMX DataAttribute having AttributeRelationship referred to all the SDMX DimensionComponents including the TimeDimension and except the MeasureDimension.
1536	1536
1537	1537	The summary mapping table of the **unpivot** mapping method is the following:
1538	1538
1539		-
1540		-|VTL|SDMX
1541		-|(Simple) Identifier|Dimension
1542		-|(Time) Identifier|TimeDimension
1543		-|All Measure Components|(((
1544		-MeasureDimension (having one Measure Concept for each VTL measure component) &
1545		-
1546		-PrimaryMeasure
	1419	+(% style="width:904.294px" %)
	1420	+|(% style="width:291px" %)**VTL**|(% style="width:611px" %)**SDMX**
	1421	+|(% style="width:291px" %)(Simple) Identifier|(% style="width:611px" %)Dimension
	1422	+|(% style="width:291px" %)(Time) Identifier|(% style="width:611px" %)TimeDimension
	1423	+|(% style="width:291px" %)All Measure Components|(% style="width:611px" %)(((
	1424	+MeasureDimension (having one Measure Concept for each VTL measure component) & PrimaryMeasure
1547	1547	)))
1548		-|Attribute |(((
1549		-DataAttribute depending on all
1550		-
1551		-SDMX Dimensions including the
1552		-
1553		-TimeDimension and except the MeasureDimension
	1426	+|(% style="width:291px" %)Attribute |(% style="width:611px" %)(((
	1427	+DataAttribute depending on all SDMX Dimensions including the TimeDimension and except the MeasureDimension
1554	1554	)))
1555	1555
1556	1556	At observation / data point level:
1557	1557
1558		- a multi-measure VTL Data Point becomes a set of SDMX observations, one for each VTL measure
	1432	+* a multi-measure VTL Data Point becomes a set of SDMX observations, one for each VTL measure
	1433	+* the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above
	1434	+* 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)
	1435	+* the value of the j^^th^^ VTL measure becomes the value of the SDMX PrimaryMeasure of the j^^th^^ observation of the set
	1436	+* the values of the VTL Attributes become the values of the corresponding SDMX DataAttributes (in principle for all the observations of the set above)
1559	1559
1560		- the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above
1561		-
1562		-*
1563		-** 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)
1564		-** the value of the j^^th^^ VTL measure becomes the value of the SDMX PrimaryMeasure of the j^^th^^ observation of the set
1565		-** the values of the VTL Attributes become the values of the corresponding SDMX DataAttributes (in principle for all the observations of the set above)
1566		-
1567	1567	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.
1568	1568
1569	1569	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”.
...	...	@@ -1570,219 +1570,150 @@
1570	1570
1571	1571	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.
1572	1572
1573		-**10.3.4.3 From VTL Measures to SDMX Data Attributes **
	1444	+==== 10.3.4.3 From VTL Measures to SDMX Data Attributes** ** ====
1574	1574
1575	1575	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”).
1576	1576
1577	1577	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:
1578	1578
1579		-|VTL|SDMX
1580		-|(Simple) Identifier|Dimension
1581		-|(Time) Identifier|TimeDimension
1582		-|(Measure) Identifier (if any)|MeasureDimension
1583		-|Measure|PrimaryMeasure
1584		-|Attribute|DataAttribute
	1450	+(% style="width:591.294px" %)
	1451	+|(% style="width:252px" %)**VTL**|(% style="width:336px" %)**SDMX**
	1452	+|(% style="width:252px" %)(Simple) Identifier|(% style="width:336px" %)Dimension
	1453	+|(% style="width:252px" %)(Time) Identifier|(% style="width:336px" %)TimeDimension
	1454	+|(% style="width:252px" %)(Measure) Identifier (if any)|(% style="width:336px" %)MeasureDimension
	1455	+|(% style="width:252px" %)Measure|(% style="width:336px" %)PrimaryMeasure
	1456	+|(% style="width:252px" %)Attribute|(% style="width:336px" %)DataAttribute
1585	1585
1586		-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.
	1458	+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.
1587	1587
1588		-2Taking into account that the multi-measure VTL structures do not have a measure 2073 identifier, the mapping table is the following:
	1460	+Taking into account that the multi-measure VTL structures do not have a measure identifier, the mapping table is the following:
1589	1589
1590		-|VTL|SDMX
1591		-|(Simple) Identifier|Dimension
1592		-|(Time) Identifier|TimeDimension
1593		-|One of the Measures|PrimaryMeasure
1594		-|Other Measures|DataAttribute
1595		-|Attribute|DataAttribute
	1462	+(% style="width:588.294px" %)
	1463	+|(% style="width:259px" %)**VTL**|(% style="width:326px" %)**SDMX**
	1464	+|(% style="width:259px" %)(Simple) Identifier|(% style="width:326px" %)Dimension
	1465	+|(% style="width:259px" %)(Time) Identifier|(% style="width:326px" %)TimeDimension
	1466	+|(% style="width:259px" %)One of the Measures|(% style="width:326px" %)PrimaryMeasure
	1467	+|(% style="width:259px" %)Other Measures|(% style="width:326px" %)DataAttribute
	1468	+|(% style="width:259px" %)Attribute|(% style="width:326px" %)DataAttribute
1596	1596
1597		-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.
	1470	+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.
1598	1598
1599	1599	=== 10.3.5 Declaration of the mapping methods between data structures ===
1600	1600
1601	1601	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.
1602	1602
1603		-
1604	1604	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.
1605	1605
1606		-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
	1478	+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.
1607	1607
1608		-“Basic” methods. In turn, the toVtlMappingMethod and fromVtlMappingMethod declared for a specific Dataflow are intended to override the default ones for such a Dataflow.
1609		-
1610	1610	The VtlMappingScheme is a container for zero or more VtlDataflowMapping (besides possible mappings to artefacts other than dataflows).
1611	1611
1612		-=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
	1482	+=== 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" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
1613	1613
1614		-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
	1484	+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).
1615	1615
1616		-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).
	1486	+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" %)^^~[26~]^^>>path:#_ftn26]](%%)
1617	1617
1618		-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" %)^^~[26~]^^>>path:#_ftn26]](%%)
	1488	+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" %)^^~[27~]^^>>path:#_ftn27]](%%)
1619	1619
1620		-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" %)^^~[27~]^^>>path:#_ftn27]](%%)
	1490	+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.
1621	1621
1622		- Given a SDMX Dataflow and some predefined Dimensions of its
	1492	+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).
1623	1623
1624		-DataStructure, it is allowed to map the subsets of observations that have the same combination of values for such Dimensions to correspondent VTL datasets.
1625		-
1626		-For example, assuming that the SDMX dataflow DF1(1.0) has the Dimensions INDICATOR, TIME_PERIOD and COUNTRY, and that the user declares the
1627		-
1628		-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).
1629		-
1630	1630	In practice, this kind mapping is obtained like follows:
1631	1631
1632		-* 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" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
	1496	+* 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" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
1633	1633	* The VTL dataset is given a name using a special notation also called “ordered concatenation” and composed of the following parts:
1634		-** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated
	1498	+** 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);
	1499	+** a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
	1500	+** 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" %)^^~[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.
1635	1635
1636		-URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
1637		-
1638		-*
1639		-** 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" %)^^~[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.
1640		-
1641	1641	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.
1642	1642
1643	1643	Therefore, the generic name of this kind of VTL datasets would be:
1644	1644
1645		-‘DF(1.0)///INDICATORvalue//.//COUNTRYvalue//’
	1506	+> ‘DF(1.0)///INDICATORvalue//.//COUNTRYvalue//’
1646	1646
1647	1647	Where DF(1.0) is the Dataflow and //INDICATORvalue// and //COUNTRYvalue //are placeholders for one value of the INDICATOR and // //COUNTRY dimensions.
1648	1648
1649	1649	Instead the specific name of one of these VTL datasets would be:
1650	1650
1651		-‘DF(1.0)/POPULATION.USA’
	1512	+> ‘DF(1.0)/POPULATION.USA’
1652	1652
1653		-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.
	1514	+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.
1654	1654
1655	1655	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.
1656	1656
1657		-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" %)^^~[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.
	1518	+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" %)^^~[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.
1658	1658
1659		-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.
	1520	+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.
1660	1660
1661		-As already said, each VTL dataset is assumed to contain all the observations of the
	1522	+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.
1662	1662
1663		-SDMX dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=
	1524	+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" %)^^~[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 …).
1664	1664
1665		-//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.
	1526	+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.
1666	1666
1667		-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" %)^^~[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 …).
1668		-
1669		-In the example above, for all the datasets of the kind
1670		-
1671		-‘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.
1672		-
1673	1673	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:
1674	1674
1675		-‘DF1(1.0)/POPULATION.USA’ :=
	1530	+> ‘DF1(1.0)/POPULATION.USA’ :=
	1531	+> DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
	1532	+> ‘DF1(1.0)/POPULATION.CANADA’ :=
	1533	+> DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
	1534	+> …   …   …
1676	1676
1677		-DF1(1.0) [ sub  INDICATOR=“POPULATION”, COUNTRY=“USA” ];
	1536	+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" %)^^~[33~]^^>>path:#_ftn33]]
1678	1678
1679		-
1680		-‘DF1(1.0)/POPULATION.CANADA’ :=
1681		-
1682		-DF1(1.0) [ sub  INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
1683		-
1684		-
1685		-…   …   …
1686		-
1687		-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" %)^^~[33~]^^>>path:#_ftn33]]
1688		-
1689	1689	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.
1690	1690
1691		-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.
	1540	+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.
1692	1692
1693	1693	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
1694	1694
1695		-‘DF1(1.0)/POPULATION.’ :=
	1544	+> ‘DF1(1.0)/POPULATION.’ :=
	1545	+> DF1(1.0) [sub INDICATOR=“POPULATION” ];
1696	1696
1697		-DF1(1.0) [ sub  INDICATOR=“POPULATION” ];
1698		-
1699		-
1700	1700	Therefore the VTL dataset ‘DF1(1.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
1701	1701
1702	1702	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
1703	1703
1704		-Let us now analyse the mapping direction from VTL to SDMX.
	1551	+Let us now analyse the __mapping direction from VTL to SDMX__.
1705	1705
1706	1706	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.
1707	1707
1708	1708	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:
1709	1709
1710		-* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)
1711		-* 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" %)^^~[35~]^^>>path:#_ftn35]]
	1557	+* 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" %)^^~[34~]^^>>path:#_ftn34]](%%)
	1558	+* 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" %)^^~[35~]^^>>path:#_ftn35]]
1712	1712
1713		-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" %)^^~[36~]^^>>path:#_ftn36]](%%).
	1560	+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" %)^^~[36~]^^>>path:#_ftn36]](%%).
1714	1714
1715		-The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]
	1562	+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" %)^^~[37~]^^>>path:#_ftn37]]
1716	1716
1717	1717	‘DF2(1.0)///INDICATORvalue//.//COUNTRYvalue//’  <-  expression
1718	1718
1719	1719	Some examples follow, for some specific values of INDICATOR and COUNTRY:
1720	1720
1721		- ‘DF2(1.0)/GDPPERCAPITA.USA’    <-   expression11;
1722		-
	1568	+‘DF2(1.0)/GDPPERCAPITA.USA’  <-   expression11;
1723	1723	‘DF2(1.0)/GDPPERCAPITA.CANADA’   <-   expression12;
1724		-
1725	1725	…   …   …
	1571	+‘DF2(1.0)/POPGROWTH.USA’  <-   expression21;
	1572	+‘DF2(1.0)/POPGROWTH.CANADA’  <-   expression22;
1726	1726
1727		- ‘DF2(1.0)/POPGROWTH.USA’   <-   expression21;
1728		-
1729		- ‘DF2(1.0)/POPGROWTH.CANADA’    <-   expression22;
1730		-
1731	1731	…   …   …
1732	1732
	1576	+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:
1733	1733
1734		-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:
	1578	+[[image:1747859458410-183.png||height="170" width="663"]]
1735	1735
1736		-|(((
1737		- //VTL dataset                                             //
	1580	+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:
1738	1738
1739		-
1740		-)))|(% colspan="2" %)//INDICATOR value //|(% colspan="2" %)//COUNTRY value//
1741		-|‘DF2(1.0)/GDPPERCAPITA.USA’              |GDPPERCAPITA| | |USA
1742		-|(((
1743		-‘DF2(1.0)/GDPPERCAPITA.CANADA’
	1582	+[[image:1747859612718-454.png||height="451" width="602"]]
1744	1744
1745		-…   …   …
1746		-)))|GDPPERCAPITA| | |CANADA
1747		-|‘DF2(1.0)/POPGROWTH.USA’                  |POPGROWTH | | |USA
1748		-|(((
1749		-‘DF2(1.0)/POPGROWTH.CANADA’
	1584	+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" %)^^~[38~]^^>>path:#_ftn38]](%%), which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
1750	1750
1751		-…   …   …
1752		-)))|POPGROWTH | | |CANADA
	1586	+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" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
1753	1753
1754		-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:
1755		-
1756		-DF2bis_GDPPERCAPITA_USA    :=   ‘DF2(1.0)/GDPPERCAPITA.USA’
1757		-
1758		-[calc  identifier INDICATOR := ”GDPPERCAPITA”,  identifier  COUNTRY := ”USA”];
1759		-
1760		-DF2bis_GDPPERCAPITA_CANADA :=   ‘DF2(1.0)/GDPPERCAPITA.CANADA’   [calc  identifier INDICATOR:=”GDPPERCAPITA”,  identifier COUNTRY:=”CANADA”]; …   …   …
1761		-
1762		-DF2bis_POPGROWTH_USA     :=  ‘DF2(1.0)/POPGROWTH.USA’
1763		-
1764		-[calc  identifier INDICATOR := ”POPGROWTH”,  identifier  COUNTRY :=”USA”];
1765		-
1766		-DF2bis_POPGROWTH_CANADA’  :=  ‘DF2(1.0)/POPGROWTH.CANADA’
1767		-
1768		-[calc  identifier INDICATOR := ”POPGROWTH”,  identifier  COUNTRY := ”CANADA”]; …   …   …
1769		-
1770		-DF2(1.0)   <-   UNION          (DF2bis_GDPPERCAPITA_USA’,
1771		-
1772		-DF2bis_GDPPERCAPITA_CANADA’,
1773		-
1774		-… ,
1775		-
1776		-DF2bis_POPGROWTH_USA’,
1777		-
1778		-DF2bis_POPGROWTH_CANADA’
1779		-
1780		-…);
1781		-
1782		-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" %)^^~[38~]^^>>path:#_ftn38]](%%), which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
1783		-
1784		-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" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
1785		-
1786	1786	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).
1787	1787
1788	1788	=== 10.3.7 Mapping variables and value domains between VTL and SDMX ===
...	...	@@ -1789,58 +1789,41 @@
1789	1789
1790	1790	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
1791	1791
1792		-|VTL|SDMX
1793		-|**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^^
1794		-|**Represented Variable**|**Concept** with  a definite Representation
1795		-|**Value Domain**|**Representation** (see the Structure Pattern in the Base Package)
1796		-|**Enumerated Value Domain / Code List**|(((
1797		-**Codelist** (for enumerated
1798		-
1799		-Dimension, PrimaryMeasure,
1800		-
1801		-DataAttribute) or **ConceptScheme**
1802		-
1803		-(for MeasureDimension)
	1594	+(% style="width:890.835px" %)
	1595	+|(% style="width:314px" %)VTL|(% style="width:574px" %)SDMX
	1596	+|(% 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^^
	1597	+|(% style="width:314px" %)**Represented Variable**|(% style="width:574px" %)**Concept** with a definite Representation
	1598	+|(% style="width:314px" %)**Value Domain**|(% style="width:574px" %)**Representation** (see the Structure Pattern in the Base Package)
	1599	+|(% style="width:314px" %)**Enumerated Value Domain / Code List**|(% style="width:574px" %)(((
	1600	+**Codelist** (for enumerated Dimension, PrimaryMeasure, DataAttribute) or **ConceptScheme **(for MeasureDimension)
1804	1804	)))
1805		-|**Code**|**Code** (for enumerated Dimension, PrimaryMeasure, DataAttribute) or **Concept** (for MeasureDimension)
1806		-|**Described Value Domain**|(((
1807		-non-enumerated** Representation**
1808		-
1809		-(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
	1602	+|(% style="width:314px" %)**Code**|(% style="width:574px" %)**Code** (for enumerated Dimension, PrimaryMeasure, DataAttribute) or **Concept** (for MeasureDimension)
	1603	+|(% style="width:314px" %)**Described Value Domain**|(% style="width:574px" %)(((
	1604	+non-enumerated** Representation **(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
1810	1810	)))
1811		-|**Value**|(((
1812		-Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a
1813		-
1814		-Codelist (for enumerated
1815		-
1816		-Representations) or to a valid **value **(for non-enumerated** **
1817		-
1818		-Representations) or to a **Concept**
1819		-
1820		-(for MeasureDimension)
	1606	+|(% style="width:314px" %)**Value**|(% style="width:574px" %)(((
	1607	+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)
1821	1821	)))
1822		-|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
1823		-|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
1824		-|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
1825		-|**Set list**|This abstraction does not exist in SDMX
	1609	+|(% style="width:314px" %)**Value Domain Subset / Set**|(% style="width:574px" %)This abstraction does not exist in SDMX
	1610	+|(% style="width:314px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:574px" %)This abstraction does not exist in SDMX
	1611	+|(% style="width:314px" %)**Described Value Domain Subset / Described Set**|(% style="width:574px" %)This abstraction does not exist in SDMX
	1612	+|(% style="width:314px" %)**Set list**|(% style="width:574px" %)This abstraction does not exist in SDMX
1826	1826
1827	1827	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).
1828	1828
1829		-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
	1616	+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).
1830	1830
1831		-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).
	1618	+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" %)^^~[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" %)^^~[42~]^^>>path:#_ftn42]](%%) This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
1832	1832
1833		-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" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="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.
	1620	+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
1834	1834
1835		-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
	1622	+DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
1836	1836
1837		- DS_c  :=  DS_a  +  DS_b  (where DS_a, DS_b, DS_c   are VTL Data Sets)
	1624	+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.
1838	1838
1839		-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.
1840		-
1841	1841	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.
1842	1842
1843		-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.
	1628	+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.
1844	1844
1845	1845	== 10.4 Mapping between SDMX and VTL Data Types ==
1846	1846
...	...	@@ -1858,6 +1858,7 @@
1858	1858
1859	1859	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):
1860	1860
	1646	+[[image:1747859722732-549.png||height="283" width="224"]]
1861	1861
1862	1862	**Figure 13 – VTL Basic Scalar Types**
1863	1863
...	...	@@ -1883,208 +1883,162 @@
1883	1883
1884	1884	The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types.
1885	1885
1886		-|**SDMX data type (BasicComponentDataType)**|**Default VTL basic scalar type**
1887		-|(((
1888		-**String   **
1889		-
	1672	+(% style="width:653.835px" %)
	1673	+|(% style="width:366px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:284px" %)**Default VTL basic scalar type**
	1674	+|(% style="width:366px" %)(((
	1675	+**String**
1890	1890	(string allowing any character)
1891		-)))|**string**
1892		-|(((
1893		-**Alpha    **
1894		-
	1677	+)))|(% style="width:284px" %)**string**
	1678	+|(% style="width:366px" %)(((
	1679	+**Alpha**
1895	1895	(string which only allows A-z)
1896		-)))|**string**
1897		-|(((
1898		-**AlphaNumeric  **
1899		-
	1681	+)))|(% style="width:284px" %)**string**
	1682	+|(% style="width:366px" %)(((
	1683	+**AlphaNumeric**
1900	1900	(string which only allows A-z and 0-9)
1901		-)))|**string**
1902		-|(((
1903		-**Numeric   **
1904		-
	1685	+)))|(% style="width:284px" %)**string**
	1686	+|(% style="width:366px" %)(((
	1687	+**Numeric**
1905	1905	(string which only allows 0-9, but is not numeric so that is can having leading zeros)
1906		-)))|**string**
1907		-|(((
1908		-**BigInteger **
1909		-
	1689	+)))|(% style="width:284px" %)**string**
	1690	+|(% style="width:366px" %)(((
	1691	+**BigInteger**
1910	1910	(corresponds to XML Schema xs:integer datatype; infinite set of integer values)
1911		-)))|**integer**
1912		-|(((
1913		-**Integer **
1914		-
1915		-(corresponds to XML Schema xs:int datatype; between
1916		-
1917		--2147483648 and +2147483647 (inclusive))
1918		-)))|**integer**
1919		-|(((
1920		-**Long **
1921		-
1922		-(corresponds to XML Schema xs:long datatype;
1923		-
1924		-between -9223372036854775808 and +9223372036854775807 (inclusive))
1925		-)))|**integer**
1926		-|(((
1927		-**Short **
1928		-
	1693	+)))|(% style="width:284px" %)**integer**
	1694	+|(% style="width:366px" %)(((
	1695	+**Integer**
	1696	+(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive))
	1697	+)))|(% style="width:284px" %)**integer**
	1698	+|(% style="width:366px" %)(((
	1699	+**Long**
	1700	+(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive))
	1701	+)))|(% style="width:284px" %)**integer**
	1702	+|(% style="width:366px" %)(((
	1703	+**Short**
1929	1929	(corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive))
1930		-)))|**integer**
1931		-|(((
	1705	+)))|(% style="width:284px" %)**integer**
	1706	+|(% style="width:366px" %)(((
1932	1932	**Decimal**
1933		-
1934	1934	(corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)
1935		-)))|**number**
1936		-|(((
1937		-**Float **
1938		-
	1709	+)))|(% style="width:284px" %)**number**
	1710	+|(% style="width:366px" %)(((
	1711	+**Float**
1939	1939	(corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type)
1940		-)))|**number**
1941		-|(((
1942		-**Double **
1943		-
	1713	+)))|(% style="width:284px" %)**number**
	1714	+|(% style="width:366px" %)(((
	1715	+**Double**
1944	1944	(corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type)
1945		-)))|**number**
1946		-|(((
1947		-**Boolean **
1948		-
1949		-(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
1950		-)))|**boolean**
1951		-|(((
1952		-**URI **
1953		-
	1717	+)))|(% style="width:284px" %)**number**
	1718	+|(% style="width:366px" %)(((
	1719	+**Boolean**
	1720	+(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false})
	1721	+)))|(% style="width:284px" %)**boolean**
	1722	+|(% style="width:366px" %)(((
	1723	+**URI**
1954	1954	(corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference)
1955		-)))|**string**
1956		-|(((
1957		-**Count   **
1958		-
	1725	+)))|(% style="width:284px" %)**string**
	1726	+|(% style="width:366px" %)(((
	1727	+**Count**
1959	1959	(an integer following a sequential pattern, increasing by 1 for each occurrence)
1960		-)))|**integer**
1961		-|(((
1962		-**InclusiveValueRange **
1963		-
	1729	+)))|(% style="width:284px" %)**integer**
	1730	+|(% style="width:366px" %)(((
	1731	+**InclusiveValueRange**
1964	1964	(decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
1965		-)))|**number**
1966		-|(((
1967		-**ExclusiveValueRange **
1968		-
	1733	+)))|(% style="width:284px" %)**number**
	1734	+|(% style="width:366px" %)(((
	1735	+**ExclusiveValueRange**
1969	1969	(decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue)
1970		-)))|**number**
1971		-|(((
1972		-**Incremental  **
1973		-
	1737	+)))|(% style="width:284px" %)**number**
	1738	+|(% style="width:366px" %)(((
	1739	+**Incremental **
1974	1974	(decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation)
1975		-)))|**number**
1976		-|(((
1977		-**ObservationalTimePeriod   **
1978		-
	1741	+)))|(% style="width:284px" %)**number**
	1742	+|(% style="width:366px" %)(((
	1743	+**ObservationalTimePeriod**
1979	1979	(superset of StandardTimePeriod and TimeRange)
1980		-)))|**time**
1981		-|(((
1982		-**StandardTimePeriod   **
1983		-
	1745	+)))|(% style="width:284px" %)**time**
	1746	+|(% style="width:366px" %)(((
	1747	+**StandardTimePeriod**
1984	1984	(superset of BasicTimePeriod and ReportingTimePeriod)
1985		-)))|**time**
1986		-|(((
1987		-**BasicTimePeriod  **
1988		-
	1749	+)))|(% style="width:284px" %)**time**
	1750	+|(% style="width:366px" %)(((
	1751	+**BasicTimePeriod**
1989	1989	(superset of GregorianTimePeriod and DateTime)
1990		-)))|**date**
1991		-|(((
1992		-**GregorianTimePeriod   **
1993		-
	1753	+)))|(% style="width:284px" %)**date**
	1754	+|(% style="width:366px" %)(((
	1755	+**GregorianTimePeriod**
1994	1994	(superset of GregorianYear, GregorianYearMonth, and GregorianDay)
1995		-)))|**date**
1996		-|**GregorianYear     **(YYYY)  |**date**
1997		-|**GregorianYearMonth** / **GregorianMonth**    (YYYY-MM)|**date**
1998		-|**GregorianDay    **(YYYY-MM-DD)|**date**
1999		-|(((
	1757	+)))|(% style="width:284px" %)**date**
	1758	+|(% style="width:366px" %)**GregorianYear **(YYYY)|(% style="width:284px" %)**date**
	1759	+|(% style="width:366px" %)**GregorianYearMonth** / **GregorianMonth** (YYYY-MM)|(% style="width:284px" %)**date**
	1760	+|(% style="width:366px" %)**GregorianDay **(YYYY-MM-DD)|(% style="width:284px" %)**date**
	1761	+|(% style="width:366px" %)(((
2000	2000	**ReportingTimePeriod **
2001		-
2002		-(superset of RepostingYear, ReportingSemester,
2003		-
2004		-ReportingTrimester, ReportingQuarter, ReportingMonth,
2005		-
2006		-ReportingWeek, ReportingDay)
2007		-)))|**time_period**
2008		-|(((
2009		-**ReportingYear   **
2010		-
	1763	+(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay)
	1764	+)))|(% style="width:284px" %)**time_period**
	1765	+|(% style="width:366px" %)(((
	1766	+**ReportingYear**
2011	2011	(YYYY-A1 – 1 year period)
2012		-)))|**time_period**
2013		-|(((
2014		-**ReportingSemester  **
2015		-
	1768	+)))|(% style="width:284px" %)**time_period**
	1769	+|(% style="width:366px" %)(((
	1770	+**ReportingSemester**
2016	2016	(YYYY-Ss – 6 month period)
2017		-)))|**time_period**
2018		-|(((
2019		-**ReportingTrimester **
2020		-
	1772	+)))|(% style="width:284px" %)**time_period**
	1773	+|(% style="width:366px" %)(((
	1774	+**ReportingTrimester**
2021	2021	(YYYY-Tt – 4 month period)
2022		-)))|**time_period**
2023		-|(((
2024		-**ReportingQuarter   **
2025		-
	1776	+)))|(% style="width:284px" %)**time_period**
	1777	+|(% style="width:366px" %)(((
	1778	+**ReportingQuarter**
2026	2026	(YYYY-Qq – 3 month period)
2027		-)))|**time_period**
2028		-|(((
2029		-**ReportingMonth   **
2030		-
	1780	+)))|(% style="width:284px" %)**time_period**
	1781	+|(% style="width:366px" %)(((
	1782	+**ReportingMonth**
2031	2031	(YYYY-Mmm – 1 month period)
2032		-)))|**time_period**
2033		-|(((
2034		-**ReportingWeek   **
2035		-
	1784	+)))|(% style="width:284px" %)**time_period**
	1785	+|(% style="width:366px" %)(((
	1786	+**ReportingWeek**
2036	2036	(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)
2037		-)))|**time_period**
2038		-|(((
2039		-**ReportingDay   **
2040		-
	1788	+)))|(% style="width:284px" %)**time_period**
	1789	+|(% style="width:366px" %)(((
	1790	+**ReportingDay**
2041	2041	(YYYY-Dddd – 1 day period)
2042		-)))|**time_period**
2043		-|(((
2044		-**DateTime  **
2045		-
	1792	+)))|(% style="width:284px" %)**time_period**
	1793	+|(% style="width:366px" %)(((
	1794	+**DateTime**
2046	2046	(YYYY-MM-DDThh:mm:ss)
2047		-)))|**date**
2048		-|(((
2049		-**TimeRange   **
	1796	+)))|(% style="width:284px" %)**date**
	1797	+|(% style="width:366px" %)(((
	1798	+**TimeRange**
2050	2050
2051	2051	(YYYY-MM-DD(Thh:mm:ss)?/<duration>)
2052		-)))|**time**
2053		-|(((
2054		-**Month   **
2055		-
2056		-(~-~-MM; speicifies a month independent of a year; e.g.
2057		-
2058		-February is black history month in the United States)
2059		-)))|**string**
2060		-|(((
2061		-**MonthDay   **
2062		-
2063		-(~-~-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)
2064		-)))|**string**
2065		-|(((
2066		-**Day   **
2067		-
	1801	+)))|(% style="width:284px" %)**time**
	1802	+|(% style="width:366px" %)(((
	1803	+**Month**
	1804	+(~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States)
	1805	+)))|(% style="width:284px" %)**string**
	1806	+|(% style="width:366px" %)(((
	1807	+**MonthDay**
	1808	+(~-~-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)
	1809	+)))|(% style="width:284px" %)**string**
	1810	+|(% style="width:366px" %)(((
	1811	+**Day**
2068	2068	(~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday)
2069		-)))|**string**
2070		-|(((
2071		-**Time   **
2072		-
	1813	+)))|(% style="width:284px" %)**string**
	1814	+|(% style="width:366px" %)(((
	1815	+**Time**
2073	2073	(hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM)
2074		-)))|**string**
2075		-|(((
2076		-**Duration **
2077		-
	1817	+)))|(% style="width:284px" %)**string**
	1818	+|(% style="width:366px" %)(((
	1819	+**Duration**
2078	2078	(corresponds to XML Schema xs:duration datatype)
2079		-)))|**duration**
2080		-|XHTML|Metadata type – not applicable
2081		-|KeyValues|Metadata type – not applicable
2082		-|IdentifiableReference|Metadata type – not applicable
2083		-|DataSetReference|Metadata type – not applicable
2084		-|AttachmentConstraintReference|Metadata type – not applicable
	1821	+)))|(% style="width:284px" %)**duration**
	1822	+|(% style="width:366px" %)XHTML|(% style="width:284px" %)Metadata type – not applicable
	1823	+|(% style="width:366px" %)KeyValues|(% style="width:284px" %)Metadata type – not applicable
	1824	+|(% style="width:366px" %)IdentifiableReference|(% style="width:284px" %)Metadata type – not applicable
	1825	+|(% style="width:366px" %)DataSetReference|(% style="width:284px" %)Metadata type – not applicable
	1826	+|(% style="width:366px" %)AttachmentConstraintReference|(% style="width:284px" %)Metadata type – not applicable
2085	2085
2086		-
2087		-
2088	2088	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
2089	2089
2090	2090	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).
...	...	@@ -2093,89 +2093,84 @@
2093	2093
2094	2094	The following table describes the default conversion from the VTL basic scalar types to the SDMX data types .
2095	2095
2096		-|**VTL basic scalar type**|**Default SDMX data type (BasicComponentDataType)**|**Default output format**
2097		-|**String**|**String **|Like XML (xs:string)
2098		-|**Number**|**Float **|Like XML (xs:float)
2099		-|**Integer**|**Integer **|Like XML (xs:int)
2100		-|**Date**|**DateTime**|YYYY-MM-DDT00:00:00Z
2101		-|**Time**|**StandardTimePeriod**|<date>/<date> (as defined above)
2102		-|**time_period**|(((
2103		-**ReportingTimePeriod**
2104		-
2105		-**(StandardReportingPeriod)**
2106		-)))|(((
	1836	+(% style="width:923.835px" %)
	1837	+|(% style="width:191px" %)**VTL basic scalar type**|(% style="width:419px" %)**Default SDMX data type (BasicComponentDataType)**|(% style="width:311px" %)**Default output format**
	1838	+|(% style="width:191px" %)**String**|(% style="width:419px" %)**String **|(% style="width:311px" %)Like XML (xs:string)
	1839	+|(% style="width:191px" %)**Number**|(% style="width:419px" %)**Float **|(% style="width:311px" %)Like XML (xs:float)
	1840	+|(% style="width:191px" %)**Integer**|(% style="width:419px" %)**Integer **|(% style="width:311px" %)Like XML (xs:int)
	1841	+|(% style="width:191px" %)**Date**|(% style="width:419px" %)**DateTime**|(% style="width:311px" %)YYYY-MM-DDT00:00:00Z
	1842	+|(% style="width:191px" %)**Time**|(% style="width:419px" %)**StandardTimePeriod**|(% style="width:311px" %)<date>/<date> (as defined above)
	1843	+|(% style="width:191px" %)**time_period**|(% style="width:419px" %)(((
	1844	+**ReportingTimePeriod
	1845	+(StandardReportingPeriod)**
	1846	+)))|(% style="width:311px" %)(((
2107	2107	YYYY-Pppp
2108		-
2109	2109	(according to SDMX )
2110	2110	)))
2111		-|**Duration**|**Duration **|(((
	1850	+|(% style="width:191px" %)**Duration**|(% style="width:419px" %)**Duration **|(% style="width:311px" %)(((
2112	2112	Like XML (xs:duration)
2113		-
2114	2114	PnYnMnDTnHnMnS
2115	2115	)))
2116		-|**Boolean**|**Boolean **|(((
2117		-Like XML (xs:boolean) with the values
2118		-
2119		-“true” or “false”
	1854	+|(% style="width:191px" %)**Boolean**|(% style="width:419px" %)**Boolean **|(% style="width:311px" %)(((
	1855	+Like XML (xs:boolean) with the values “true” or “false”
2120	2120	)))
2121	2121
2122	2122	**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
2123	2123
2124		-In case a different default conversion is desired, it can be achieved through the
	1860	+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).
2125	2125
2126		-CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
2127		-
2128	2128	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.
2129	2129
2130		-|(% colspan="2" %)**VTL special characters for the formatting masks**
2131		-|(% colspan="2" %)** **
2132		-|(% colspan="2" %)**Number **
2133		-|D|one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
2134		-|E|one numeric digit (for the exponent of the scientific notation)
2135		-|.    (dot)|possible separator between the integer and the decimal parts.
2136		-|,   (comma)|possible separator between the integer and the decimal parts.
2137		-| |
2138		-|(% colspan="2" %)**Time and duration**
2139		-|C |century
2140		-|Y|year
2141		-|S|semester
2142		-|Q|quarter
2143		-|M|month
2144		-|W|week
2145		-|D|day
2146		-|h |hour digit (by default on 24 hours)
2147		-|M|minute
2148		-|S|second
2149		-|D|decimal of second
2150		-|P|period indicator (representation in one digit for the duration)
2151		-|P|number of the periods specified in the period indicator
2152		-|AM/PM |indicator of AM / PM (e.g. am/pm for “am” or “pm”)
2153		-|MONTH|uppercase textual representation of the month (e.g., JANUARY for January)
2154		-|DAY|uppercase textual representation of the day (e.g., MONDAY for Monday)
2155		-|Month|lowercase textual representation of the month (e.g., january)
2156		-|Day|lowercase textual representation of the month (e.g., monday)
2157		-|Month|First character uppercase, then lowercase textual representation of the month (e.g., January)
2158		-|Day|First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
2159		-| |
2160		-|(% colspan="2" %)**String  **
2161		-|X|any string character
2162		-|Z|any string character from “A” to “z”
2163		-|9|any string character from “0” to “9”
2164		-| |
2165		-|(% colspan="2" %)**Boolean **
2166		-|B|Boolean using “true” for True and “false” for False
2167		-|1|Boolean using “1” for True and “0” for False
2168		-|0|Boolean using “0” for True and “1” for False
2169		-| |
2170		-|(% colspan="2" %)Other qualifiers
2171		-|*|an arbitrary number of digits (of the preceding type)
2172		-|+|at least one digit (of the preceding type)
2173		-|( )|optional digits (specified within the brackets)
2174		-|\|prefix for the special characters that must appear in the mask
2175		-|N|fixed number of digits used in the preceding  textual representation of the month or the day
2176		-| |
	1864	+(% style="width:671.835px" %)
	1865	+|(% colspan="2" style="width:669px" %)**VTL special characters for the formatting masks**
	1866	+|(% colspan="2" style="width:669px" %)** **
	1867	+|(% colspan="2" style="width:669px" %)**Number **
	1868	+|(% style="width:141px" %)D|(% style="width:528px" %)one numeric digit (if the scientific notation is adopted, D is only for the mantissa)
	1869	+|(% style="width:141px" %)E|(% style="width:528px" %)one numeric digit (for the exponent of the scientific notation)
	1870	+|(% style="width:141px" %).(dot)|(% style="width:528px" %)possible separator between the integer and the decimal parts.
	1871	+|(% style="width:141px" %),(comma)|(% style="width:528px" %)possible separator between the integer and the decimal parts.
	1872	+|(% style="width:141px" %) |(% style="width:528px" %)
	1873	+|(% colspan="2" style="width:669px" %)**Time and duration**
	1874	+|(% style="width:141px" %)C |(% style="width:528px" %)century
	1875	+|(% style="width:141px" %)Y|(% style="width:528px" %)year
	1876	+|(% style="width:141px" %)S|(% style="width:528px" %)semester
	1877	+|(% style="width:141px" %)Q|(% style="width:528px" %)quarter
	1878	+|(% style="width:141px" %)M|(% style="width:528px" %)month
	1879	+|(% style="width:141px" %)W|(% style="width:528px" %)week
	1880	+|(% style="width:141px" %)D|(% style="width:528px" %)day
	1881	+|(% style="width:141px" %)h |(% style="width:528px" %)hour digit (by default on 24 hours)
	1882	+|(% style="width:141px" %)M|(% style="width:528px" %)minute
	1883	+|(% style="width:141px" %)S|(% style="width:528px" %)second
	1884	+|(% style="width:141px" %)D|(% style="width:528px" %)decimal of second
	1885	+|(% style="width:141px" %)P|(% style="width:528px" %)period indicator (representation in one digit for the duration)
	1886	+|(% style="width:141px" %)P|(% style="width:528px" %)number of the periods specified in the period indicator
	1887	+|(% style="width:141px" %)AM/PM |(% style="width:528px" %)indicator of AM / PM (e.g. am/pm for “am” or “pm”)
	1888	+|(% style="width:141px" %)MONTH|(% style="width:528px" %)uppercase textual representation of the month (e.g., JANUARY for January)
	1889	+|(% style="width:141px" %)DAY|(% style="width:528px" %)uppercase textual representation of the day (e.g., MONDAY for Monday)
	1890	+|(% style="width:141px" %)Month|(% style="width:528px" %)lowercase textual representation of the month (e.g., january)
	1891	+|(% style="width:141px" %)Day|(% style="width:528px" %)lowercase textual representation of the month (e.g., monday)
	1892	+|(% style="width:141px" %)Month|(% style="width:528px" %)First character uppercase, then lowercase textual representation of the month (e.g., January)
	1893	+|(% style="width:141px" %)Day|(% style="width:528px" %)First character uppercase, then lowercase textual representation of the day using (e.g. Monday)
	1894	+|(% style="width:141px" %) |(% style="width:528px" %)
	1895	+|(% colspan="2" style="width:669px" %)**String**
	1896	+|(% style="width:141px" %)X|(% style="width:528px" %)any string character
	1897	+|(% style="width:141px" %)Z|(% style="width:528px" %)any string character from “A” to “z”
	1898	+|(% style="width:141px" %)9|(% style="width:528px" %)any string character from “0” to “9”
	1899	+|(% style="width:141px" %) |(% style="width:528px" %)
	1900	+|(% colspan="2" style="width:669px" %)**Boolean **
	1901	+|(% style="width:141px" %)B|(% style="width:528px" %)Boolean using “true” for True and “false” for False
	1902	+|(% style="width:141px" %)1|(% style="width:528px" %)Boolean using “1” for True and “0” for False
	1903	+|(% style="width:141px" %)0|(% style="width:528px" %)Boolean using “0” for True and “1” for False
	1904	+|(% style="width:141px" %) |(% style="width:528px" %)
	1905	+|(% colspan="2" style="width:669px" %)Other qualifiers
	1906	+|(% style="width:141px" %)*|(% style="width:528px" %)an arbitrary number of digits (of the preceding type)
	1907	+|(% style="width:141px" %)+|(% style="width:528px" %)at least one digit (of the preceding type)
	1908	+|(% style="width:141px" %)( )|(% style="width:528px" %)optional digits (specified within the brackets)
	1909	+|(% style="width:141px" %)\|(% style="width:528px" %)prefix for the special characters that must appear in the mask
	1910	+|(% style="width:141px" %)N|(% style="width:528px" %)fixed number of digits used in the preceding textual representation of the month or the day
	1911	+|(% style="width:141px" %) |(% style="width:528px" %)
2177	2177
2178		-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" %)^^~[43~]^^>>path:#_ftn43]](%%).
	1913	+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" %)^^~[43~]^^>>path:#_ftn43]](%%).
2179	2179
2180	2180	=== 10.4.5 Null Values ===
2181	2181
...	...	@@ -2183,22 +2183,20 @@
2183	2183
2184	2184	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.
2185	2185
2186		-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.
	1921	+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.
2187	2187
2188	2188	=== 10.4.6 Format of the literals used in VTL transformations ===
2189	2189
2190	2190	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.
2191	2191
2192		-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.
	1927	+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.
2193	2193
2194	2194	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.
2195	2195
2196	2196	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).
2197	2197
2198		-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
	1933	+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.
2199	2199
2200		-TransformationScheme.
2201		-
2202	2202	In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats.
2203	2203
2204	2204	= 11 Annex I: How to eliminate extra element in the .NET SDMX Web Service =
...	...	@@ -2207,12 +2207,18 @@
2207	2207
2208	2208	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”.
2209	2209
2210		-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:
	1943	+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:
2211	2211
	1945	+[[image:1747854006117-843.png]]
	1946	+
2212	2212	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.
2213	2213
2214	2214	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:
2215	2215
	1951	+[[image:1747854039499-443.png]]
	1952	+
	1953	+[[image:1747854067769-691.png]]
	1954	+
2216	2216	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.
2217	2217
2218	2218	== 11.2 Solution ==
...	...	@@ -2233,20 +2233,30 @@
2233	2233
2234	2234	To understand how the **XmlAnyElement** attribute works we present the following two web methods:
2235	2235
2236		-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.
	1975	+[[image:1747854096778-844.png]]
2237	2237
2238		-The difference between the two is that for the first method, **SubmitXml**, the
	1977	+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.
2239	2239
2240		-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.
	1979	+[[image:1747854127303-270.png]]
2241	2241
	1981	+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.
	1982	+
	1983	+[[image:1747854163928-581.png]]
	1984	+
2242	2242	Now we look at the message for the method that uses the **XmlAnyElement** attribute.
2243	2243
	1987	+[[image:1747854190641-364.png]]
	1988	+
	1989	+[[image:1747854236732-512.png]]
	1990	+
2244	2244	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.
2245	2245
2246		-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]]
	1993	+For more information please consult: [[http:~~/~~/msdn.microsoft.com/en-us/library/aa480498.aspx>>http://msdn.microsoft.com/en-us/library/aa480498.aspx]]
2247	2247
2248	2248	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.
2249	2249
	1997	+[[image:1747854286398-614.png]]
	1998	+
2250	2250	Without a common WSDL still the solution doesn’t enforce interoperability. In order to
2251	2251
2252	2252	“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.
...	...	@@ -2259,16 +2259,27 @@
2259	2259
2260	2260	In the context of the SDMX Web Service, applying the above solution translates into the following:
2261	2261
	2011	+[[image:1747854385465-132.png]]
	2012	+
2262	2262	The SOAP request/response will then be as follows:
2263	2263
2264	2264	**GenericData Request**
2265	2265
	2017	+[[image:1747854406014-782.png]]
	2018	+
2266	2266	**GenericData Response**
2267	2267
	2021	+[[image:1747854424488-855.png]]
	2022	+
2268	2268	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:
2269	2269
	2025	+[[image:1747854453895-524.png]]
	2026	+
	2027	+[[image:1747854476631-125.png]]
	2028	+
2270	2270	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:
2271	2271
	2031	+[[image:1747854493363-776.png]]
2272	2272
2273	2273	----
2274	2274
...	...	@@ -2296,15 +2296,15 @@
2296	2296
2297	2297	[[~[12~]>>path:#_ftnref12]] In case the invoked artefact is a VTL component, which can be invoked only within the invocation of a
2298	2298
2299		-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.
	2059	+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.
2300	2300
2301		-[[~[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)
	2061	+[[~[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)
2302	2302
2303	2303	[[~[14~]>>path:#_ftnref14]] Single quotes are needed because this reference is not a VTL regular name.
2304	2304
2305	2305	[[~[15~]>>path:#_ftnref15]] Single quotes are not needed in this case because CL_FREQ is a VTL regular name.
2306	2306
2307		-[[~[16~]>>path:#_ftnref16]] The result DFR(1.0)  is be equal to DF1(1.0) save that the component SECTOR is called SEC
	2067	+[[~[16~]>>path:#_ftnref16]] The result DFR(1.0) is be equal to DF1(1.0) save that the component SECTOR is called SEC
2308	2308
2309	2309	[[~[17~]>>path:#_ftnref17]] Rulesets of this kind cannot be reused when the referenced Concept has a different representation.
2310	2310
...	...	@@ -2320,7 +2320,7 @@
2320	2320
2321	2321	[[~[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.
2322	2322
2323		-[[~[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
	2083	+[[~[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
2324	2324
2325	2325	[[~[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.
2326	2326
...	...	@@ -2328,7 +2328,7 @@
2328	2328
2329	2329	[[~[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.
2330	2330
2331		-[[~[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.
	2091	+[[~[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.
2332	2332
2333	2333	[[~[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.
2334	2334
...	...	@@ -2336,13 +2336,13 @@
2336	2336
2337	2337	[[~[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.
2338	2338
2339		-[[~[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). ^^ ^^
	2099	+[[~[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). ^^ ^^
2340	2340
2341		-[[~[33~]>>path:#_ftnref33]] In case  the ordered concatenation notation is used, the VTL Transformation described above, e.g.
	2101	+[[~[33~]>>path:#_ftnref33]] In case the ordered concatenation notation is used, the VTL Transformation described above, e.g.
2342	2342
2343		-‘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.
	2103	+‘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.
2344	2344
2345		-[[~[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..
	2105	+[[~[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..
2346	2346
2347	2347	[[~[35~]>>path:#_ftnref35]] This is possible as each VTL dataset corresponds to one particular combination of values of INDICATOR and COUNTRY
2348	2348
...	...	@@ -2361,3 +2361,5 @@
2361	2361	[[~[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.
2362	2362
2363	2363	[[~[43~]>>path:#_ftnref43]] The representation given in the DSD should obviously be compatible with the VTL data type.
	2124	+
	2125	+{{putFootnotes/}}

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