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

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...	...	@@ -13,8 +13,10 @@
13	13
14	14	== 1.1 Purpose ==
15	15
16		-The intention of this document is to document certain aspects of SDMX that are important to understand and will aid implementation decisions. The explanations here supplement the information documented in the SDMX XML schema and the Information Model.
	16	+The intention of this document is to document certain aspects of SDMX that are important to understand and will aid implementation decisions. The explanations here supplement the information documented in the SDMX XML schema and the
17	17
	18	+Information Model.
	19	+
18	18	== 1.2 Structure ==
19	19
20	20	This document is organized into the following major parts:
...	...	@@ -39,7 +39,7 @@
39	39
40	40	== 3.2 SDMX Information Model for Format Implementers ==
41	41
42		-=== 3.2.1 Introduction ===
	44	+=== 3.2.1 Introduction ===
43	43
44	44	The purpose of this sub-section is to provide an introduction to the SDMX-IM relating to Data Structure Definitions and Data Sets for those whose primary interest is in the use of the XML or EDI formats.  For those wishing to have a deeper understanding of the Information Model, the full SDMX-IM document, and other sections in this guide provide a more in-depth view, along with UML diagrams and supporting explanation. For those who are unfamiliar with DSDs, an appendix to the SDMX-IM provides a tutorial which may serve as a useful introduction.
45	45
...	...	@@ -47,12 +47,16 @@
47	47
48	48	The Data Structure Definition and Data Set parts of the information model are consistent with the GESMES/TS version 3.0 Data Model (called SDMX-EDI in the SDMX standard), with these exceptions:
49	49
50		-* the “sibling group” construct has been generalized to permit any dimension or dimensions to be wildcarded, and not just frequency, as in GESMES/TS. It has been renamed a “group” to distinguish it from the “sibling group” where only frequency is wildcarded. The set of allowable partial “group” keys must be declared in the DSD, and attributes may be attached to any of these group keys;
51		-* furthermore, whilst the “group” has been retained for compatibility with version 2.0 and with SDMX-EDI, it has, at version 2.1, been replaced by the “Attribute Relationship” definition which is explained later
52		-* the section on data representation is now a convention, to support interoperability with EDIFACT-syntax implementations ( see section 3.3.2);
	52	+the “sibling group” construct has been generalized to permit any dimension or dimensions to be wildcarded, and not just frequency, as in GESMES/TS. It has been renamed a “group” to distinguish it from the “sibling group” where only frequency is wildcarded. The set of allowable partial “group” keys must be declared in the DSD, and attributes may be attached to any of these group keys;
53	53
54		-DSD-specific data formats are derived from the model, and some supporting features for declaring multiple measures have been added to the structural metadata descriptions Clearly, this is not a coincidence. The GESMES/TS Data Model provides the foundation for the EDIFACT messages in SDMX-EDI, and also is the starting point for the development of SDMX-ML.
	54	+furthermore, whilst the “group” has been retained for compatibility with version 2.0 and with SDMX-EDI, it has, at version 2.1, been replaced by the “Attribute Relationship” definition which is explained later
55	55
	56	+the section on data representation is now a convention, to support interoperability with EDIFACT-syntax implementations ( see section 3.3.2);
	57	+
	58	+DSD-specific data formats are derived from the model, and some supporting features for declaring multiple measures have been added to the structural metadata descriptions
	59	+
	60	+Clearly, this is not a coincidence. The GESMES/TS Data Model provides the foundation for the EDIFACT messages in SDMX-EDI, and also is the starting point for the development of SDMX-ML.
	61	+
56	56	Note that in the descriptions below, text in courier and italicised are the names used in the information model (e.g. //DataSet//).
57	57
58	58	== 3.3 SDMX-ML and SDMX-EDI: Comparison of Expressive Capabilities and Function ==
...	...	@@ -59,16 +59,22 @@
59	59
60	60	SDMX offers several equivalent formats for describing data and structural metadata, optimized for use in different applications. Although all of these formats are derived directly from the SDM-IM, and are thus equivalent, the syntaxes used to express the model place some restrictions on their use. Also, different optimizations provide different capabilities. This section describes these differences, and provides some rules for applications which may need to support more than one SDMX format or syntax. This section is constrained to the Data Structure Definitionand the Date Set.
61	61
62		-=== 3.3.1 Format Optimizations and Differences ===
	68	+=== 3.3.1 Format Optimizations and Differences ===
63	63
64	64	The following section provides a brief overview of the differences between the various SDMX formats.
65	65
66		-Version 2.0 was characterised by 4 data messages, each with a distinct format: Generic, Compact, Cross-Sectional and Utility. Because of the design, data in some formats could not always be related to another format. In version 2.1, this issue has been addressed by merging some formats and eliminating others. As a result, in SDMX 2.1 there are just two types of data formats: //GenericData// and //StructureSpecificData// (i.e. specific to one Data Structure Definition).
	72	+Version 2.0 was characterised by 4 data messages, each with a distinct format: Generic, Compact, Cross-Sectional and Utility. Because of the design, data in some formats could not always be related to another format. In version 2.1, this issue has been addressed by merging some formats and eliminating others. As a result, in
67	67
	74	+SDMX 2.1 there are just two types of data formats: //GenericData// and
	75	+
	76	+//StructureSpecificData// (i.e. specific to one Data Structure Definition).
	77	+
68	68	Both of these formats are now flexible enough to allow for data to be oriented in series with any dimension used to disambiguate the observations (as opposed to only time or a cross sectional measure in version 2.0). The formats have also been expanded to allow for ungrouped observations.
69	69
70		-To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages; //GenericTimeSeriesData// and //StructureSpecificTimeSeriesData//. It is important to note that these variations are built on the same root structure and can be processed in the same manner as the base format so that they do NOT introduce additional processing requirements.
	80	+To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages;
71	71
	82	+//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.
	83	+
72	72	=== //Structure Definition// ===
73	73
74	74	The SDMX-ML Structure Message supports the use of annotations to the structure, which is not supported by the SDMX-EDI syntax.
...	...	@@ -77,8 +77,10 @@
77	77
78	78	=== //Validation// ===
79	79
80		-SDMX-EDI – as is typical of EDIFACT syntax messages – leaves validation to dedicated applications (“validation” being the checking of syntax, data typing, and adherence of the data message to the structure as described in the structural definition.)
	92	+SDMX-EDI – as is typical of EDIFACT syntax messages – leaves validation to dedicated applications (“validation” being the checking of syntax, data typing, and adherence of the data message to the structure as described in the structural
81	81
	94	+definition.)
	95	+
82	82	The SDMX-ML Generic Data Message also leaves validation above the XML syntax level to the application.
83	83
84	84	The SDMX-ML DSD-specific messages will allow validation of XML syntax and datatyping to be performed with a generic XML parser, and enforce agreement between the structural definition and the data to a moderate degree with the same tool.
...	...	@@ -89,13 +89,17 @@
89	89
90	90	=== //Character Encodings// ===
91	91
92		-All SDMX-ML messages use the UTF-8 encoding, while SDMX-EDI uses the ISO 8879-1 character encoding. There is a greater capacity with UTF-8 to express some character sets (see the “APPENDIX: MAP OF ISO 8859-1 (UNOC) CHARACTER SET (LATIN 1 OR “WESTERN”) in the document “SYNTAX AND DOCUMENTATION VERSION 2.0”.) Many transformation tools are available which allow XML instances with UTF-8 encodings to be expressed as ISO 8879-1-encoded characters, and to transform UTF-8 into ISO 8879-1. Such tools should be used when transforming SDMX-ML messages into SDMX-EDI messages and vice-versa.
	106	+All SDMX-ML messages use the UTF-8 encoding, while SDMX-EDI uses the ISO 8879-1 character encoding. There is a greater capacity with UTF-8 to express some character sets (see the “APPENDIX: MAP OF ISO 8859-1 (UNOC) CHARACTER
93	93
	108	+SET (LATIN 1 OR “WESTERN”) in the document “SYNTAX AND
	109	+
	110	+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.
	111	+
94	94	=== //Data Typing// ===
95	95
96	96	The XML syntax and EDIFACT syntax have different data-typing mechanisms. The section below provides a set of conventions to be observed when support for messages in both syntaxes is required. For more information on the SDMX-ML representations of data, see below.
97	97
98		-==== 3.3.2 Data Types ====
	116	+==== 3.3.2 Data Types ====
99	99
100	100	The XML syntax has a very different mechanism for data-typing than the EDIFACT syntax, and this difference may create some difficulties for applications which support both EDIFACT-based and XML-based SDMX data formats. This section provides a set of conventions for the expression in data in all formats, to allow for clean interoperability between them.
101	101
...	...	@@ -111,8 +111,7 @@
111	111	1*. Maximum 70 characters.
112	112	1*. From ISO 8859-1 character set (including accented characters)
113	113	1. **Descriptions **are:
114		-1*. Maximum 350 characters;
115		-1*. From ISO 8859-1 character set.
	132	+1*. Maximum 350 characters;  From ISO 8859-1 character set.
116	116	1. **Code values** are:
117	117	1*. Maximum 18 characters;
118	118	1*. Any of A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore), / (solidus, slash), = (equal sign), - (hyphen);
...	...	@@ -121,43 +121,37 @@
121	121
122	122	A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore)
123	123
124		-**5. Observation values** are:
	141	+1. **Observation values** are:
	142	+1*. Decimal numerics (signed only if they are negative);
	143	+1*. The maximum number of significant figures is:
	144	+1*. 15 for a positive number
	145	+1*. 14 for a positive decimal or a negative integer
	146	+1*. 13 for a negative decimal
	147	+1*. Scientific notation may be used.
	148	+1. **Uncoded statistical concept** text values are:
	149	+1*.
	150	+1**. Maximum 1050 characters;
	151	+1**. From ISO 8859-1 character set.
	152	+1. **Time series keys**:
125	125
126		-* Decimal numerics (signed only if they are negative);
127		-* The maximum number of significant figures is:
128		-* 15 for a positive number
129		-* 14 for a positive decimal or a negative integer
130		-* 13 for a negative decimal
131		-* Scientific notation may be used.
	154	+In principle, the maximum permissible length of time series keys used in a data exchange does not need to be restricted. However, for working purposes, an effort is made to limit the maximum length to 35 characters; in this length, also (for SDMXEDI) one (separator) position is included between all successive dimension values; this means that the maximum length allowed for a pure series key (concatenation of dimension values) can be less than 35 characters.  The separator character is a colon (“:”) by conventional usage.
132	132
133		-**6. Uncoded statistical concept** text values are:
134		-
135		-* Maximum 1050 characters;
136		-* From ISO 8859-1 character set.
137		-
138		-**7. Time series keys**:
139		-
140		-In principle, the maximum permissible length of time series keys used in a data exchange does not need to be restricted. However, for working purposes, an effort is made to limit the maximum length to 35 characters; in this length, also (for SDMXEDI) one (separator) position is included between all successive dimension values; this means that the maximum length allowed for a pure series key (concatenation of dimension values) can be less than 35 characters. The separator character is a colon (“:”) by conventional usage.
141		-
142	142	== 3.4 SDMX-ML and SDMX-EDI Best Practices ==
143	143
144		-=== 3.4.1 Reporting and Dissemination Guidelines ===
	158	+=== 3.4.1 Reporting and Dissemination Guidelines ===
145	145
146		-==== 3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges ====
	160	+**3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges **Central institutions are the organisations to which other partner institutions "report" statistics. These statistics are used by central institutions either to compile aggregates and/or they are put together and made available in a uniform manner (e.g. on-line or on a CD-ROM or through file transfers). Therefore, central institutions receive data from other institutions and, usually, they also "disseminate" data to individual and/or institutions for end-use.  Within a country, a NSI or a national central bank (NCB) plays, of course, a central institution role as it collects data from other entities and it disseminates statistical information to end users. In SDMX the role of central institution is very important: every statistical message is based on underlying structural definitions (statistical concepts, code lists, DSDs) which have been devised by a particular agency, usually a central institution. Such an institution plays the role of the reference "structural definitions maintenance agency" for the corresponding messages which are exchanged. Of course, two institutions could exchange data using/referring to structural information devised by a third institution.
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.
149		-
150	150	Central institutions can play a double role:
151	151
152	152	* collecting and further disseminating statistics;
153	153	* devising structural definitions for use in data exchanges.
154	154
155		-==== 3.4.1.2 Defining Data Structure Definitions (DSDs) ====
	167	+**3.4.1.2 Defining Data Structure Definitions (DSDs)**
156	156
157	157	The following guidelines are suggested for building a DSD. However, it is expected that these guidelines will be considered by central institutions when devising new DSDs.
158	158
159		-(% class="wikigeneratedid" id="HDimensions2CAttributesandCodeLists" %)
160		-__Dimensions, Attributes and Code Lists__
	171	+=== Dimensions, Attributes and Code Lists ===
161	161
162	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
...	...	@@ -187,8 +187,7 @@
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		-__Data Structure Definition Structure__
	201	+=== 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:
194	194
...	...	@@ -218,7 +218,7 @@
218	218	* code list name
219	219	* code values and descriptions
220	220
221		-Definition of data flow definitions. Two (or more) partners performing data exchanges in a certain context need to agree on:
	231	+Definition of data flow definitions.  Two (or more) partners performing data exchanges in a certain context need to agree on:
222	222
223	223	* the list of data set identifiers they will be using;
224	224	* for each data flow:
...	...	@@ -225,12 +225,10 @@
225	225	* its content and description
226	226	* the relevant DSD that defines the structure of the data reported or disseminated according the the dataflow definition
227	227
228		-==== 3.4.1.3 Exchanging Attributes ====
	238	+**3.4.1.3 Exchanging Attributes**
229	229
230		-===== //3.4.1.3.1 Attributes on series, sibling and data set level // =====
	240	+**//3.4.1.3.1 Attributes on series, sibling and data set level //**//Static properties//.
231	231
232		-//Static properties//.
233		-
234	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.
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.
...	...	@@ -247,21 +247,21 @@
247	247	* If the “observation status” changes and the observation remains unchanged, both components would have to be reported.
248	248	* For Data Structure Definitions having also the observation level attributes “observation confidentiality” and "observation pre-break" defined, this rule applies to these attribute as well: if an institution receives from another institution an observation with an observation status attribute only attached, this means that the associated observation confidentiality and prebreak observation attributes either never existed or from now they do not have a value for this observation.
249	249
250		-=== 3.4.2 Best Practices for Batch Data Exchange ===
	258	+==== 3.4.2 Best Practices for Batch Data Exchange ====
251	251
252		-==== 3.4.2.1 Introduction ====
	260	+**3.4.2.1 Introduction**
253	253
254	254	Batch data exchange is the exchange and maintenance of entire databases between counterparties. It is an activity that often employs SDMX-EDI formats, and might also use the SDMX-ML DSD-specific data set. The following points apply equally to both formats.
255	255
256		-==== 3.4.2.2 Positioning of the Dimension "Frequency" ====
	264	+**3.4.2.2 Positioning of the Dimension "Frequency"**
257	257
258	258	The position of the “frequency” dimension is unambiguously identified in the data structure definition. Moreover, most central institutions devising structural definitions have decided to assign to this dimension the first position in the key structure. This facilitates the easy identification of this dimension, something that it is necessary to frequency's crucial role in several database systems and in attaching attributes at the “sibling” group level.
259	259
260		-==== 3.4.2.3 Identification of Data Structure Definitions (DSDs) ====
	268	+**3.4.2.3 Identification of Data Structure Definitions (DSDs)**
261	261
262	262	In order to facilitate the easy and immediate recognition of the structural definition maintenance agency that defined a data structure definition, most central institutions devising structural definitions use the first characters of the data structure definition identifiers to identify their institution: e.g. BIS_EER, EUROSTAT_BOP_01, ECB_BOP1, etc.
263	263
264		-==== 3.4.2.4 Identification of the Data Flows ====
	272	+**3.4.2.4 Identification of the Data Flows**
265	265
266	266	In order to facilitate the easy and immediate recognition of the institution administrating a data flow definitions, many central institutions prefer to use the first characters of the data flow definition identifiers to identify their institution: e.g. BIS_EER, ECB_BOP1, ECB_BOP1, etc. Note that in GESMES/TS the Data Set plays the role of the data flow definition (see //DataSet //in the SDMX-IM//)//.
267	267
...	...	@@ -269,7 +269,7 @@
269	269
270	270	Note that the role of the Data Flow (called //DataflowDefintion// in the model) and Data Set is very specific in the model, and the terminology used may not be the same as used in all organisations, and specifically the term Data Set is used differently in SDMX than in GESMES/TS. Essentially the GESMES/TS term "Data Set" is, in SDMX, the "Dataflow Definition" whist the term "Data Set" in SDMX is used to describe the "container" for an instance of the data.
271	271
272		-==== 3.4.2.5 Special Issues ====
	280	+**3.4.2.5 Special Issues**
273	273
274	274	===== 3.4.2.5.1 "Frequency" related issues =====
275	275
...	...	@@ -280,6 +280,7 @@
280	280
281	281	**//Tick data.//** The issue of data collected at irregular intervals at a higher than daily frequency (e.g. tick-by-tick data) is not discussed here either. However, for data exchange purposes, such series can already be exchanged in the SDMX-EDI format by using the option to send observations with the associated time stamp.
282	282
	291	+
283	283	= 4 General Notes for Implementers =
284	284
285	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.
...	...	@@ -290,31 +290,39 @@
290	290
291	291	There are several different representations in SDMX-ML, taken from XML Schemas and common programming languages. The table below describes the various representations which are found in SDMX-ML, and their equivalents.
292	292
293		-(% style="width:912.294px" %)
294		-|(% style="width:172px" %)**SDMX-ML Data Type**|(% style="width:204px" %)**XML Schema Data Type**|(% style="width:189px" %)**.NET Framework Type**|(% style="width:342px" %)(((
295		-**Java Data Type **
	302	+|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|(((
	303	+**Java Data Type**
	304	+
	305	+**~ **
296	296	)))
297		-|(% style="width:172px" %)String|(% style="width:204px" %)xsd:string|(% style="width:189px" %)System.String|(% style="width:342px" %)java.lang.String
298		-|(% style="width:172px" %)Big Integer|(% style="width:204px" %)xsd:integer|(% style="width:189px" %)System.Decimal|(% style="width:342px" %)java.math.BigInteg er
299		-|(% style="width:172px" %)Integer|(% style="width:204px" %)xsd:int|(% style="width:189px" %)System.Int32|(% style="width:342px" %)int
300		-|(% style="width:172px" %)Long|(% style="width:204px" %)xsd.long|(% style="width:189px" %)System.Int64|(% style="width:342px" %)long
301		-|(% style="width:172px" %)Short|(% style="width:204px" %)xsd:short|(% style="width:189px" %)System.Int16|(% style="width:342px" %)short
302		-|(% style="width:172px" %)Decimal|(% style="width:204px" %)xsd:decimal|(% style="width:189px" %)System.Decimal|(% style="width:342px" %)java.math.BigDecim al
303		-|(% style="width:172px" %)Float|(% style="width:204px" %)xsd:float|(% style="width:189px" %)System.Single|(% style="width:342px" %)float
304		-|(% style="width:172px" %)Double|(% style="width:204px" %)xsd:double|(% style="width:189px" %)System.Double|(% style="width:342px" %)double
305		-|(% style="width:172px" %)Boolean|(% style="width:204px" %)xsd:boolean|(% style="width:189px" %)System.Boolean|(% style="width:342px" %)boolean
306		-|(% style="width:172px" %)URI|(% style="width:204px" %)xsd:anyURI|(% style="width:189px" %)System.Uri|(% style="width:342px" %)Java.net.URI or java.lang.String
307		-|(% style="width:172px" %)DateTime|(% style="width:204px" %)xsd:dateTime|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
308		-|(% style="width:172px" %)Time|(% style="width:204px" %)xsd:time|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
309		-|(% style="width:172px" %)GregorianYear|(% style="width:204px" %)xsd:gYear|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
310		-|(% style="width:172px" %)GregorianMonth|(% style="width:204px" %)xsd:gYearMonth|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
311		-|(% style="width:172px" %)GregorianDay|(% style="width:204px" %)xsd:date|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
312		-|(% style="width:172px" %)(((
313		-Day, MonthDay, Month
314		-)))|(% style="width:204px" %)xsd:g*|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar
315		-|(% style="width:172px" %)Duration|(% style="width:204px" %)xsd:duration |(% style="width:189px" %)System.TimeSpa|(% style="width:342px" %)javax.xml.datatype
316		-|(% style="width:172px" %) |(% style="width:204px" %) |(% style="width:189px" %)n|(% style="width:342px" %).Duration
	307	+|String|xsd:string|System.String|java.lang.String
	308	+|Big Integer|xsd:integer|System.Decimal|java.math.BigInteg er
	309	+|Integer|xsd:int|System.Int32|int
	310	+|Long|xsd.long|System.Int64|long
	311	+|Short|xsd:short|System.Int16|short
	312	+|Decimal|xsd:decimal|System.Decimal|java.math.BigDecim al
	313	+|Float|xsd:float|System.Single|float
	314	+|Double|xsd:double|System.Double|double
	315	+|Boolean|xsd:boolean|System.Boolean|boolean
	316	+|URI|xsd:anyURI|System.Uri|Java.net.URI or java.lang.String
	317	+|DateTime|xsd:dateTime|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
	318	+|Time|xsd:time|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
	319	+|GregorianYear|xsd:gYear|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
	320	+|GregorianMont h|xsd:gYearMont h|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
	321	+|GregorianDay|xsd:date|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
	322	+|(((
	323	+Day,
317	317
	325	+MonthDay, Month
	326	+)))|xsd:g*|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
	327	+|Duration|xsd:duration |System.TimeSpa|javax.xml.datatype
	328	+|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|(((
	329	+**Java Data Type**
	330	+
	331	+**~ **
	332	+)))
	333	+| | |n|.Duration
	334	+
318	318	There are also a number of SDMX-ML data types which do not have these direct correspondences, often because they are composite representations or restrictions of a broader data type. For most of these, there are simple types which can be referenced from the SDMX schemas, for others a derived simple type will be necessary:
319	319
320	320	* AlphaNumeric (common:AlphaNumericType, string which only allows A-z and 0-9)
...	...	@@ -340,8 +340,10 @@
340	340	* KeyValues (common:DataKeyType)
341	341	* IdentifiableReference (types for each identifiable object)
342	342	* DataSetReference (common:DataSetReferenceType)
343		-* AttachmentConstraintReference (common:AttachmentConstraintReferenceType)
	360	+* AttachmentConstraintReference
344	344
	362	+(common:AttachmentConstraintReferenceType)
	363	+
345	345	Data types also have a set of facets:
346	346
347	347	* isSequence = true | false (indicates a sequentially increasing value)
...	...	@@ -363,7 +363,7 @@
363	363
364	364	== 4.2 Time and Time Format ==
365	365
366		-=== 4.2.1 Introduction ===
	385	+==== 4.2.1 Introduction ====
367	367
368	368	First, it is important to recognize that most observation times are a period. SDMX specifies precisely how Time is handled.
369	369
...	...	@@ -371,47 +371,50 @@
371	371
372	372	The hierarchy of time formats is as follows (**bold** indicates a category which is made up of multiple formats, //italic// indicates a distinct format):
373	373
374		-* **Observational Time Period**
375		-** **Standard Time Period**
376		-*** **Basic Time Period**
377		-**** **Gregorian Time Period**
378		-**** //Date Time//
379		-*** **Reporting Time Period**
380		-** //Time Range//
	393	+* **Observational Time Period **o **Standard Time Period**
381	381
	395	+ § **Basic Time Period**
	396	+
	397	+* **Gregorian Time Period**
	398	+* //Date Time//
	399	+
	400	+§ **Reporting Time Period **o //Time Range//
	401	+
382	382	The details of these time period categories and of the distinct formats which make them up are detailed in the sections to follow.
383	383
384		-=== 4.2.2 Observational Time Period ===
	404	+==== 4.2.2 Observational Time Period ====
385	385
386	386	This is the superset of all time representations in SDMX. This allows for time to be expressed as any of the allowable formats.
387	387
388		-=== 4.2.3 Standard Time Period ===
	408	+==== 4.2.3 Standard Time Period ====
389	389
390	390	This is the superset of any predefined time period or a distinct point in time. A time period consists of a distinct start and end point. If the start and end of a period are expressed as date instead of a complete date time, then it is implied that the start of the period is the beginning of the start day (i.e. 00:00:00) and the end of the period is the end of the end day (i.e. 23:59:59).
391	391
392		-=== 4.2.4 Gregorian Time Period ===
	412	+==== 4.2.4 Gregorian Time Period ====
393	393
394	394	A Gregorian time period is always represented by a Gregorian year, year-month, or day. These are all based on ISO 8601 dates. The representation in SDMX-ML messages and the period covered by each of the Gregorian time periods are as follows:
395	395
396		-**Gregorian Year:**
	416	+**Gregorian Year:**
	417	+
397	397	Representation: xs:gYear (YYYY)
398		-Period: the start of January 1 to the end of December 31
399	399
400		-**Gregorian Year Month**:
	420	+Period: the start of January 1 to the end of December 31 **Gregorian Year Month**:
	421	+
401	401	Representation: xs:gYearMonth (YYYY-MM)
402		-Period: the start of the first day of the month to end of the last day of the month
403	403
404		-**Gregorian Day**:
	424	+Period: the start of the first day of the month to end of the last day of the month **Gregorian Day**:
	425	+
405	405	Representation: xs:date (YYYY-MM-DD)
	427	+
406	406	Period: the start of the day (00:00:00) to the end of the day (23:59:59)
407	407
408		-=== 4.2.5 Date Time ===
	430	+==== 4.2.5 Date Time ====
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]]
	434	+Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
413	413
414		-=== 4.2.6 Standard Reporting Period ===
	436	+==== 4.2.6 Standard Reporting Period ====
415	415
416	416	Standard reporting periods are periods of time in relation to a reporting year. Each of these standard reporting periods has a duration (based on the ISO 8601 definition) associated with it. The general format of a reporting period is as follows:
417	417
...	...	@@ -418,52 +418,75 @@
418	418	[REPORTING_YEAR]-[PERIOD_INDICATOR][PERIOD_VALUE]
419	419
420	420	Where:
	443	+
421	421	REPORTING_YEAR represents the reporting year as four digits (YYYY) PERIOD_INDICATOR identifies the type of period which determines the duration of the period
	445	+
422	422	PERIOD_VALUE indicates the actual period within the year
423	423
424	424	The following section details each of the standard reporting periods defined in SDMX:
425	425
426		-**Reporting Year**:
427		-Period Indicator: A
	450	+**Reporting Year**:
	451	+
	452	+ Period Indicator: A
	453	+
428	428	Period Duration: P1Y (one year)
	455	+
429	429	Limit per year: 1
430		-Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1)
431	431
432		-**Reporting Semester:**
433		-Period Indicator: S
	458	+Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1) **Reporting Semester:**
	459	+
	460	+ Period Indicator: S
	461	+
434	434	Period Duration: P6M (six months)
	463	+
435	435	Limit per year: 2
436		-Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2)
437	437
438		-**Reporting Trimester:**
439		-Period Indicator: T
	466	+Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2) **Reporting Trimester:**
	467	+
	468	+ Period Indicator: T
	469	+
440	440	Period Duration: P4M (four months)
	471	+
441	441	Limit per year: 3
442		-Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3)
443	443
444		-**Reporting Quarter:**
445		-Period Indicator: Q
	474	+Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3) **Reporting Quarter:**
	475	+
	476	+ Period Indicator: Q
	477	+
446	446	Period Duration: P3M (three months)
	479	+
447	447	Limit per year: 4
448		-Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4)
449	449
450		-**Reporting Month**:
	482	+Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4) **Reporting Month**:
	483	+
451	451	Period Indicator: M
	485	+
452	452	Period Duration: P1M (one month)
	487	+
453	453	Limit per year: 1
	489	+
454	454	Representation: common:ReportingMonthType (YYYY-Mmm, e.g. 2000-M12) Notes: The reporting month is always represented as two digits, therefore 1-9 are 0 padded (e.g. 01). This allows the values to be sorted chronologically using textual sorting methods.
455	455
456	456	**Reporting Week**:
	493	+
457	457	Period Indicator: W
	495	+
458	458	Period Duration: P7D (seven days)
	497	+
459	459	Limit per year: 53
	499	+
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.
462	462
	502	+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" %)^^~[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.
	503	+
463	463	**Reporting Day**:
	505	+
464	464	Period Indicator: D
	507	+
465	465	Period Duration: P1D (one day)
	509	+
466	466	Limit per year: 366
	511	+
467	467	Representation: common:ReportingDayType (YYYY-Dddd, e.g. 2000-D366) Notes: There are either 365 or 366 days in a reporting year, depending on whether the reporting year includes leap day (February 29). The reporting day is always represented as three digits, therefore 1-99 are 0 padded (e.g. 001).
468	468
469	469	This allows the values to be sorted chronologically using textual sorting methods.
...	...	@@ -474,31 +474,45 @@
474	474
475	475	Since the duration and the reporting year start day are known for any reporting period, it is possible to relate any reporting period to a distinct calendar period. The actual Gregorian calendar period covered by the reporting period can be computed as follows (based on the standard format of [REPROTING_YEAR][PERIOD_INDICATOR][PERIOD_VALUE] and the reporting year start day as [REPORTING_YEAR_START_DAY]):
476	476
477		-**~1. Determine [REPORTING_YEAR_BASE]:**
	522	+1. **Determine [REPORTING_YEAR_BASE]:**
	523	+
478	478	Combine [REPORTING_YEAR] of the reporting period value (YYYY) with [REPORTING_YEAR_START_DAY] (MM-DD) to get a date (YYYY-MM-DD).
	525	+
479	479	This is the [REPORTING_YEAR_START_DATE]
480		-**a) If the [PERIOD_INDICATOR] is W:
481		-~1. If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
	527	+
	528	+**a) If the [PERIOD_INDICATOR] is W:**
	529	+
	530	+1.
	531	+11.
	532	+111.
	533	+1111. **If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
	534	+
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:**
	537	+1.
	538	+11.
	539	+111.
	540	+1111. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
	541	+
485	485	Add^^3^^ (P0D, -P1D, -P2D, or -P3D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE].
486		-b) **Else:**
487		-The [REPORTING_YEAR_START_DATE] is the [REPORTING_YEAR_BASE]
488	488
489		-**2. Determine [PERIOD_DURATION]:**
	544	+b) **Else:**
490	490
491		-a) If the [PERIOD_INDICATOR] is A, the [PERIOD_DURATION] is P1Y.
492		-b) If the [PERIOD_INDICATOR] is S, the [PERIOD_DURATION] is P6M.
493		-c) If the [PERIOD_INDICATOR] is T, the [PERIOD_DURATION] is P4M.
494		-d) If the [PERIOD_INDICATOR] is Q, the [PERIOD_DURATION] is P3M.
495		-e) If the [PERIOD_INDICATOR] is M, the [PERIOD_DURATION] is P1M.
496		-f) If the [PERIOD_INDICATOR] is W, the [PERIOD_DURATION] is P7D.
497		-g) If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D.
	546	+The [REPORTING_YEAR_START_DATE] is the [REPORTING_YEAR_BASE].
498	498
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].
	548	+1. **Determine [PERIOD_DURATION]:**
	549	+11.
	550	+111. If the [PERIOD_INDICATOR] is A, the [PERIOD_DURATION] is P1Y.
	551	+111. If the [PERIOD_INDICATOR] is S, the [PERIOD_DURATION] is P6M.
	552	+111. If the [PERIOD_INDICATOR] is T, the [PERIOD_DURATION] is P4M.
	553	+111. If the [PERIOD_INDICATOR] is Q, the [PERIOD_DURATION] is P3M.
	554	+111. If the [PERIOD_INDICATOR] is M, the [PERIOD_DURATION] is P1M.
	555	+111. If the [PERIOD_INDICATOR] is W, the [PERIOD_DURATION] is P7D.
	556	+111. If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D.
	557	+1. **Determine [PERIOD_START]:**
501	501
	559	+Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[(% class="wikiinternallink wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
	560	+
502	502	1. **Determine the [PERIOD_END]:**
503	503
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].
...	...	@@ -1193,7 +1193,7 @@
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:
	1255	+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" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
1197	1197
1198	1198	* 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);
...	...	@@ -1217,7 +1217,7 @@
1217	1217
1218	1218	In any case, the aliases used in the VTL transformations have to be mapped to the
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.
	1279	+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" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%)  to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.
1221	1221
1222	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	1223
...	...	@@ -1227,7 +1227,7 @@
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:^^ ^^
	1289	+The SDMX URN[[(% class="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	1232	* SDMXprefix
1233	1233	* SDMX-IM-package-name
...	...	@@ -1235,7 +1235,7 @@
1235	1235	* agency-id
1236	1236	* maintainedobject-id
1237	1237	* maintainedobject-version
1238		-* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
	1297	+* container-object-id [[(% class="wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
1239	1239	* object-id
1240	1240
1241	1241	The generic structure of the URN is the following:
...	...	@@ -1254,7 +1254,7 @@
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:
	1316	+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" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
1258	1258
1259	1259	* if the artefact is a ,,Dataflow,,, which is a maintainable class,  the maintainedobject-id is the Dataflow name (dataflow-id);
1260	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;
...	...	@@ -1274,7 +1274,7 @@
1274	1274
1275	1275	* if the artefact is a ,,Concept ,,(the object-id is the name of the ,,Concept,,)
1276	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]](%%):
	1336	+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" %)^^~[10~]^^>>path:#_ftn10]](%%):
1278	1278
1279	1279	‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  <-
1280	1280
...	...	@@ -1292,14 +1292,14 @@
1292	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	1293	** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,
1294	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).
	1354	+* 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" %)^^~[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" %)^^~[12~]^^>>path:#_ftn12]](%%).
	1355	+* 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" %)^^~[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	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	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	1299
1300	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	1301
1302		-*
	1361	+*
1303	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	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.
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.,, ,,
...	...	@@ -1320,11 +1320,11 @@
1320	1320
1321	1321	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]](%%):
	1382	+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" %)^^~[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]](%%):
	1386	+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" %)^^~[15~]^^>>path:#_ftn15]](%%):
1328	1328
1329	1329	CL_FREQ
1330	1330
...	...	@@ -1334,7 +1334,7 @@
1334	1334
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]](%%):
	1396	+For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[(% class="wikiinternallink wikiinternallink" %)^^~[16~]^^>>path:#_ftn16]](%%):
1338	1338
1339	1339	‘DFR(1.0)’ := ‘DF1(1.0)’ [rename SECTOR to SEC]
1340	1340
...	...	@@ -1368,9 +1368,9 @@
1368	1368
1369	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.
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]](%%).
	1430	+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" %)^^~[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]](%%)
	1432	+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" %)^^~[18~]^^>>path:#_ftn18]](%%)
1374	1374
1375	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.
1376	1376
...	...	@@ -1384,15 +1384,15 @@
1384	1384
1385	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.
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]](%%).
	1446	+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" %)^^~[19~]^^>>path:#_ftn19]](%%).
1388	1388
1389	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).
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]](%%).
	1452	+This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="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]](%%)
	1454	+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" %)^^~[22~]^^>>path:#_ftn22]](%%)
1396	1396
1397	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.
1398	1398
...	...	@@ -1402,7 +1402,7 @@
1402	1402
1403	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.
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.
	1464	+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" %)^^~[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.
1406	1406
1407	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.
1408	1408
...	...	@@ -1466,7 +1466,7 @@
1466	1466
1467	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;
1468	1468
1469		-*
	1528	+*
1470	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	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	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
...	...	@@ -1473,7 +1473,7 @@
1473	1473
1474	1474	**10.3.3.3 From SDMX DataAttributes to VTL Measures **
1475	1475
1476		-*
	1535	+*
1477	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	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.
...	...	@@ -1492,7 +1492,7 @@
1492	1492
1493	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
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]](%%)
	1554	+PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[(% class="wikiinternallink wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)
1496	1496
1497	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	1498
...	...	@@ -1559,7 +1559,7 @@
1559	1559
1560	1560	 the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above
1561	1561
1562		-*
	1621	+*
1563	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	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	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)
...	...	@@ -1609,15 +1609,15 @@
1609	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]](%%) ===
	1671	+=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
1613	1613
1614	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
1615	1615
1616	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).
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]](%%)
	1677	+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" %)^^~[26~]^^>>path:#_ftn26]](%%)
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]](%%)
	1679	+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" %)^^~[27~]^^>>path:#_ftn27]](%%)
1621	1621
1622	1622	Given a SDMX Dataflow and some predefined Dimensions of its
1623	1623
...	...	@@ -1629,14 +1629,14 @@
1629	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.
	1691	+* 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" %)^^~[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	1634	** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated
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]]
	1695	+URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
1637	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.
	1697	+*
	1698	+** 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" %)^^~[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	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
...	...	@@ -1654,7 +1654,7 @@
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.
	1716	+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" %)^^~[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	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.
1660	1660
...	...	@@ -1664,7 +1664,7 @@
1664	1664
1665	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.
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 …).
	1726	+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" %)^^~[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	1668
1669	1669	In the example above, for all the datasets of the kind
1670	1670
...	...	@@ -1684,7 +1684,7 @@
1684	1684
1685	1685	…   …   …
1686	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]]
	1746	+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" %)^^~[33~]^^>>path:#_ftn33]]
1688	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
...	...	@@ -1707,12 +1707,12 @@
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]]
	1769	+* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)
	1770	+* 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" %)^^~[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]](%%).
	1772	+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" %)^^~[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]]
	1774	+The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]
1716	1716
1717	1717	‘DF2(1.0)///INDICATORvalue//.//COUNTRYvalue//’  <-  expression
1718	1718
...	...	@@ -1779,9 +1779,9 @@
1779	1779
1780	1780	…);
1781	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.
	1841	+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" %)^^~[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	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]]
	1843	+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" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
1785	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
...	...	@@ -1830,7 +1830,7 @@
1830	1830
1831	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).
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.
	1892	+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" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="wikiinternallink wikiinternallink" %)^^~[42~]^^>>path:#_ftn42]](%%) This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
1834	1834
1835	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
1836	1836
...	...	@@ -2175,7 +2175,7 @@
2175	2175	|N|fixed number of digits used in the preceding  textual representation of the month or the day
2176	2176	| |
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]](%%).
	2237	+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" %)^^~[43~]^^>>path:#_ftn43]](%%).
2179	2179
2180	2180	=== 10.4.5 Null Values ===
2181	2181