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Summary

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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
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.
17 17  
18 -Information Model.
19 -
20 20  == 1.2 Structure ==
21 21  
22 22  This document is organized into the following major parts:
... ... @@ -41,7 +41,7 @@
41 41  
42 42  == 3.2 SDMX Information Model for Format Implementers ==
43 43  
44 -=== 3.2.1 Introduction ===
42 +=== 3.2.1 Introduction ===
45 45  
46 46  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.
47 47  
... ... @@ -49,16 +49,12 @@
49 49  
50 50  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:
51 51  
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;
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);
53 53  
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
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.
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 -
62 62  Note that in the descriptions below, text in courier and italicised are the names used in the information model (e.g. //DataSet//).
63 63  
64 64  == 3.3 SDMX-ML and SDMX-EDI: Comparison of Expressive Capabilities and Function ==
... ... @@ -65,22 +65,16 @@
65 65  
66 66  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.
67 67  
68 -=== 3.3.1 Format Optimizations and Differences ===
62 +=== 3.3.1 Format Optimizations and Differences ===
69 69  
70 70  The following section provides a brief overview of the differences between the various SDMX formats.
71 71  
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
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).
73 73  
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 -
78 78  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.
79 79  
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;
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.
81 81  
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 -
84 84  === //Structure Definition// ===
85 85  
86 86  The SDMX-ML Structure Message supports the use of annotations to the structure, which is not supported by the SDMX-EDI syntax.
... ... @@ -89,10 +89,8 @@
89 89  
90 90  === //Validation// ===
91 91  
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
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.)
93 93  
94 -definition.)
95 -
96 96  The SDMX-ML Generic Data Message also leaves validation above the XML syntax level to the application.
97 97  
98 98  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.
... ... @@ -103,17 +103,13 @@
103 103  
104 104  === //Character Encodings// ===
105 105  
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
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.
107 107  
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 -
112 112  === //Data Typing// ===
113 113  
114 114  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.
115 115  
116 -==== 3.3.2 Data Types ====
98 +==== 3.3.2 Data Types ====
117 117  
118 118  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.
119 119  
... ... @@ -129,7 +129,8 @@
129 129  1*. Maximum 70 characters.
130 130  1*. From ISO 8859-1 character set (including accented characters)
131 131  1. **Descriptions **are:
132 -1*. Maximum 350 characters;  From ISO 8859-1 character set.
114 +1*. Maximum 350 characters;
115 +1*. From ISO 8859-1 character set.
133 133  1. **Code values** are:
134 134  1*. Maximum 18 characters;
135 135  1*. Any of A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore), / (solidus, slash), = (equal sign), - (hyphen);
... ... @@ -138,37 +138,43 @@
138 138  
139 139  A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore)
140 140  
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**:
124 +**5. Observation values** are:
153 153  
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.
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.
155 155  
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 +
156 156  == 3.4 SDMX-ML and SDMX-EDI Best Practices ==
157 157  
158 -=== 3.4.1 Reporting and Dissemination Guidelines ===
144 +=== 3.4.1 Reporting and Dissemination Guidelines ===
159 159  
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.
146 +==== 3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges ====
161 161  
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 +
162 162  Central institutions can play a double role:
163 163  
164 164  * collecting and further disseminating statistics;
165 165  * devising structural definitions for use in data exchanges.
166 166  
167 -**3.4.1.2 Defining Data Structure Definitions (DSDs)**
155 +==== 3.4.1.2 Defining Data Structure Definitions (DSDs) ====
168 168  
169 169  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.
170 170  
171 -=== Dimensions, Attributes and Code Lists ===
159 +(% class="wikigeneratedid" id="HDimensions2CAttributesandCodeLists" %)
160 +__Dimensions, Attributes and Code Lists__
172 172  
173 173  **//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.
174 174  
... ... @@ -198,7 +198,8 @@
198 198  
199 199  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.
200 200  
201 -=== Data Structure Definition Structure ===
190 +(% class="wikigeneratedid" id="HDataStructureDefinitionStructure" %)
191 +__Data Structure Definition Structure__
202 202  
203 203  The following items have to be specified by a structural definitions maintenance agency when defining a new data structure definition:
204 204  
... ... @@ -228,7 +228,7 @@
228 228  * code list name
229 229  * code values and descriptions
230 230  
231 -Definition of data flow definitions.  Two (or more) partners performing data exchanges in a certain context need to agree on:
221 +Definition of data flow definitions. Two (or more) partners performing data exchanges in a certain context need to agree on:
232 232  
233 233  * the list of data set identifiers they will be using;
234 234  * for each data flow:
... ... @@ -235,10 +235,12 @@
235 235  * its content and description
236 236  * the relevant DSD that defines the structure of the data reported or disseminated according the the dataflow definition
237 237  
238 -**3.4.1.3 Exchanging Attributes**
228 +==== 3.4.1.3 Exchanging Attributes ====
239 239  
240 -**//3.4.1.3.1 Attributes on series, sibling and data set level //**//Static properties//.
230 +===== //3.4.1.3.1 Attributes on series, sibling and data set level // =====
241 241  
232 +//Static properties//.
233 +
242 242  * 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.
243 243  * A centre may agree with its data exchange partners special procedures for authorising the setting of attributes' initial values.
244 244  * Attribute values at a data set level are set and maintained exclusively by the centre administrating the exchanged data set.
... ... @@ -255,21 +255,21 @@
255 255  * If the “observation status” changes and the observation remains unchanged, both components would have to be reported.
256 256  * 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.
257 257  
258 -==== 3.4.2 Best Practices for Batch Data Exchange ====
250 +=== 3.4.2 Best Practices for Batch Data Exchange ===
259 259  
260 -**3.4.2.1 Introduction**
252 +==== 3.4.2.1 Introduction ====
261 261  
262 262  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.
263 263  
264 -**3.4.2.2 Positioning of the Dimension "Frequency"**
256 +==== 3.4.2.2 Positioning of the Dimension "Frequency" ====
265 265  
266 266  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.
267 267  
268 -**3.4.2.3 Identification of Data Structure Definitions (DSDs)**
260 +==== 3.4.2.3 Identification of Data Structure Definitions (DSDs) ====
269 269  
270 270  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.
271 271  
272 -**3.4.2.4 Identification of the Data Flows**
264 +==== 3.4.2.4 Identification of the Data Flows ====
273 273  
274 274  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//)//.
275 275  
... ... @@ -277,7 +277,7 @@
277 277  
278 278  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.
279 279  
280 -**3.4.2.5 Special Issues**
272 +==== 3.4.2.5 Special Issues ====
281 281  
282 282  ===== 3.4.2.5.1 "Frequency" related issues =====
283 283  
... ... @@ -288,7 +288,6 @@
288 288  
289 289  **//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.
290 290  
291 -
292 292  = 4 General Notes for Implementers =
293 293  
294 294  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.
... ... @@ -299,39 +299,31 @@
299 299  
300 300  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.
301 301  
302 -|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|(((
303 -**Java Data Type**
304 -
305 -**~ **
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 **
306 306  )))
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,
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
324 324  
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 -
335 335  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:
336 336  
337 337  * AlphaNumeric (common:AlphaNumericType, string which only allows A-z and 0-9)
... ... @@ -357,10 +357,8 @@
357 357  * KeyValues (common:DataKeyType)
358 358  * IdentifiableReference (types for each identifiable object)
359 359  * DataSetReference (common:DataSetReferenceType)
360 -* AttachmentConstraintReference
343 +* AttachmentConstraintReference (common:AttachmentConstraintReferenceType)
361 361  
362 -(common:AttachmentConstraintReferenceType)
363 -
364 364  Data types also have a set of facets:
365 365  
366 366  * isSequence = true | false (indicates a sequentially increasing value)
... ... @@ -382,7 +382,7 @@
382 382  
383 383  == 4.2 Time and Time Format ==
384 384  
385 -==== 4.2.1 Introduction ====
366 +=== 4.2.1 Introduction ===
386 386  
387 387  First, it is important to recognize that most observation times are a period. SDMX specifies precisely how Time is handled.
388 388  
... ... @@ -390,50 +390,47 @@
390 390  
391 391  The hierarchy of time formats is as follows (**bold** indicates a category which is made up of multiple formats, //italic// indicates a distinct format):
392 392  
393 -* **Observational Time Period **o **Standard Time Period**
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//
394 394  
395 - § **Basic Time Period**
396 -
397 -* **Gregorian Time Period**
398 -* //Date Time//
399 -
400 -§ **Reporting Time Period **o //Time Range//
401 -
402 402  The details of these time period categories and of the distinct formats which make them up are detailed in the sections to follow.
403 403  
404 -==== 4.2.2 Observational Time Period ====
384 +=== 4.2.2 Observational Time Period ===
405 405  
406 406  This is the superset of all time representations in SDMX. This allows for time to be expressed as any of the allowable formats.
407 407  
408 -==== 4.2.3 Standard Time Period ====
388 +=== 4.2.3 Standard Time Period ===
409 409  
410 410  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).
411 411  
412 -==== 4.2.4 Gregorian Time Period ====
392 +=== 4.2.4 Gregorian Time Period ===
413 413  
414 414  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:
415 415  
416 -**Gregorian Year:**
417 -
396 +**Gregorian Year:**
418 418  Representation: xs:gYear (YYYY)
398 +Period: the start of January 1 to the end of December 31
419 419  
420 -Period: the start of January 1 to the end of December 31 **Gregorian Year Month**:
421 -
400 +**Gregorian Year Month**:
422 422  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
423 423  
424 -Period: the start of the first day of the month to end of the last day of the month **Gregorian Day**:
425 -
404 +**Gregorian Day**:
426 426  Representation: xs:date (YYYY-MM-DD)
427 -
428 428  Period: the start of the day (00:00:00) to the end of the day (23:59:59)
429 429  
430 -==== 4.2.5 Date Time ====
408 +=== 4.2.5 Date Time ===
431 431  
432 432  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.
433 433  
434 -Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
412 +Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
435 435  
436 -==== 4.2.6 Standard Reporting Period ====
414 +=== 4.2.6 Standard Reporting Period ===
437 437  
438 438  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:
439 439  
... ... @@ -440,75 +440,52 @@
440 440  [REPORTING_YEAR]-[PERIOD_INDICATOR][PERIOD_VALUE]
441 441  
442 442  Where:
443 -
444 444  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 -
446 446  PERIOD_VALUE indicates the actual period within the year
447 447  
448 448  The following section details each of the standard reporting periods defined in SDMX:
449 449  
450 -**Reporting Year**:
451 -
452 - Period Indicator: A
453 -
426 +**Reporting Year**:
427 +Period Indicator: A
454 454  Period Duration: P1Y (one year)
455 -
456 456  Limit per year: 1
430 +Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1)
457 457  
458 -Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1) **Reporting Semester:**
459 -
460 - Period Indicator: S
461 -
432 +**Reporting Semester:**
433 +Period Indicator: S
462 462  Period Duration: P6M (six months)
463 -
464 464  Limit per year: 2
436 +Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2)
465 465  
466 -Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2) **Reporting Trimester:**
467 -
468 - Period Indicator: T
469 -
438 +**Reporting Trimester:**
439 +Period Indicator: T
470 470  Period Duration: P4M (four months)
471 -
472 472  Limit per year: 3
442 +Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3)
473 473  
474 -Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3) **Reporting Quarter:**
475 -
476 - Period Indicator: Q
477 -
444 +**Reporting Quarter:**
445 +Period Indicator: Q
478 478  Period Duration: P3M (three months)
479 -
480 480  Limit per year: 4
448 +Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4)
481 481  
482 -Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4) **Reporting Month**:
483 -
450 +**Reporting Month**:
484 484  Period Indicator: M
485 -
486 486  Period Duration: P1M (one month)
487 -
488 488  Limit per year: 1
489 -
490 490  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.
491 491  
492 492  **Reporting Week**:
493 -
494 494  Period Indicator: W
495 -
496 496  Period Duration: P7D (seven days)
497 -
498 498  Limit per year: 53
499 -
500 500  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 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.
501 501  
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 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 -
504 504  **Reporting Day**:
505 -
506 506  Period Indicator: D
507 -
508 508  Period Duration: P1D (one day)
509 -
510 510  Limit per year: 366
511 -
512 512  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).
513 513  
514 514  This allows the values to be sorted chronologically using textual sorting methods.
... ... @@ -519,143 +519,109 @@
519 519  
520 520  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]):
521 521  
522 -1. **Determine [REPORTING_YEAR_BASE]:**
523 -
477 +**~1. Determine [REPORTING_YEAR_BASE]:**
524 524  Combine [REPORTING_YEAR] of the reporting period value (YYYY) with [REPORTING_YEAR_START_DAY] (MM-DD) to get a date (YYYY-MM-DD).
525 -
526 526  This is the [REPORTING_YEAR_START_DATE]
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 -
480 +**a) If the [PERIOD_INDICATOR] is W:
481 +~1. If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
535 535  Add^^3^^ (P3D, P2D, or P1D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE].
536 536  
537 -1.
538 -11.
539 -111.
540 -1111. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
541 -
484 +2. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
542 542  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]
543 543  
544 -b) **Else:**
489 +**2. Determine [PERIOD_DURATION]:**
545 545  
546 -The [REPORTING_YEAR_START_DATE] is the [REPORTING_YEAR_BASE].
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.
547 547  
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]:**
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 wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
558 558  
559 -Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
560 -
561 -1. **Determine the [PERIOD_END]:**
562 -
502 +**4. Determine the [PERIOD_END]:**
563 563  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].
564 564  
565 565  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).
566 566  
567 -**Examples: **
507 +**Examples:**
568 568  
569 569  **2010-Q2, REPORTING_YEAR_START_DAY = ~-~-07-01 (July 1)**
570 -
571 571  ~1. [REPORTING_YEAR_START_DATE] = 2010-07-01
572 -
573 573  b) [REPORTING_YEAR_BASE] = 2010-07-01
574 -
575 -1. [PERIOD_DURATION] = P3M
576 -1. (2-1) * P3M = P3M
577 -
512 +[PERIOD_DURATION] = P3M
513 +(2-1) * P3M = P3M
578 578  2010-07-01 + P3M = 2010-10-01
579 -
580 580  [PERIOD_START] = 2010-10-01
581 -
582 582  4. 2 * P3M = P6M
583 -
584 584  2010-07-01 + P6M = 2010-13-01 = 2011-01-01
585 -
586 586  2011-01-01 + -P1D = 2010-12-31
587 -
588 588  [PERIOD_END] = 2011-12-31
589 589  
590 590  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
591 591  
592 592  **2011-W36, REPORTING_YEAR_START_DAY = ~-~-07-01 (July 1)**
593 -
594 594  ~1. [REPORTING_YEAR_START_DATE] = 2010-07-01
595 -
596 596  a) 2011-07-01 = Friday
597 -
598 598  2011-07-01 + P3D = 2011-07-04
599 -
600 600  [REPORTING_YEAR_BASE] = 2011-07-04
601 -
602 -1. [PERIOD_DURATION] = P7D
603 -1. (36-1) * P7D = P245D
604 -
528 +2. [PERIOD_DURATION] = P7D
529 +3. (36-1) * P7D = P245D
605 605  2011-07-04 + P245D = 2012-03-05
606 -
607 607  [PERIOD_START] = 2012-03-05
608 -
609 609  4. 36 * P7D = P252D
610 -
611 611  2011-07-04 + P252D =2012-03-12
612 -
613 613  2012-03-12 + -P1D = 2012-03-11
614 -
615 615  [PERIOD_END] = 2012-03-11
616 616  
617 617  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
618 618  
619 -==== 4.2.7 Distinct Range ====
539 +=== 4.2.7 Distinct Range ===
620 620  
621 621  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.
622 622  
623 -==== 4.2.8 Time Format ====
543 +=== 4.2.8 Time Format ===
624 624  
625 625  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. 
626 626  
627 -|**Code**|**Format**
628 -|**OTP**|Observational Time Period: Superset of all SDMX time formats (Gregorian Time Period, Reporting Time Period, and Time Range)
629 -|**STP**|Standard Time Period: Superset of Gregorian and Reporting Time Periods
630 -|**GTP**|Superset of all Gregorian Time Periods and date-time
631 -|**RTP**|Superset of all Reporting Time Periods
632 -|**TR**|Time Range: Start time and duration (YYYY-MMDD(Thh:mm:ss)?/<duration>)
633 -|**GY**|Gregorian Year (YYYY)
634 -|**GTM**|Gregorian Year Month (YYYY-MM)
635 -|**GD**|Gregorian Day (YYYY-MM-DD)
636 -|**DT**|Distinct Point: date-time (YYYY-MM-DDThh:mm:ss)
637 -|**RY**|Reporting Year (YYYY-A1)
638 -|**RS**|Reporting Semester (YYYY-Ss)
639 -|**RT**|Reporting Trimester (YYYY-Tt)
640 -|**RQ**|Reporting Quarter (YYYY-Qq)
641 -|**RM**|Reporting Month (YYYY-Mmm)
642 -|**Code**|**Format**
643 -|**RW**|Reporting Week (YYYY-Www)
644 -|**RD**|Reporting Day (YYYY-Dddd)
547 +(% style="width:1049.29px" %)
548 +|**Code**|(% style="width:926px" %)**Format**
549 +|**OTP**|(% style="width:926px" %)Observational Time Period: Superset of all SDMX time formats (Gregorian Time Period, Reporting Time Period, and Time Range)
550 +|**STP**|(% style="width:926px" %)Standard Time Period: Superset of Gregorian and Reporting Time Periods
551 +|**GTP**|(% style="width:926px" %)Superset of all Gregorian Time Periods and date-time
552 +|**RTP**|(% style="width:926px" %)Superset of all Reporting Time Periods
553 +|**TR**|(% style="width:926px" %)Time Range: Start time and duration (YYYY-MMDD(Thh:mm:ss)?/<duration>)
554 +|**GY**|(% style="width:926px" %)Gregorian Year (YYYY)
555 +|**GTM**|(% style="width:926px" %)Gregorian Year Month (YYYY-MM)
556 +|**GD**|(% style="width:926px" %)Gregorian Day (YYYY-MM-DD)
557 +|**DT**|(% style="width:926px" %)Distinct Point: date-time (YYYY-MM-DDThh:mm:ss)
558 +|**RY**|(% style="width:926px" %)Reporting Year (YYYY-A1)
559 +|**RS**|(% style="width:926px" %)Reporting Semester (YYYY-Ss)
560 +|**RT**|(% style="width:926px" %)Reporting Trimester (YYYY-Tt)
561 +|**RQ**|(% style="width:926px" %)Reporting Quarter (YYYY-Qq)
562 +|**RM**|(% style="width:926px" %)Reporting Month (YYYY-Mmm)
563 +|**Code**|(% style="width:926px" %)**Format**
564 +|**RW**|(% style="width:926px" %)Reporting Week (YYYY-Www)
565 +|**RD**|(% style="width:926px" %)Reporting Day (YYYY-Dddd)
645 645  
646 - **Table 1: SDMX-ML Time Format Codes**
567 +**Table 1: SDMX-ML Time Format Codes**
647 647  
648 -==== 4.2.9 Transformation between SDMX-ML and SDMX-EDI ====
569 +=== 4.2.9 Transformation between SDMX-ML and SDMX-EDI ===
649 649  
650 650  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".
651 651  
652 -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)
573 +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).
653 653  
654 654  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.
655 655  
656 656  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.
657 657  
658 -==== 4.2.10 Time Zones ====
579 +=== 4.2.10 Time Zones ===
659 659  
660 660  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):
661 661  
... ... @@ -676,7 +676,7 @@
676 676  
677 677  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.
678 678  
679 -==== 4.2.11 Representing Time Spans Elsewhere ====
600 +=== 4.2.11 Representing Time Spans Elsewhere ===
680 680  
681 681  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:
682 682  
... ... @@ -686,30 +686,29 @@
686 686  
687 687  <Series REF_PERIOD="2000-01-01T00:00:00/P2M"/>
688 688  
689 -==== 4.2.12 Notes on Formats ====
610 +=== 4.2.12 Notes on Formats ===
690 690  
691 691  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.
692 692  
693 -==== 4.2.13 Effect on Time Ranges ====
614 +=== 4.2.13 Effect on Time Ranges ===
694 694  
695 695  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.
696 696  
697 -==== 4.2.14 Time in Query Messages ====
618 +=== 4.2.14 Time in Query Messages ===
698 698  
699 699  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.
700 700  
701 701  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.
702 702  
703 -|**Operator**|**Rule**
704 -|Greater Than|Any data after the last moment of the period
705 -|Less Than|Any data before the first moment of the period
706 -|Greater Than or Equal To|(((
707 -Any data on or after the first moment of
708 -
709 -the period
624 +(% style="width:1024.29px" %)
625 +|(% style="width:238px" %)**Operator**|(% style="width:782px" %)**Rule**
626 +|(% style="width:238px" %)Greater Than|(% style="width:782px" %)Any data after the last moment of the period
627 +|(% style="width:238px" %)Less Than|(% style="width:782px" %)Any data before the first moment of the period
628 +|(% style="width:238px" %)Greater Than or Equal To|(% style="width:782px" %)(((
629 +Any data on or after the first moment of the period
710 710  )))
711 -|Less Than or Equal To|Any data on or before the last moment of the period
712 -|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
631 +|(% style="width:238px" %)Less Than or Equal To|(% style="width:782px" %)Any data on or before the last moment of the period
632 +|(% 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
713 713  
714 714  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":
715 715  
... ... @@ -1252,7 +1252,7 @@
1252 1252  
1253 1253  == 10.1 Introduction ==
1254 1254  
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 wikiinternallink" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
1175 +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" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
1256 1256  
1257 1257  * definition of validation and transformation algorithms, in order to specify how to calculate new data  from existing ones;
1258 1258  * 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);
... ... @@ -1276,7 +1276,7 @@
1276 1276  
1277 1277  In any case, the aliases used in the VTL transformations have to be mapped to the
1278 1278  
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 wikiinternallink" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%)  to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 
1199 +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" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%)  to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 
1280 1280  
1281 1281  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.
1282 1282  
... ... @@ -1286,7 +1286,7 @@
1286 1286  
1287 1287  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.
1288 1288  
1289 -The SDMX URN[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[7~]^^>>path:#_ftn7]](%%) is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:^^ ^^
1209 +The SDMX URN[[(% class="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:^^ ^^
1290 1290  
1291 1291  * SDMXprefix                                                                                   
1292 1292  * SDMX-IM-package-name             
... ... @@ -1294,7 +1294,7 @@
1294 1294  * agency-id                                                                          
1295 1295  * maintainedobject-id
1296 1296  * maintainedobject-version
1297 -* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
1217 +* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
1298 1298  * object-id
1299 1299  
1300 1300  The generic structure of the URN is the following:
... ... @@ -1313,7 +1313,7 @@
1313 1313  
1314 1314  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).
1315 1315  
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 wikiinternallink" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
1236 +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" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
1317 1317  
1318 1318  * if the artefact is a ,,Dataflow,,, which is a maintainable class,  the maintainedobject-id is the Dataflow name (dataflow-id);
1319 1319  * 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;
... ... @@ -1333,7 +1333,7 @@
1333 1333  
1334 1334  * if the artefact is a ,,Concept ,,(the object-id is the name of the ,,Concept,,)
1335 1335  
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 wikiinternallink" %)^^~[10~]^^>>path:#_ftn10]](%%):
1256 +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" %)^^~[10~]^^>>path:#_ftn10]](%%):
1337 1337  
1338 1338  ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  <-
1339 1339  
... ... @@ -1351,14 +1351,14 @@
1351 1351  * 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: 
1352 1352  ** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,  
1353 1353  ** “conceptscheme” for the classes Concept and ConceptScheme o “codelist” for the class Codelist.
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 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" %)^^~[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 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).
1274 +* 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" %)^^~[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" %)^^~[12~]^^>>path:#_ftn12]](%%).
1275 +* 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 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).
1356 1356  * 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;
1357 1357  ** 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
1358 1358  
1359 1359  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;
1360 1360  
1361 -*
1281 +*
1362 1362  ** if the referenced artefact is a ,,ConceptScheme, ,,which is a,, ,,maintainable class,,, ,,the maintained object is the ,,conceptScheme-id,, and obviously cannot be omitted;
1363 1363  ** if the referenced artefact is a ,,Codelist, ,,which is a maintainable class, the maintainedobject-id is the ,,codelist-id,, and obviously cannot be omitted.
1364 1364  * 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.,, ,,
... ... @@ -1379,11 +1379,11 @@
1379 1379  
1380 1380  DFR  :=  DF1 + DF2
1381 1381  
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 wikiinternallink" %)^^~[14~]^^>>path:#_ftn14]](%%):
1302 +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" %)^^~[14~]^^>>path:#_ftn14]](%%):
1383 1383  
1384 1384  ‘urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0)’
1385 1385  
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 wikiinternallink" %)^^~[15~]^^>>path:#_ftn15]](%%):
1306 +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" %)^^~[15~]^^>>path:#_ftn15]](%%):
1387 1387  
1388 1388  CL_FREQ
1389 1389  
... ... @@ -1393,7 +1393,7 @@
1393 1393  
1394 1394  SECTOR
1395 1395  
1396 -For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[16~]^^>>path:#_ftn16]](%%):
1316 +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" %)^^~[16~]^^>>path:#_ftn16]](%%):
1397 1397  
1398 1398  ‘DFR(1.0)’ := ‘DF1(1.0)’ [rename SECTOR to SEC]
1399 1399  
... ... @@ -1427,9 +1427,9 @@
1427 1427  
1428 1428  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. 
1429 1429  
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 wikiinternallink" %)^^~[17~]^^>>path:#_ftn17]](%%).
1350 +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" %)^^~[17~]^^>>path:#_ftn17]](%%).
1431 1431  
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 wikiinternallink" %)^^~[18~]^^>>path:#_ftn18]](%%)
1352 +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" %)^^~[18~]^^>>path:#_ftn18]](%%)
1433 1433  
1434 1434  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.
1435 1435  
... ... @@ -1443,15 +1443,15 @@
1443 1443  
1444 1444  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. 
1445 1445  
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 wikiinternallink" %)^^~[19~]^^>>path:#_ftn19]](%%).
1366 +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" %)^^~[19~]^^>>path:#_ftn19]](%%).
1447 1447  
1448 1448  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). 
1449 1449  
1450 1450  === 10.3.2 General mapping of VTL and SDMX data structures ===
1451 1451  
1452 -This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%).
1372 +This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%).
1453 1453  
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 wikiinternallink" %)^^~[22~]^^>>path:#_ftn22]](%%)
1374 +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" %)^^~[22~]^^>>path:#_ftn22]](%%)
1455 1455  
1456 1456  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.
1457 1457  
... ... @@ -1461,7 +1461,7 @@
1461 1461  
1462 1462  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. 
1463 1463  
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 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.
1384 +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" %)^^~[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.
1465 1465  
1466 1466  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. 
1467 1467  
... ... @@ -1525,7 +1525,7 @@
1525 1525  
1526 1526   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;
1527 1527  
1528 -*
1448 +*
1529 1529  ** 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.
1530 1530  ** 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
1531 1531  ** 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
... ... @@ -1532,7 +1532,7 @@
1532 1532  
1533 1533  **10.3.3.3 From SDMX DataAttributes to VTL Measures **
1534 1534  
1535 -*
1455 +*
1536 1536  ** 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.
1537 1537  
1538 1538  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.
... ... @@ -1551,7 +1551,7 @@
1551 1551  
1552 1552  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
1553 1553  
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 wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)
1474 +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 wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)
1555 1555  
1556 1556  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. 
1557 1557  
... ... @@ -1618,7 +1618,7 @@
1618 1618  
1619 1619   the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above
1620 1620  
1621 -*
1541 +*
1622 1622  ** 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)
1623 1623  ** the value of the j^^th^^ VTL measure becomes the value of the SDMX PrimaryMeasure of the j^^th^^ observation of the set
1624 1624  ** the values of the VTL Attributes become the values of the corresponding SDMX DataAttributes (in principle for all the observations of the set above)
... ... @@ -1668,15 +1668,15 @@
1668 1668  
1669 1669   The VtlMappingScheme is a container for zero or more VtlDataflowMapping (besides possible mappings to artefacts other than dataflows).
1670 1670  
1671 -=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
1591 +=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
1672 1672  
1673 1673  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
1674 1674  
1675 1675  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).
1676 1676  
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 wikiinternallink" %)^^~[26~]^^>>path:#_ftn26]](%%)
1597 +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" %)^^~[26~]^^>>path:#_ftn26]](%%)
1678 1678  
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 wikiinternallink" %)^^~[27~]^^>>path:#_ftn27]](%%)
1599 +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" %)^^~[27~]^^>>path:#_ftn27]](%%)
1680 1680  
1681 1681   Given a SDMX Dataflow and some predefined Dimensions of its
1682 1682  
... ... @@ -1688,14 +1688,14 @@
1688 1688  
1689 1689  In practice, this kind mapping is obtained like follows:
1690 1690  
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 wikiinternallink" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
1611 +* 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" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
1692 1692  * The VTL dataset is given a name using a special notation also called “ordered concatenation” and composed of the following parts: 
1693 1693  ** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated
1694 1694  
1695 -URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
1615 +URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
1696 1696  
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 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.
1617 +*
1618 +** 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" %)^^~[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.
1699 1699  
1700 1700  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.
1701 1701  
... ... @@ -1713,7 +1713,7 @@
1713 1713  
1714 1714  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.
1715 1715  
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 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.
1636 +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" %)^^~[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.
1717 1717  
1718 1718  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.
1719 1719  
... ... @@ -1723,7 +1723,7 @@
1723 1723  
1724 1724  //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.
1725 1725  
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 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 …). 
1646 +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" %)^^~[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 …). 
1727 1727  
1728 1728  In the example above, for all the datasets of the kind
1729 1729  
... ... @@ -1743,7 +1743,7 @@
1743 1743  
1744 1744  …   …   …
1745 1745  
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 wikiinternallink" %)^^~[33~]^^>>path:#_ftn33]]
1666 +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" %)^^~[33~]^^>>path:#_ftn33]]
1747 1747  
1748 1748  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.
1749 1749  
... ... @@ -1766,12 +1766,12 @@
1766 1766  
1767 1767  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:
1768 1768  
1769 -* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink 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 wikiinternallink" %)^^~[35~]^^>>path:#_ftn35]]
1689 +* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)
1690 +* 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" %)^^~[35~]^^>>path:#_ftn35]]
1771 1771  
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 wikiinternallink" %)^^~[36~]^^>>path:#_ftn36]](%%).
1692 +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" %)^^~[36~]^^>>path:#_ftn36]](%%).
1773 1773  
1774 -The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]
1694 +The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]
1775 1775  
1776 1776  ‘DF2(1.0)///INDICATORvalue//.//COUNTRYvalue//’  <-  expression
1777 1777  
... ... @@ -1838,9 +1838,9 @@
1838 1838  
1839 1839  …);
1840 1840  
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 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.
1761 +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" %)^^~[38~]^^>>path:#_ftn38]](%%), which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
1842 1842  
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 wikiinternallink" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
1763 +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" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
1844 1844  
1845 1845  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).
1846 1846  
... ... @@ -1889,7 +1889,7 @@
1889 1889  
1890 1890  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). 
1891 1891  
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 wikiinternallink" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="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.
1812 +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" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="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.
1893 1893  
1894 1894  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
1895 1895  
... ... @@ -2178,12 +2178,12 @@
2178 2178  “true” or “false”
2179 2179  )))
2180 2180  
2181 -**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
2182 2182  
2183 -In case a different default conversion is desired, it can be achieved through the
2184 2184  
2185 -CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model).
2103 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types**
2186 2186  
2105 +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).
2106 +
2187 2187  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.
2188 2188  
2189 2189  |(% colspan="2" %)**VTL special characters for the formatting masks**
... ... @@ -2234,7 +2234,7 @@
2234 2234  |N|fixed number of digits used in the preceding  textual representation of the month or the day
2235 2235  | |
2236 2236  
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 wikiinternallink" %)^^~[43~]^^>>path:#_ftn43]](%%).
2157 +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" %)^^~[43~]^^>>path:#_ftn43]](%%).
2238 2238  
2239 2239  === 10.4.5 Null Values ===
2240 2240  
... ... @@ -2266,12 +2266,18 @@
2266 2266  
2267 2267  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”.
2268 2268  
2269 -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:
2189 +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:
2270 2270  
2191 +[[image:1747854006117-843.png]]
2192 +
2271 2271  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.
2272 2272  
2273 2273  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:
2274 2274  
2197 +[[image:1747854039499-443.png]]
2198 +
2199 +[[image:1747854067769-691.png]]
2200 +
2275 2275  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.
2276 2276  
2277 2277  == 11.2 Solution ==
... ... @@ -2292,20 +2292,30 @@
2292 2292  
2293 2293  To understand how the **XmlAnyElement** attribute works we present the following two web methods:
2294 2294  
2295 -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.
2221 +[[image:1747854096778-844.png]]
2296 2296  
2297 -The difference between the two is that for the first method, **SubmitXml**, the
2223 +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.
2298 2298  
2299 -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.
2225 +[[image:1747854127303-270.png]]
2300 2300  
2227 +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.
2228 +
2229 +[[image:1747854163928-581.png]]
2230 +
2301 2301  Now we look at the message for the method that uses the **XmlAnyElement** attribute.
2302 2302  
2233 +[[image:1747854190641-364.png]]
2234 +
2235 +[[image:1747854236732-512.png]]
2236 +
2303 2303  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.
2304 2304  
2305 -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]]
2239 +For more information please consult: [[http:~~/~~/msdn.microsoft.com/en-us/library/aa480498.aspx>>http://msdn.microsoft.com/en-us/library/aa480498.aspx]]
2306 2306  
2307 2307  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.
2308 2308  
2243 +[[image:1747854286398-614.png]]
2244 +
2309 2309  Without a common WSDL still the solution doesn’t enforce interoperability. In order to
2310 2310  
2311 2311  “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.
... ... @@ -2318,16 +2318,27 @@
2318 2318  
2319 2319  In the context of the SDMX Web Service, applying the above solution translates into the following:
2320 2320  
2257 +[[image:1747854385465-132.png]]
2258 +
2321 2321  The SOAP request/response will then be as follows:
2322 2322  
2323 2323  **GenericData Request**
2324 2324  
2263 +[[image:1747854406014-782.png]]
2264 +
2325 2325  **GenericData Response**
2326 2326  
2267 +[[image:1747854424488-855.png]]
2268 +
2327 2327  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:
2328 2328  
2271 +[[image:1747854453895-524.png]]
2272 +
2273 +[[image:1747854476631-125.png]]
2274 +
2329 2329  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:
2330 2330  
2277 +[[image:1747854493363-776.png]]
2331 2331  
2332 2332  ----
2333 2333  
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