Changes for page SDMX 2.1 Standards. Section 6. Technical Notes
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... ... @@ -63,12 +63,18 @@ 63 63 64 64 The following section provides a brief overview of the differences between the various SDMX formats. 65 65 66 -Version 2.0 was characterised by 4 data messages, each with a distinct format: Generic, Compact, Cross-Sectional and Utility. Because of the design, data in some formats could not always be related to another format. In version 2.1, this issue has been addressed by merging some formats and eliminating others. As a result, in SDMX 2.1 there are just two types of data formats: //GenericData// and //StructureSpecificData// (i.e. specific to one Data Structure Definition).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 67 67 68 +SDMX 2.1 there are just two types of data formats: //GenericData// and 69 + 70 +//StructureSpecificData// (i.e. specific to one Data Structure Definition). 71 + 68 68 Both of these formats are now flexible enough to allow for data to be oriented in series with any dimension used to disambiguate the observations (as opposed to only time or a cross sectional measure in version 2.0). The formats have also been expanded to allow for ungrouped observations. 69 69 70 -To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages; //GenericTimeSeriesData// and //StructureSpecificTimeSeriesData//. It is important to note that these variations are built on the same root structure and can be processed in the same manner as the base format so that they do NOT introduce additional processing requirements.74 +To allow for applications which only understand time series data, variations of these formats have been introduced in the form of two data messages; 71 71 76 +//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. 77 + 72 72 === //Structure Definition// === 73 73 74 74 The SDMX-ML Structure Message supports the use of annotations to the structure, which is not supported by the SDMX-EDI syntax. ... ... @@ -77,8 +77,10 @@ 77 77 78 78 === //Validation// === 79 79 80 -SDMX-EDI – as is typical of EDIFACT syntax messages – leaves validation to dedicated applications (“validation” being the checking of syntax, data typing, and adherence of the data message to the structure as described in the structural definition.)86 +SDMX-EDI – as is typical of EDIFACT syntax messages – leaves validation to dedicated applications (“validation” being the checking of syntax, data typing, and adherence of the data message to the structure as described in the structural 81 81 88 +definition.) 89 + 82 82 The SDMX-ML Generic Data Message also leaves validation above the XML syntax level to the application. 83 83 84 84 The SDMX-ML DSD-specific messages will allow validation of XML syntax and datatyping to be performed with a generic XML parser, and enforce agreement between the structural definition and the data to a moderate degree with the same tool. ... ... @@ -89,13 +89,17 @@ 89 89 90 90 === //Character Encodings// === 91 91 92 -All SDMX-ML messages use the UTF-8 encoding, while SDMX-EDI uses the ISO 8879-1 character encoding. There is a greater capacity with UTF-8 to express some character sets (see the “APPENDIX: MAP OF ISO 8859-1 (UNOC) CHARACTER SET (LATIN 1 OR “WESTERN”) in the document “SYNTAX AND DOCUMENTATION VERSION 2.0”.) Many transformation tools are available which allow XML instances with UTF-8 encodings to be expressed as ISO 8879-1-encoded characters, and to transform UTF-8 into ISO 8879-1. Such tools should be used when transforming SDMX-ML messages into SDMX-EDI messages and vice-versa.100 +All SDMX-ML messages use the UTF-8 encoding, while SDMX-EDI uses the ISO 8879-1 character encoding. There is a greater capacity with UTF-8 to express some character sets (see the “APPENDIX: MAP OF ISO 8859-1 (UNOC) CHARACTER 93 93 102 +SET (LATIN 1 OR “WESTERN”) in the document “SYNTAX AND 103 + 104 +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. 105 + 94 94 === //Data Typing// === 95 95 96 96 The XML syntax and EDIFACT syntax have different data-typing mechanisms. The section below provides a set of conventions to be observed when support for messages in both syntaxes is required. For more information on the SDMX-ML representations of data, see below. 97 97 98 -==== 3.3.2 Data Types ==== 110 +==== 3.3.2 Data Types ==== 99 99 100 100 The XML syntax has a very different mechanism for data-typing than the EDIFACT syntax, and this difference may create some difficulties for applications which support both EDIFACT-based and XML-based SDMX data formats. This section provides a set of conventions for the expression in data in all formats, to allow for clean interoperability between them. 101 101 ... ... @@ -111,8 +111,7 @@ 111 111 1*. Maximum 70 characters. 112 112 1*. From ISO 8859-1 character set (including accented characters) 113 113 1. **Descriptions **are: 114 -1*. Maximum 350 characters; 115 -1*. From ISO 8859-1 character set. 126 +1*. Maximum 350 characters; From ISO 8859-1 character set. 116 116 1. **Code values** are: 117 117 1*. Maximum 18 characters; 118 118 1*. Any of A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore), / (solidus, slash), = (equal sign), - (hyphen); ... ... @@ -121,43 +121,37 @@ 121 121 122 122 A..Z (upper case alphabetic), 0..9 (numeric), _ (underscore) 123 123 124 -**5. Observation values** are: 135 +1. **Observation values** are: 136 +1*. Decimal numerics (signed only if they are negative); 137 +1*. The maximum number of significant figures is: 138 +1*. 15 for a positive number 139 +1*. 14 for a positive decimal or a negative integer 140 +1*. 13 for a negative decimal 141 +1*. Scientific notation may be used. 142 +1. **Uncoded statistical concept** text values are: 143 +1*. 144 +1**. Maximum 1050 characters; 145 +1**. From ISO 8859-1 character set. 146 +1. **Time series keys**: 125 125 126 -* Decimal numerics (signed only if they are negative); 127 -* The maximum number of significant figures is: 128 -* 15 for a positive number 129 -* 14 for a positive decimal or a negative integer 130 -* 13 for a negative decimal 131 -* Scientific notation may be used. 148 +In principle, the maximum permissible length of time series keys used in a data exchange does not need to be restricted. However, for working purposes, an effort is made to limit the maximum length to 35 characters; in this length, also (for SDMXEDI) one (separator) position is included between all successive dimension values; this means that the maximum length allowed for a pure series key (concatenation of dimension values) can be less than 35 characters. The separator character is a colon (“:”) by conventional usage. 132 132 133 -**6. Uncoded statistical concept** text values are: 134 - 135 -* Maximum 1050 characters; 136 -* From ISO 8859-1 character set. 137 - 138 -**7. Time series keys**: 139 - 140 -In principle, the maximum permissible length of time series keys used in a data exchange does not need to be restricted. However, for working purposes, an effort is made to limit the maximum length to 35 characters; in this length, also (for SDMXEDI) one (separator) position is included between all successive dimension values; this means that the maximum length allowed for a pure series key (concatenation of dimension values) can be less than 35 characters. The separator character is a colon (“:”) by conventional usage. 141 - 142 142 == 3.4 SDMX-ML and SDMX-EDI Best Practices == 143 143 144 -=== 3.4.1 Reporting and Dissemination Guidelines === 152 +=== 3.4.1 Reporting and Dissemination Guidelines === 145 145 146 - ====3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges====154 +**3.4.1.1 Central Institutions and Their Role in Statistical Data Exchanges **Central institutions are the organisations to which other partner institutions "report" statistics. These statistics are used by central institutions either to compile aggregates and/or they are put together and made available in a uniform manner (e.g. on-line or on a CD-ROM or through file transfers). Therefore, central institutions receive data from other institutions and, usually, they also "disseminate" data to individual and/or institutions for end-use. Within a country, a NSI or a national central bank (NCB) plays, of course, a central institution role as it collects data from other entities and it disseminates statistical information to end users. In SDMX the role of central institution is very important: every statistical message is based on underlying structural definitions (statistical concepts, code lists, DSDs) which have been devised by a particular agency, usually a central institution. Such an institution plays the role of the reference "structural definitions maintenance agency" for the corresponding messages which are exchanged. Of course, two institutions could exchange data using/referring to structural information devised by a third institution. 147 147 148 -Central institutions are the organisations to which other partner institutions "report" statistics. These statistics are used by central institutions either to compile aggregates and/or they are put together and made available in a uniform manner (e.g. on-line or on a CD-ROM or through file transfers). Therefore, central institutions receive data from other institutions and, usually, they also "disseminate" data to individual and/or institutions for end-use. Within a country, a NSI or a national central bank (NCB) plays, of course, a central institution role as it collects data from other entities and it disseminates statistical information to end users. In SDMX the role of central institution is very important: every statistical message is based on underlying structural definitions (statistical concepts, code lists, DSDs) which have been devised by a particular agency, usually a central institution. Such an institution plays the role of the reference "structural definitions maintenance agency" for the corresponding messages which are exchanged. Of course, two institutions could exchange data using/referring to structural information devised by a third institution. 149 - 150 150 Central institutions can play a double role: 151 151 152 152 * collecting and further disseminating statistics; 153 153 * devising structural definitions for use in data exchanges. 154 154 155 - ====3.4.1.2 Defining Data Structure Definitions (DSDs)====161 +**3.4.1.2 Defining Data Structure Definitions (DSDs)** 156 156 157 157 The following guidelines are suggested for building a DSD. However, it is expected that these guidelines will be considered by central institutions when devising new DSDs. 158 158 159 -(% class="wikigeneratedid" id="HDimensions2CAttributesandCodeLists" %) 160 -__Dimensions, Attributes and Code Lists__ 165 +=== Dimensions, Attributes and Code Lists === 161 161 162 162 **//Avoid dimensions that are not appropriate for all the series in the data structure definition.//** If some dimensions are not applicable (this is evident from the need to have a code in a code list which is marked as “not applicable”, “not relevant” or “total”) for some series then consider moving these series to a new data structure definition in which these dimensions are dropped from the key structure. This is a judgement call as it is sometimes difficult to achieve this without increasing considerably the number of DSDs. 163 163 ... ... @@ -187,8 +187,7 @@ 187 187 188 188 The same code list can be used for several statistical concepts, within a data structure definition or across DSDs. Note that SDMX has recognised that these classifications are often quite large and the usage of codes in any one DSD is only a small extract of the full code list. In this version of the standard it is possible to exchange and disseminate a **partial code list** which is extracted from the full code list and which supports the dimension values valid for a particular DSD. 189 189 190 -(% class="wikigeneratedid" id="HDataStructureDefinitionStructure" %) 191 -__Data Structure Definition Structure__ 195 +=== Data Structure Definition Structure === 192 192 193 193 The following items have to be specified by a structural definitions maintenance agency when defining a new data structure definition: 194 194 ... ... @@ -218,7 +218,7 @@ 218 218 * code list name 219 219 * code values and descriptions 220 220 221 -Definition of data flow definitions. Two (or more) partners performing data exchanges in a certain context need to agree on: 225 +Definition of data flow definitions. Two (or more) partners performing data exchanges in a certain context need to agree on: 222 222 223 223 * the list of data set identifiers they will be using; 224 224 * for each data flow: ... ... @@ -225,12 +225,10 @@ 225 225 * its content and description 226 226 * the relevant DSD that defines the structure of the data reported or disseminated according the the dataflow definition 227 227 228 - ====3.4.1.3 Exchanging Attributes====232 +**3.4.1.3 Exchanging Attributes** 229 229 230 - =====//3.4.1.3.1 Attributes on series, sibling and data set level //=====234 +**//3.4.1.3.1 Attributes on series, sibling and data set level //**//Static properties//. 231 231 232 -//Static properties//. 233 - 234 234 * Upon creation of a series the sender has to provide to the receiver values for all mandatory attributes. In case they are available, values for conditional attributes should also be provided. Whereas initially this information may be provided by means other than SDMX-ML or SDMX-EDI messages (e.g. paper, telephone) it is expected that partner institutions will be in a position to provide this information in SDMX-ML or SDMX-EDI format over time. 235 235 * A centre may agree with its data exchange partners special procedures for authorising the setting of attributes' initial values. 236 236 * Attribute values at a data set level are set and maintained exclusively by the centre administrating the exchanged data set. ... ... @@ -247,21 +247,21 @@ 247 247 * If the “observation status” changes and the observation remains unchanged, both components would have to be reported. 248 248 * For Data Structure Definitions having also the observation level attributes “observation confidentiality” and "observation pre-break" defined, this rule applies to these attribute as well: if an institution receives from another institution an observation with an observation status attribute only attached, this means that the associated observation confidentiality and prebreak observation attributes either never existed or from now they do not have a value for this observation. 249 249 250 -=== 3.4.2 Best Practices for Batch Data Exchange === 252 +==== 3.4.2 Best Practices for Batch Data Exchange ==== 251 251 252 - ====3.4.2.1 Introduction====254 +**3.4.2.1 Introduction** 253 253 254 254 Batch data exchange is the exchange and maintenance of entire databases between counterparties. It is an activity that often employs SDMX-EDI formats, and might also use the SDMX-ML DSD-specific data set. The following points apply equally to both formats. 255 255 256 - ====3.4.2.2 Positioning of the Dimension "Frequency"====258 +**3.4.2.2 Positioning of the Dimension "Frequency"** 257 257 258 258 The position of the “frequency” dimension is unambiguously identified in the data structure definition. Moreover, most central institutions devising structural definitions have decided to assign to this dimension the first position in the key structure. This facilitates the easy identification of this dimension, something that it is necessary to frequency's crucial role in several database systems and in attaching attributes at the “sibling” group level. 259 259 260 - ====3.4.2.3 Identification of Data Structure Definitions (DSDs)====262 +**3.4.2.3 Identification of Data Structure Definitions (DSDs)** 261 261 262 262 In order to facilitate the easy and immediate recognition of the structural definition maintenance agency that defined a data structure definition, most central institutions devising structural definitions use the first characters of the data structure definition identifiers to identify their institution: e.g. BIS_EER, EUROSTAT_BOP_01, ECB_BOP1, etc. 263 263 264 - ====3.4.2.4 Identification of the Data Flows====266 +**3.4.2.4 Identification of the Data Flows** 265 265 266 266 In order to facilitate the easy and immediate recognition of the institution administrating a data flow definitions, many central institutions prefer to use the first characters of the data flow definition identifiers to identify their institution: e.g. BIS_EER, ECB_BOP1, ECB_BOP1, etc. Note that in GESMES/TS the Data Set plays the role of the data flow definition (see //DataSet //in the SDMX-IM//)//. 267 267 ... ... @@ -269,7 +269,7 @@ 269 269 270 270 Note that the role of the Data Flow (called //DataflowDefintion// in the model) and Data Set is very specific in the model, and the terminology used may not be the same as used in all organisations, and specifically the term Data Set is used differently in SDMX than in GESMES/TS. Essentially the GESMES/TS term "Data Set" is, in SDMX, the "Dataflow Definition" whist the term "Data Set" in SDMX is used to describe the "container" for an instance of the data. 271 271 272 - ====3.4.2.5 Special Issues====274 +**3.4.2.5 Special Issues** 273 273 274 274 ===== 3.4.2.5.1 "Frequency" related issues ===== 275 275 ... ... @@ -280,6 +280,7 @@ 280 280 281 281 **//Tick data.//** The issue of data collected at irregular intervals at a higher than daily frequency (e.g. tick-by-tick data) is not discussed here either. However, for data exchange purposes, such series can already be exchanged in the SDMX-EDI format by using the option to send observations with the associated time stamp. 282 282 285 + 283 283 = 4 General Notes for Implementers = 284 284 285 285 This section discusses a number of topics other than the exchange of data sets in SDMX-ML and SDMX-EDI. Supported only in SDMX-ML, these topics include the use of the reference metadata mechanism in SDMX, the use of Structure Sets and Reporting Taxonomies, the use of Processes, a discussion of time and data-typing, and some of the conventional mechanisms within the SDMX-ML Structure message regarding versioning and external referencing. ... ... @@ -290,31 +290,39 @@ 290 290 291 291 There are several different representations in SDMX-ML, taken from XML Schemas and common programming languages. The table below describes the various representations which are found in SDMX-ML, and their equivalents. 292 292 293 -(% style="width:912.294px" %) 294 -|(% style="width:172px" %)**SDMX-ML Data Type**|(% style="width:204px" %)**XML Schema Data Type**|(% style="width:189px" %)**.NET Framework Type**|(% style="width:342px" %)((( 295 -**Java Data Type ** 296 +|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|((( 297 +**Java Data Type** 298 + 299 +**~ ** 296 296 ))) 297 -|(% style="width:172px" %)String|(% style="width:204px" %)xsd:string|(% style="width:189px" %)System.String|(% style="width:342px" %)java.lang.String 298 -|(% style="width:172px" %)Big Integer|(% style="width:204px" %)xsd:integer|(% style="width:189px" %)System.Decimal|(% style="width:342px" %)java.math.BigInteg er 299 -|(% style="width:172px" %)Integer|(% style="width:204px" %)xsd:int|(% style="width:189px" %)System.Int32|(% style="width:342px" %)int 300 -|(% style="width:172px" %)Long|(% style="width:204px" %)xsd.long|(% style="width:189px" %)System.Int64|(% style="width:342px" %)long 301 -|(% style="width:172px" %)Short|(% style="width:204px" %)xsd:short|(% style="width:189px" %)System.Int16|(% style="width:342px" %)short 302 -|(% style="width:172px" %)Decimal|(% style="width:204px" %)xsd:decimal|(% style="width:189px" %)System.Decimal|(% style="width:342px" %)java.math.BigDecim al 303 -|(% style="width:172px" %)Float|(% style="width:204px" %)xsd:float|(% style="width:189px" %)System.Single|(% style="width:342px" %)float 304 -|(% style="width:172px" %)Double|(% style="width:204px" %)xsd:double|(% style="width:189px" %)System.Double|(% style="width:342px" %)double 305 -|(% style="width:172px" %)Boolean|(% style="width:204px" %)xsd:boolean|(% style="width:189px" %)System.Boolean|(% style="width:342px" %)boolean 306 -|(% style="width:172px" %)URI|(% style="width:204px" %)xsd:anyURI|(% style="width:189px" %)System.Uri|(% style="width:342px" %)Java.net.URI or java.lang.String 307 -|(% style="width:172px" %)DateTime|(% style="width:204px" %)xsd:dateTime|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar 308 -|(% style="width:172px" %)Time|(% style="width:204px" %)xsd:time|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar 309 -|(% style="width:172px" %)GregorianYear|(% style="width:204px" %)xsd:gYear|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar 310 -|(% style="width:172px" %)GregorianMonth|(% style="width:204px" %)xsd:gYearMonth|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar 311 -|(% style="width:172px" %)GregorianDay|(% style="width:204px" %)xsd:date|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar 312 -|(% style="width:172px" %)((( 313 -Day, MonthDay, Month 314 -)))|(% style="width:204px" %)xsd:g*|(% style="width:189px" %)System.DateTime|(% style="width:342px" %)javax.xml.datatype .XMLGregorianCalen dar 315 -|(% style="width:172px" %)Duration|(% style="width:204px" %)xsd:duration |(% style="width:189px" %)System.TimeSpa|(% style="width:342px" %)javax.xml.datatype 316 -|(% style="width:172px" %) |(% style="width:204px" %) |(% style="width:189px" %)n|(% style="width:342px" %).Duration 301 +|String|xsd:string|System.String|java.lang.String 302 +|Big Integer|xsd:integer|System.Decimal|java.math.BigInteg er 303 +|Integer|xsd:int|System.Int32|int 304 +|Long|xsd.long|System.Int64|long 305 +|Short|xsd:short|System.Int16|short 306 +|Decimal|xsd:decimal|System.Decimal|java.math.BigDecim al 307 +|Float|xsd:float|System.Single|float 308 +|Double|xsd:double|System.Double|double 309 +|Boolean|xsd:boolean|System.Boolean|boolean 310 +|URI|xsd:anyURI|System.Uri|Java.net.URI or java.lang.String 311 +|DateTime|xsd:dateTime|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar 312 +|Time|xsd:time|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar 313 +|GregorianYear|xsd:gYear|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar 314 +|GregorianMont h|xsd:gYearMont h|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar 315 +|GregorianDay|xsd:date|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar 316 +|((( 317 +Day, 317 317 319 +MonthDay, Month 320 +)))|xsd:g*|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar 321 +|Duration|xsd:duration |System.TimeSpa|javax.xml.datatype 322 +|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|((( 323 +**Java Data Type** 324 + 325 +**~ ** 326 +))) 327 +| | |n|.Duration 328 + 318 318 There are also a number of SDMX-ML data types which do not have these direct correspondences, often because they are composite representations or restrictions of a broader data type. For most of these, there are simple types which can be referenced from the SDMX schemas, for others a derived simple type will be necessary: 319 319 320 320 * AlphaNumeric (common:AlphaNumericType, string which only allows A-z and 0-9) ... ... @@ -340,8 +340,10 @@ 340 340 * KeyValues (common:DataKeyType) 341 341 * IdentifiableReference (types for each identifiable object) 342 342 * DataSetReference (common:DataSetReferenceType) 343 -* AttachmentConstraintReference (common:AttachmentConstraintReferenceType)354 +* AttachmentConstraintReference 344 344 356 +(common:AttachmentConstraintReferenceType) 357 + 345 345 Data types also have a set of facets: 346 346 347 347 * isSequence = true | false (indicates a sequentially increasing value) ... ... @@ -363,7 +363,7 @@ 363 363 364 364 == 4.2 Time and Time Format == 365 365 366 -=== 4.2.1 Introduction === 379 +==== 4.2.1 Introduction ==== 367 367 368 368 First, it is important to recognize that most observation times are a period. SDMX specifies precisely how Time is handled. 369 369 ... ... @@ -412,7 +412,7 @@ 412 412 413 413 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. 414 414 415 -Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]428 +Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]] 416 416 417 417 ==== 4.2.6 Standard Reporting Period ==== 418 418 ... ... @@ -480,7 +480,7 @@ 480 480 481 481 Representation: common:ReportingWeekType (YYYY-Www, e.g. 2000-W53) 482 482 483 -Notes: There are either 52 or 53 weeks in a reporting year. This is based on the ISO 8601 definition of a week (Monday - Saturday), where the first week of a reporting year is defined as the week with the first Thursday on or after the reporting year start day.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[2~]^^>>path:#_ftn2]](%%) The reporting week is always represented as two digits, therefore 1-9 are 0 padded (e.g. 01). This allows the values to be sorted chronologically using textual sorting methods.496 +Notes: There are either 52 or 53 weeks in a reporting year. This is based on the ISO 8601 definition of a week (Monday - Saturday), where the first week of a reporting year is defined as the week with the first Thursday on or after the reporting year start day.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[2~]^^>>path:#_ftn2]](%%) The reporting week is always represented as two digits, therefore 1-9 are 0 padded (e.g. 01). This allows the values to be sorted chronologically using textual sorting methods. 484 484 485 485 **Reporting Day**: 486 486 ... ... @@ -508,16 +508,16 @@ 508 508 509 509 **a) If the [PERIOD_INDICATOR] is W:** 510 510 511 -1. 512 -11. 513 -111. 524 +1. 525 +11. 526 +111. 514 514 1111. **If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:** 515 515 516 516 Add^^3^^ (P3D, P2D, or P1D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE]. 517 517 518 -1. 519 -11. 520 -111. 531 +1. 532 +11. 533 +111. 521 521 1111. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:** 522 522 523 523 Add^^3^^ (P0D, -P1D, -P2D, or -P3D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE]. ... ... @@ -527,7 +527,7 @@ 527 527 The [REPORTING_YEAR_START_DATE] is the [REPORTING_YEAR_BASE]. 528 528 529 529 1. **Determine [PERIOD_DURATION]:** 530 -11. 543 +11. 531 531 111. If the [PERIOD_INDICATOR] is A, the [PERIOD_DURATION] is P1Y. 532 532 111. If the [PERIOD_INDICATOR] is S, the [PERIOD_DURATION] is P6M. 533 533 111. If the [PERIOD_INDICATOR] is T, the [PERIOD_DURATION] is P4M. ... ... @@ -537,7 +537,7 @@ 537 537 111. If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D. 538 538 1. **Determine [PERIOD_START]:** 539 539 540 -Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].553 +Subtract one from the [PERIOD_VALUE] and multiply this by the [PERIOD_DURATION]. Add[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START]. 541 541 542 542 1. **Determine the [PERIOD_END]:** 543 543 ... ... @@ -1233,7 +1233,7 @@ 1233 1233 1234 1234 == 10.1 Introduction == 1235 1235 1236 -The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:1249 +The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the: 1237 1237 1238 1238 * definition of validation and transformation algorithms, in order to specify how to calculate new data from existing ones; 1239 1239 * 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); ... ... @@ -1257,7 +1257,7 @@ 1257 1257 1258 1258 In any case, the aliases used in the VTL transformations have to be mapped to the 1259 1259 1260 -SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL transformations, rulesets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%) to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping.1273 +SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL transformations, rulesets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%) to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 1261 1261 1262 1262 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. 1263 1263 ... ... @@ -1267,7 +1267,7 @@ 1267 1267 1268 1268 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. 1269 1269 1270 -The SDMX URN[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[7~]^^>>path:#_ftn7]](%%) is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:^^ ^^1283 +The SDMX URN[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[7~]^^>>path:#_ftn7]](%%) is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:^^ ^^ 1271 1271 1272 1272 * SDMXprefix 1273 1273 * SDMX-IM-package-name ... ... @@ -1275,7 +1275,7 @@ 1275 1275 * agency-id 1276 1276 * maintainedobject-id 1277 1277 * maintainedobject-version 1278 -* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]1291 +* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]] 1279 1279 * object-id 1280 1280 1281 1281 The generic structure of the URN is the following: ... ... @@ -1294,7 +1294,7 @@ 1294 1294 1295 1295 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). 1296 1296 1297 -The **maintainedobject-id** is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:1310 +The **maintainedobject-id** is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact: 1298 1298 1299 1299 * if the artefact is a ,,Dataflow,,, which is a maintainable class, the maintainedobject-id is the Dataflow name (dataflow-id); 1300 1300 * 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; ... ... @@ -1314,7 +1314,7 @@ 1314 1314 1315 1315 * if the artefact is a ,,Concept ,,(the object-id is the name of the ,,Concept,,) 1316 1316 1317 -For example, by using the URN, the VTL transformation that sums two SDMX dataflows DF1 and DF2 and assigns the result to a third persistent dataflow DFR, assuming that DF1, DF2 and DFR are the maintainedobject-id of the three dataflows, that their version is 1.0 and their Agency is AG, would be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[10~]^^>>path:#_ftn10]](%%):1330 +For example, by using the URN, the VTL transformation that sums two SDMX dataflows DF1 and DF2 and assigns the result to a third persistent dataflow DFR, assuming that DF1, DF2 and DFR are the maintainedobject-id of the three dataflows, that their version is 1.0 and their Agency is AG, would be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[10~]^^>>path:#_ftn10]](%%): 1318 1318 1319 1319 ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’ <- 1320 1320 ... ... @@ -1332,14 +1332,14 @@ 1332 1332 * 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: 1333 1333 ** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute, 1334 1334 ** “conceptscheme” for the classes Concept and ConceptScheme o “codelist” for the class Codelist. 1335 -* The **class-name** can be omitted as it can be deduced from the VTL invocation. In particular, starting from the VTL class of the invoked artefact (e.g. dataset, component, identifier, measure, attribute, variable, valuedomain), which is known given the syntax of the invoking VTL operator[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[11~]^^>>path:#_ftn11]](%%), the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section “Mapping between VTL and SDMX” hereinafter)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink" %)^^~[12~]^^>>path:#_ftn12]](%%).1336 -* If the **agency-id** is not specified, it is assumed by default equal to the agency-id of the TransformationScheme, UserDefinedOperatorScheme or RulesetScheme from which the artefact is invoked. For example, the agency-id can be omitted if it is the same as the invoking T,,ransformationScheme,, and cannot be omitted if the artefact comes from another agency.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[13~]^^>>path:#_ftn13]](%%) Take also into account that, according to the VTL consistency rules, the agency of the result of a ,,Transformation,, must be the same as its ,,TransformationScheme,,, therefore the agency-id can be omitted for all the results (left part of ,,Transformation,, statements).1348 +* The **class-name** can be omitted as it can be deduced from the VTL invocation. In particular, starting from the VTL class of the invoked artefact (e.g. dataset, component, identifier, measure, attribute, variable, valuedomain), which is known given the syntax of the invoking VTL operator[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[11~]^^>>path:#_ftn11]](%%), the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section “Mapping between VTL and SDMX” hereinafter)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[12~]^^>>path:#_ftn12]](%%). 1349 +* If the **agency-id** is not specified, it is assumed by default equal to the agency-id of the TransformationScheme, UserDefinedOperatorScheme or RulesetScheme from which the artefact is invoked. For example, the agency-id can be omitted if it is the same as the invoking T,,ransformationScheme,, and cannot be omitted if the artefact comes from another agency.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[13~]^^>>path:#_ftn13]](%%) Take also into account that, according to the VTL consistency rules, the agency of the result of a ,,Transformation,, must be the same as its ,,TransformationScheme,,, therefore the agency-id can be omitted for all the results (left part of ,,Transformation,, statements). 1337 1337 * 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; 1338 1338 ** 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 1339 1339 1340 1340 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; 1341 1341 1342 -* 1355 +* 1343 1343 ** if the referenced artefact is a ,,ConceptScheme, ,,which is a,, ,,maintainable class,,, ,,the maintained object is the ,,conceptScheme-id,, and obviously cannot be omitted; 1344 1344 ** if the referenced artefact is a ,,Codelist, ,,which is a maintainable class, the maintainedobject-id is the ,,codelist-id,, and obviously cannot be omitted. 1345 1345 * 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.,, ,, ... ... @@ -1360,11 +1360,11 @@ 1360 1360 1361 1361 DFR := DF1 + DF2 1362 1362 1363 -The references to the ,,Codelists,, can be simplified similarly. For example, given the non-abbreviated reference to the ,,Codelist,, AG:CL_FREQ(1.0), which is[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[14~]^^>>path:#_ftn14]](%%):1376 +The references to the ,,Codelists,, can be simplified similarly. For example, given the non-abbreviated reference to the ,,Codelist,, AG:CL_FREQ(1.0), which is[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[14~]^^>>path:#_ftn14]](%%): 1364 1364 1365 1365 ‘urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0)’ 1366 1366 1367 -if the ,,Codelist,, is referenced from a ruleset scheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[15~]^^>>path:#_ftn15]](%%):1380 +if the ,,Codelist,, is referenced from a ruleset scheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[15~]^^>>path:#_ftn15]](%%): 1368 1368 1369 1369 CL_FREQ 1370 1370 ... ... @@ -1374,7 +1374,7 @@ 1374 1374 1375 1375 SECTOR 1376 1376 1377 -For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[16~]^^>>path:#_ftn16]](%%):1390 +For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[16~]^^>>path:#_ftn16]](%%): 1378 1378 1379 1379 ‘DFR(1.0)’ := ‘DF1(1.0)’ [rename SECTOR to SEC] 1380 1380 ... ... @@ -1408,9 +1408,9 @@ 1408 1408 1409 1409 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. 1410 1410 1411 -In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist or to a SDMX ConceptScheme (for SDMX measure dimensions), while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[17~]^^>>path:#_ftn17]](%%).1424 +In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist or to a SDMX ConceptScheme (for SDMX measure dimensions), while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[17~]^^>>path:#_ftn17]](%%). 1412 1412 1413 -In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called “valueDomain” and “variable” for the Datapoint Rulesets and “ruleValueDomain”, “ruleVariable”, “condValueDomain” “condVariable” for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific ruleset definition statement and cannot be mapped to SDMX.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[18~]^^>>path:#_ftn18]](%%)1426 +In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called “valueDomain” and “variable” for the Datapoint Rulesets and “ruleValueDomain”, “ruleVariable”, “condValueDomain” “condVariable” for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific ruleset definition statement and cannot be mapped to SDMX.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[18~]^^>>path:#_ftn18]](%%) 1414 1414 1415 1415 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. 1416 1416 ... ... @@ -1424,15 +1424,15 @@ 1424 1424 1425 1425 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. 1426 1426 1427 -In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[19~]^^>>path:#_ftn19]](%%).1440 +In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place. The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[19~]^^>>path:#_ftn19]](%%). 1428 1428 1429 1429 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). 1430 1430 1431 1431 === 10.3.2 General mapping of VTL and SDMX data structures === 1432 1432 1433 -This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%).1446 +This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%). 1434 1434 1435 -The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[22~]^^>>path:#_ftn22]](%%)1448 +The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[22~]^^>>path:#_ftn22]](%%) 1436 1436 1437 1437 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. 1438 1438 ... ... @@ -1442,7 +1442,7 @@ 1442 1442 1443 1443 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. 1444 1444 1445 -However, a VTL Data Structure can have any number of Identifiers, Measures and Attributes, while a SDMX 2.1 DataStructureDefinition can have any number of Dimensions and DataAttributes but just one PrimaryMeasure[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[23~]^^>>path:#_ftn23]](%%). This is due to a difference between SDMX 2.1 and VTL in the possible representation methods of the data that contain more measures.1458 +However, a VTL Data Structure can have any number of Identifiers, Measures and Attributes, while a SDMX 2.1 DataStructureDefinition can have any number of Dimensions and DataAttributes but just one PrimaryMeasure[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[23~]^^>>path:#_ftn23]](%%). This is due to a difference between SDMX 2.1 and VTL in the possible representation methods of the data that contain more measures. 1446 1446 1447 1447 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. 1448 1448 ... ... @@ -1506,7 +1506,7 @@ 1506 1506 1507 1507 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; 1508 1508 1509 -* 1522 +* 1510 1510 ** 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. 1511 1511 ** 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 1512 1512 ** 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 ... ... @@ -1513,7 +1513,7 @@ 1513 1513 1514 1514 **10.3.3.3 From SDMX DataAttributes to VTL Measures ** 1515 1515 1516 -* 1529 +* 1517 1517 ** 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. 1518 1518 1519 1519 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. ... ... @@ -1532,7 +1532,7 @@ 1532 1532 1533 1533 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 1534 1534 1535 -PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)1548 +PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%) 1536 1536 1537 1537 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. 1538 1538 ... ... @@ -1599,7 +1599,7 @@ 1599 1599 1600 1600 the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above 1601 1601 1602 -* 1615 +* 1603 1603 ** 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) 1604 1604 ** the value of the j^^th^^ VTL measure becomes the value of the SDMX PrimaryMeasure of the j^^th^^ observation of the set 1605 1605 ** the values of the VTL Attributes become the values of the corresponding SDMX DataAttributes (in principle for all the observations of the set above) ... ... @@ -1649,15 +1649,15 @@ 1649 1649 1650 1650 The VtlMappingScheme is a container for zero or more VtlDataflowMapping (besides possible mappings to artefacts other than dataflows). 1651 1651 1652 -=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===1665 +=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) === 1653 1653 1654 1654 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 1655 1655 1656 1656 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). 1657 1657 1658 -As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[26~]^^>>path:#_ftn26]](%%)1671 +As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[26~]^^>>path:#_ftn26]](%%) 1659 1659 1660 -Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL data sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[27~]^^>>path:#_ftn27]](%%)1673 +Therefore, in order to make the coding of VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL data sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[27~]^^>>path:#_ftn27]](%%) 1661 1661 1662 1662 Given a SDMX Dataflow and some predefined Dimensions of its 1663 1663 ... ... @@ -1669,14 +1669,14 @@ 1669 1669 1670 1670 In practice, this kind mapping is obtained like follows: 1671 1671 1672 -* For a given SDMX dataflow, the user (VTL definer) declares the dimension components on which the mapping will be based, in a given order.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.1685 +* For a given SDMX dataflow, the user (VTL definer) declares the dimension components on which the mapping will be based, in a given order.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY. 1673 1673 * The VTL dataset is given a name using a special notation also called “ordered concatenation” and composed of the following parts: 1674 1674 ** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated 1675 1675 1676 -URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]1689 +URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]] 1677 1677 1678 -* 1679 -** The reference to a specific part of the SDMX dataflow above, expressed as the concatenation of the values that the SDMX dimensions declared above must have, separated by dots (“.”) and written in the order in which these dimensions are defined[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[30~]^^>>path:#_ftn30]](%%) . For example POPULATION.USA would mean that such a VTL dataset is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.1691 +* 1692 +** The reference to a specific part of the SDMX dataflow above, expressed as the concatenation of the values that the SDMX dimensions declared above must have, separated by dots (“.”) and written in the order in which these dimensions are defined[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[30~]^^>>path:#_ftn30]](%%) . For example POPULATION.USA would mean that such a VTL dataset is mapped to the SDMX observations for which the dimension //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA. 1680 1680 1681 1681 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. 1682 1682 ... ... @@ -1694,7 +1694,7 @@ 1694 1694 1695 1695 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. 1696 1696 1697 -As already said, the mapping from SDMX to VTL happens when the VTL datasets are operand of VTL transformations, instead the mapping from VTL to SDMX happens when the VTL datasets are result of VTL transformations[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[31~]^^>>path:#_ftn31]](%%) and need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively.1710 +As already said, the mapping from SDMX to VTL happens when the VTL datasets are operand of VTL transformations, instead the mapping from VTL to SDMX happens when the VTL datasets are result of VTL transformations[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[31~]^^>>path:#_ftn31]](%%) and need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively. 1698 1698 1699 1699 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. 1700 1700 ... ... @@ -1704,7 +1704,7 @@ 1704 1704 1705 1705 //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. 1706 1706 1707 -In order to obtain the data structure of these VTL datasets from the SDMX one, it is assumed that the SDMX dimensions on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL datasets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[32~]^^>>path:#_ftn32]](%%). After that, the mapping method from SDMX to VTL specified for the dataflow DF1(1.0) is applied (i.e. basic, pivot …).1720 +In order to obtain the data structure of these VTL datasets from the SDMX one, it is assumed that the SDMX dimensions on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL datasets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[32~]^^>>path:#_ftn32]](%%). After that, the mapping method from SDMX to VTL specified for the dataflow DF1(1.0) is applied (i.e. basic, pivot …). 1708 1708 1709 1709 In the example above, for all the datasets of the kind 1710 1710 ... ... @@ -1724,7 +1724,7 @@ 1724 1724 1725 1725 … … … 1726 1726 1727 -In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX dataflow to different VTL datasets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a dataflow. [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[33~]^^>>path:#_ftn33]]1740 +In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX dataflow to different VTL datasets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a dataflow. [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[33~]^^>>path:#_ftn33]] 1728 1728 1729 1729 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. 1730 1730 ... ... @@ -1747,12 +1747,12 @@ 1747 1747 1748 1748 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: 1749 1749 1750 -* each part is calculated as a VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)1751 -* the data structure of all these VTL datasets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[35~]^^>>path:#_ftn35]]1763 +* each part is calculated as a VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%) 1764 +* the data structure of all these VTL datasets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[35~]^^>>path:#_ftn35]] 1752 1752 1753 -Under these hypothesis, such derived VTL datasets can be mapped to DF2(1.0) by declaring the Dimensions INDICATOR and COUNTRY as mapping dimensions[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[36~]^^>>path:#_ftn36]](%%).1766 +Under these hypothesis, such derived VTL datasets can be mapped to DF2(1.0) by declaring the Dimensions INDICATOR and COUNTRY as mapping dimensions[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[36~]^^>>path:#_ftn36]](%%). 1754 1754 1755 -The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]1768 +The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]] 1756 1756 1757 1757 ‘DF2(1.0)///INDICATORvalue//.//COUNTRYvalue//’ <- expression 1758 1758 ... ... @@ -1819,9 +1819,9 @@ 1819 1819 1820 1820 …); 1821 1821 1822 -In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent data sets are united and give the final result DF2(1.0)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[38~]^^>>path:#_ftn38]](%%), which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.1835 +In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent data sets are united and give the final result DF2(1.0)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[38~]^^>>path:#_ftn38]](%%), which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY. 1823 1823 1824 -Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]1837 +Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]] 1825 1825 1826 1826 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). 1827 1827 ... ... @@ -1870,7 +1870,7 @@ 1870 1870 1871 1871 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). 1872 1872 1873 -As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallink" %)^^~[42~]^^>>path:#_ftn42]](%%) This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.1886 +As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[42~]^^>>path:#_ftn42]](%%) This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has. 1874 1874 1875 1875 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 1876 1876 ... ... @@ -2215,7 +2215,7 @@ 2215 2215 |N|fixed number of digits used in the preceding textual representation of the month or the day 2216 2216 | | 2217 2217 2218 -The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[43~]^^>>path:#_ftn43]](%%).2231 +The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[43~]^^>>path:#_ftn43]](%%). 2219 2219 2220 2220 === 10.4.5 Null Values === 2221 2221