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... ... @@ -143,18 +143,21 @@
143 143  
144 144  === 3.4.1 Reporting and Dissemination Guidelines ===
145 145  
146 -**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 ====
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 +
148 148  Central institutions can play a double role:
149 149  
150 150  * collecting and further disseminating statistics;
151 151  * devising structural definitions for use in data exchanges.
152 152  
153 -**3.4.1.2 Defining Data Structure Definitions (DSDs)**
155 +==== 3.4.1.2 Defining Data Structure Definitions (DSDs) ====
154 154  
155 155  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.
156 156  
157 -=== Dimensions, Attributes and Code Lists ===
159 +(% class="wikigeneratedid" id="HDimensions2CAttributesandCodeLists" %)
160 +__Dimensions, Attributes and Code Lists__
158 158  
159 159  **//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.
160 160  
... ... @@ -184,7 +184,8 @@
184 184  
185 185  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.
186 186  
187 -=== Data Structure Definition Structure ===
190 +(% class="wikigeneratedid" id="HDataStructureDefinitionStructure" %)
191 +__Data Structure Definition Structure__
188 188  
189 189  The following items have to be specified by a structural definitions maintenance agency when defining a new data structure definition:
190 190  
... ... @@ -214,7 +214,7 @@
214 214  * code list name
215 215  * code values and descriptions
216 216  
217 -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:
218 218  
219 219  * the list of data set identifiers they will be using;
220 220  * for each data flow:
... ... @@ -243,21 +243,21 @@
243 243  * If the “observation status” changes and the observation remains unchanged, both components would have to be reported.
244 244  * 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.
245 245  
246 -==== 3.4.2 Best Practices for Batch Data Exchange ====
250 +=== 3.4.2 Best Practices for Batch Data Exchange ===
247 247  
248 -**3.4.2.1 Introduction**
252 +==== 3.4.2.1 Introduction ====
249 249  
250 250  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.
251 251  
252 -**3.4.2.2 Positioning of the Dimension "Frequency"**
256 +==== 3.4.2.2 Positioning of the Dimension "Frequency" ====
253 253  
254 254  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.
255 255  
256 -**3.4.2.3 Identification of Data Structure Definitions (DSDs)**
260 +==== 3.4.2.3 Identification of Data Structure Definitions (DSDs) ====
257 257  
258 258  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.
259 259  
260 -**3.4.2.4 Identification of the Data Flows**
264 +==== 3.4.2.4 Identification of the Data Flows ====
261 261  
262 262  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//)//.
263 263  
... ... @@ -265,7 +265,7 @@
265 265  
266 266  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.
267 267  
268 -**3.4.2.5 Special Issues**
272 +==== 3.4.2.5 Special Issues ====
269 269  
270 270  ===== 3.4.2.5.1 "Frequency" related issues =====
271 271  
... ... @@ -276,7 +276,6 @@
276 276  
277 277  **//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.
278 278  
279 -
280 280  = 4 General Notes for Implementers =
281 281  
282 282  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.
... ... @@ -287,39 +287,31 @@
287 287  
288 288  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.
289 289  
290 -|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|(((
291 -**Java Data Type**
292 -
293 -**~ **
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 **
294 294  )))
295 -|String|xsd:string|System.String|java.lang.String
296 -|Big Integer|xsd:integer|System.Decimal|java.math.BigInteg er
297 -|Integer|xsd:int|System.Int32|int
298 -|Long|xsd.long|System.Int64|long
299 -|Short|xsd:short|System.Int16|short
300 -|Decimal|xsd:decimal|System.Decimal|java.math.BigDecim al
301 -|Float|xsd:float|System.Single|float
302 -|Double|xsd:double|System.Double|double
303 -|Boolean|xsd:boolean|System.Boolean|boolean
304 -|URI|xsd:anyURI|System.Uri|Java.net.URI or java.lang.String
305 -|DateTime|xsd:dateTime|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
306 -|Time|xsd:time|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
307 -|GregorianYear|xsd:gYear|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
308 -|GregorianMont h|xsd:gYearMont h|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
309 -|GregorianDay|xsd:date|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
310 -|(((
311 -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
312 312  
313 -MonthDay, Month
314 -)))|xsd:g*|System.DateTim e|javax.xml.datatype .XMLGregorianCalen dar
315 -|Duration|xsd:duration |System.TimeSpa|javax.xml.datatype
316 -|**SDMX-ML Data Type**|**XML Schema Data Type**|**.NET Framework Type**|(((
317 -**Java Data Type**
318 -
319 -**~ **
320 -)))
321 -| | |n|.Duration
322 -
323 323  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:
324 324  
325 325  * AlphaNumeric (common:AlphaNumericType, string which only allows A-z and 0-9)
... ... @@ -345,10 +345,8 @@
345 345  * KeyValues (common:DataKeyType)
346 346  * IdentifiableReference (types for each identifiable object)
347 347  * DataSetReference (common:DataSetReferenceType)
348 -* AttachmentConstraintReference
343 +* AttachmentConstraintReference (common:AttachmentConstraintReferenceType)
349 349  
350 -(common:AttachmentConstraintReferenceType)
351 -
352 352  Data types also have a set of facets:
353 353  
354 354  * isSequence = true | false (indicates a sequentially increasing value)
... ... @@ -370,7 +370,7 @@
370 370  
371 371  == 4.2 Time and Time Format ==
372 372  
373 -==== 4.2.1 Introduction ====
366 +=== 4.2.1 Introduction ===
374 374  
375 375  First, it is important to recognize that most observation times are a period. SDMX specifies precisely how Time is handled.
376 376  
... ... @@ -378,50 +378,47 @@
378 378  
379 379  The hierarchy of time formats is as follows (**bold** indicates a category which is made up of multiple formats, //italic// indicates a distinct format):
380 380  
381 -* **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//
382 382  
383 - § **Basic Time Period**
384 -
385 -* **Gregorian Time Period**
386 -* //Date Time//
387 -
388 -§ **Reporting Time Period **o //Time Range//
389 -
390 390  The details of these time period categories and of the distinct formats which make them up are detailed in the sections to follow.
391 391  
392 -==== 4.2.2 Observational Time Period ====
384 +=== 4.2.2 Observational Time Period ===
393 393  
394 394  This is the superset of all time representations in SDMX. This allows for time to be expressed as any of the allowable formats.
395 395  
396 -==== 4.2.3 Standard Time Period ====
388 +=== 4.2.3 Standard Time Period ===
397 397  
398 398  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).
399 399  
400 -==== 4.2.4 Gregorian Time Period ====
392 +=== 4.2.4 Gregorian Time Period ===
401 401  
402 402  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:
403 403  
404 -**Gregorian Year:**
405 -
396 +**Gregorian Year:**
406 406  Representation: xs:gYear (YYYY)
398 +Period: the start of January 1 to the end of December 31
407 407  
408 -Period: the start of January 1 to the end of December 31 **Gregorian Year Month**:
409 -
400 +**Gregorian Year Month**:
410 410  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
411 411  
412 -Period: the start of the first day of the month to end of the last day of the month **Gregorian Day**:
413 -
404 +**Gregorian Day**:
414 414  Representation: xs:date (YYYY-MM-DD)
415 -
416 416  Period: the start of the day (00:00:00) to the end of the day (23:59:59)
417 417  
418 -==== 4.2.5 Date Time ====
408 +=== 4.2.5 Date Time ===
419 419  
420 420  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.
421 421  
422 -Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
412 +Representation: xs:dateTime (YYYY-MM-DDThh:mm:ss)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[1~]^^>>path:#_ftn1]]
423 423  
424 -==== 4.2.6 Standard Reporting Period ====
414 +=== 4.2.6 Standard Reporting Period ===
425 425  
426 426  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:
427 427  
... ... @@ -428,75 +428,52 @@
428 428  [REPORTING_YEAR]-[PERIOD_INDICATOR][PERIOD_VALUE]
429 429  
430 430  Where:
431 -
432 432  REPORTING_YEAR represents the reporting year as four digits (YYYY) PERIOD_INDICATOR identifies the type of period which determines the duration of the period
433 -
434 434  PERIOD_VALUE indicates the actual period within the year
435 435  
436 436  The following section details each of the standard reporting periods defined in SDMX:
437 437  
438 -**Reporting Year**:
439 -
440 - Period Indicator: A
441 -
426 +**Reporting Year**:
427 +Period Indicator: A
442 442  Period Duration: P1Y (one year)
443 -
444 444  Limit per year: 1
430 +Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1)
445 445  
446 -Representation: common:ReportingYearType (YYYY-A1, e.g. 2000-A1) **Reporting Semester:**
447 -
448 - Period Indicator: S
449 -
432 +**Reporting Semester:**
433 +Period Indicator: S
450 450  Period Duration: P6M (six months)
451 -
452 452  Limit per year: 2
436 +Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2)
453 453  
454 -Representation: common:ReportingSemesterType (YYYY-Ss, e.g. 2000-S2) **Reporting Trimester:**
455 -
456 - Period Indicator: T
457 -
438 +**Reporting Trimester:**
439 +Period Indicator: T
458 458  Period Duration: P4M (four months)
459 -
460 460  Limit per year: 3
442 +Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3)
461 461  
462 -Representation: common:ReportingTrimesterType (YYYY-Tt, e.g. 2000-T3) **Reporting Quarter:**
463 -
464 - Period Indicator: Q
465 -
444 +**Reporting Quarter:**
445 +Period Indicator: Q
466 466  Period Duration: P3M (three months)
467 -
468 468  Limit per year: 4
448 +Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4)
469 469  
470 -Representation: common:ReportingQuarterType (YYYY-Qq, e.g. 2000-Q4) **Reporting Month**:
471 -
450 +**Reporting Month**:
472 472  Period Indicator: M
473 -
474 474  Period Duration: P1M (one month)
475 -
476 476  Limit per year: 1
477 -
478 478  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.
479 479  
480 480  **Reporting Week**:
481 -
482 482  Period Indicator: W
483 -
484 484  Period Duration: P7D (seven days)
485 -
486 486  Limit per year: 53
487 -
488 488  Representation: common:ReportingWeekType (YYYY-Www, e.g. 2000-W53)
461 +Notes: There are either 52 or 53 weeks in a reporting year. This is based on the ISO 8601 definition of a week (Monday - Saturday), where the first week of a reporting year is defined as the week with the first Thursday on or after the reporting year start day.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[2~]^^>>path:#_ftn2]](%%) The reporting week is always represented as two digits, therefore 1-9 are 0 padded (e.g. 01). This allows the values to be sorted chronologically using textual sorting methods.
489 489  
490 -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.
491 -
492 492  **Reporting Day**:
493 -
494 494  Period Indicator: D
495 -
496 496  Period Duration: P1D (one day)
497 -
498 498  Limit per year: 366
499 -
500 500  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).
501 501  
502 502  This allows the values to be sorted chronologically using textual sorting methods.
... ... @@ -507,45 +507,31 @@
507 507  
508 508  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]):
509 509  
510 -1. **Determine [REPORTING_YEAR_BASE]:**
511 -
477 +**~1. Determine [REPORTING_YEAR_BASE]:**
512 512  Combine [REPORTING_YEAR] of the reporting period value (YYYY) with [REPORTING_YEAR_START_DAY] (MM-DD) to get a date (YYYY-MM-DD).
513 -
514 514  This is the [REPORTING_YEAR_START_DATE]
515 -
516 -**a) If the [PERIOD_INDICATOR] is W:**
517 -
518 -1.
519 -11.
520 -111.
521 -1111. **If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
522 -
480 +**a) If the [PERIOD_INDICATOR] is W:
481 +~1. If [REPORTING_YEAR_START_DATE] is a Friday, Saturday, or Sunday:**
523 523  Add^^3^^ (P3D, P2D, or P1D respectively) to the [REPORTING_YEAR_START_DATE]. The result is the [REPORTING_YEAR_BASE].
524 524  
525 -1.
526 -11.
527 -111.
528 -1111. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
529 -
484 +​​​​​​​2. **If [REPORTING_YEAR_START_DATE] is a Monday, Tuesday, Wednesday, or Thursday:**
530 530  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]
531 531  
532 -b) **Else:**
489 +**2. Determine [PERIOD_DURATION]:**
533 533  
534 -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.
535 535  
536 -1. **Determine [PERIOD_DURATION]:**
537 -11.
538 -111. If the [PERIOD_INDICATOR] is A, the [PERIOD_DURATION] is P1Y.
539 -111. If the [PERIOD_INDICATOR] is S, the [PERIOD_DURATION] is P6M.
540 -111. If the [PERIOD_INDICATOR] is T, the [PERIOD_DURATION] is P4M.
541 -111. If the [PERIOD_INDICATOR] is Q, the [PERIOD_DURATION] is P3M.
542 -111. If the [PERIOD_INDICATOR] is M, the [PERIOD_DURATION] is P1M.
543 -111. If the [PERIOD_INDICATOR] is W, the [PERIOD_DURATION] is P7D.
544 -111. If the [PERIOD_INDICATOR] is D, the [PERIOD_DURATION] is P1D.
545 -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" %)^^~[3~]^^>>path:#_ftn3]](%%) this to the [REPORTING_YEAR_BASE]. The result is the [PERIOD_START].
546 546  
547 -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].
548 -
549 549  1. **Determine the [PERIOD_END]:**
550 550  
551 551  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].
... ... @@ -1240,7 +1240,7 @@
1240 1240  
1241 1241  == 10.1 Introduction ==
1242 1242  
1243 -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:
1196 +The Validation and Transformation Language (VTL) supports the definition of Transformations, which are algorithms to calculate new data starting from already existing ones[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[4~]^^>>path:#_ftn4]](%%). The purpose of the VTL in the SDMX context is to enable the:
1244 1244  
1245 1245  * definition of validation and transformation algorithms, in order to specify how to calculate new data  from existing ones;
1246 1246  * 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);
... ... @@ -1264,7 +1264,7 @@
1264 1264  
1265 1265  In any case, the aliases used in the VTL transformations have to be mapped to the
1266 1266  
1267 -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. 
1220 +SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL transformations, rulesets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[5~]^^>>path:#_ftn5]](%%) or user defined operators[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[6~]^^>>path:#_ftn6]](%%)  to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 
1268 1268  
1269 1269  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.
1270 1270  
... ... @@ -1274,7 +1274,7 @@
1274 1274  
1275 1275  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.
1276 1276  
1277 -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:^^ ^^
1230 +The SDMX URN[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[7~]^^>>path:#_ftn7]](%%) is the concatenation of the following parts, separated by special symbols like dot, equal, asterisk, comma, and parenthesis:^^ ^^
1278 1278  
1279 1279  * SDMXprefix                                                                                   
1280 1280  * SDMX-IM-package-name             
... ... @@ -1282,7 +1282,7 @@
1282 1282  * agency-id                                                                          
1283 1283  * maintainedobject-id
1284 1284  * maintainedobject-version
1285 -* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
1238 +* container-object-id [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[8~]^^>>path:#_ftn8]]
1286 1286  * object-id
1287 1287  
1288 1288  The generic structure of the URN is the following:
... ... @@ -1301,7 +1301,7 @@
1301 1301  
1302 1302  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).
1303 1303  
1304 -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:
1257 +The **maintainedobject-id** is the name of the maintained object which the artefact belongs to, and in case the artefact itself is maintainable[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[9~]^^>>path:#_ftn9]](%%), coincides with the name of the artefact. Therefore the maintainedobject-id depends on the class of the artefact:
1305 1305  
1306 1306  * if the artefact is a ,,Dataflow,,, which is a maintainable class,  the maintainedobject-id is the Dataflow name (dataflow-id);
1307 1307  * 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;
... ... @@ -1321,7 +1321,7 @@
1321 1321  
1322 1322  * if the artefact is a ,,Concept ,,(the object-id is the name of the ,,Concept,,)
1323 1323  
1324 -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]](%%):
1277 +For example, by using the URN, the VTL transformation that sums two SDMX dataflows DF1 and DF2 and assigns the result to a third persistent dataflow DFR, assuming that DF1, DF2  and  DFR are the maintainedobject-id of the three dataflows, that their version is 1.0 and their Agency is AG, would be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[10~]^^>>path:#_ftn10]](%%):
1325 1325  
1326 1326  ‘urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=AG:DFR(1.0)’  <-
1327 1327  
... ... @@ -1339,14 +1339,14 @@
1339 1339  * 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: 
1340 1340  ** “datastructure” for the classes Dataflow, Dimension, MeasureDimension, TimeDimension, PrimaryMeasure, DataAttribute,  
1341 1341  ** “conceptscheme” for the classes Concept and ConceptScheme o “codelist” for the class Codelist.
1342 -* 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]](%%).
1343 -* 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).
1295 +* The **class-name** can be omitted as it can be deduced from the VTL invocation.  In particular, starting from the VTL class of the invoked artefact (e.g. dataset, component, identifier, measure, attribute, variable, valuedomain),  which is known given the syntax of the invoking VTL operator[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[11~]^^>>path:#_ftn11]](%%), the SDMX class can be deduced from the mapping rules between VTL and SDMX (see the section “Mapping between VTL and SDMX” hereinafter)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[12~]^^>>path:#_ftn12]](%%).
1296 +* If the **agency-id** is not specified, it is assumed by default equal to the agency-id of the TransformationScheme, UserDefinedOperatorScheme or RulesetScheme from which the artefact is invoked. For example, the agency-id can be omitted if it is the same as the invoking T,,ransformationScheme,, and cannot be omitted if the artefact comes from another agency.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[13~]^^>>path:#_ftn13]](%%)  Take also into account that, according to the VTL consistency rules, the agency of the result of a ,,Transformation,, must be the same as its ,,TransformationScheme,,, therefore the agency-id can be omitted for all the results (left part of ,,Transformation,, statements).
1344 1344  * 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;
1345 1345  ** 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
1346 1346  
1347 1347  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;
1348 1348  
1349 -*
1302 +*
1350 1350  ** if the referenced artefact is a ,,ConceptScheme, ,,which is a,, ,,maintainable class,,, ,,the maintained object is the ,,conceptScheme-id,, and obviously cannot be omitted;
1351 1351  ** if the referenced artefact is a ,,Codelist, ,,which is a maintainable class, the maintainedobject-id is the ,,codelist-id,, and obviously cannot be omitted.
1352 1352  * 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.,, ,,
... ... @@ -1367,11 +1367,11 @@
1367 1367  
1368 1368  DFR  :=  DF1 + DF2
1369 1369  
1370 -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]](%%):
1323 +The references to the ,,Codelists,, can be simplified similarly. For example, given the non-abbreviated reference to the ,,Codelist,,  AG:CL_FREQ(1.0), which is[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[14~]^^>>path:#_ftn14]](%%):
1371 1371  
1372 1372  ‘urn:sdmx:org.sdmx.infomodel.codelist.Codelist=AG:CL_FREQ(1.0)’
1373 1373  
1374 -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]](%%):
1327 +if the ,,Codelist,, is referenced from a ruleset scheme belonging to the agency AG, omitting all the optional parts, the abbreviated reference would become simply[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[15~]^^>>path:#_ftn15]](%%):
1375 1375  
1376 1376  CL_FREQ
1377 1377  
... ... @@ -1381,7 +1381,7 @@
1381 1381  
1382 1382  SECTOR
1383 1383  
1384 -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]](%%):
1337 +For example, the transformation for renaming the component SECTOR of the dataflow DF1 into SEC can be written as[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[16~]^^>>path:#_ftn16]](%%):
1385 1385  
1386 1386  ‘DFR(1.0)’ := ‘DF1(1.0)’ [rename SECTOR to SEC]
1387 1387  
... ... @@ -1415,9 +1415,9 @@
1415 1415  
1416 1416  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. 
1417 1417  
1418 -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]](%%).
1371 +In the signature, given the mapping between VTL and SDMX better described in the following paragraphs, a reference to a VTL Value Domain becomes a reference to a SDMX Codelist or to a SDMX ConceptScheme (for SDMX measure dimensions), while a reference to a VTL Represented Variable becomes a reference to a SDMX Concept, assuming for it a definite representation[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[17~]^^>>path:#_ftn17]](%%).
1419 1419  
1420 -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]](%%)
1373 +In general, for referencing SDMX Codelists and Concepts, the conventions described in the previous paragraphs apply. In the Ruleset syntax, the elements that reference SDMX artefacts are called “valueDomain” and “variable” for the Datapoint Rulesets and “ruleValueDomain”, “ruleVariable”, “condValueDomain” “condVariable” for the Hierarchical Rulesets). The syntax of the Ruleset signature allows also to define aliases of the elements above, these aliases are valid only within the specific ruleset definition statement and cannot be mapped to SDMX.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[18~]^^>>path:#_ftn18]](%%)
1421 1421  
1422 1422  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.
1423 1423  
... ... @@ -1431,15 +1431,15 @@
1431 1431  
1432 1432  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. 
1433 1433  
1434 -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]](%%).
1387 +In the opposite direction, every time an object calculated by means of VTL must be treated as a SDMX object (for example for exchanging it through SDMX), there is the need of a SDMX definition of the object, so that the SDMX operations can take place.  The SDMX definition is needed for the VTL objects for which a SDMX use is envisaged[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[19~]^^>>path:#_ftn19]](%%).
1435 1435  
1436 1436  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). 
1437 1437  
1438 1438  === 10.3.2 General mapping of VTL and SDMX data structures ===
1439 1439  
1440 -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]](%%).
1393 +This section makes reference to the VTL “Model for data and their structure”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[20~]^^>>path:#_ftn20]](%%) and the correspondent SDMX “Data Structure Definition”[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[21~]^^>>path:#_ftn21]](%%).
1441 1441  
1442 -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]](%%)
1395 +The main type of artefact that the VTL can manipulate is the VTL Data Set, which in general is mapped to the SDMX Dataflow. This means that a VTL Transformation, in the SDMX context, expresses the algorithm for calculating a derived Dataflow starting from some already existing Dataflows (either collected or derived).[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[22~]^^>>path:#_ftn22]](%%)
1443 1443  
1444 1444  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.
1445 1445  
... ... @@ -1449,7 +1449,7 @@
1449 1449  
1450 1450  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. 
1451 1451  
1452 -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.
1405 +However, a VTL Data Structure can have any number of Identifiers, Measures and Attributes, while a SDMX 2.1 DataStructureDefinition can have any number of Dimensions and DataAttributes but just one PrimaryMeasure[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[23~]^^>>path:#_ftn23]](%%). This is due to a difference between SDMX 2.1 and VTL in the possible representation methods of the data that contain more measures.
1453 1453  
1454 1454  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. 
1455 1455  
... ... @@ -1513,7 +1513,7 @@
1513 1513  
1514 1514   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;
1515 1515  
1516 -*
1469 +*
1517 1517  ** 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.
1518 1518  ** 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
1519 1519  ** 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
... ... @@ -1520,7 +1520,7 @@
1520 1520  
1521 1521  **10.3.3.3 From SDMX DataAttributes to VTL Measures **
1522 1522  
1523 -*
1476 +*
1524 1524  ** 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.
1525 1525  
1526 1526  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.
... ... @@ -1539,7 +1539,7 @@
1539 1539  
1540 1540  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
1541 1541  
1542 -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]](%%)
1495 +PrimaryMeasure). In this case it becomes mandatory to specify a different 1958 mapping method through the VtlMappingScheme and VtlDataflowMapping 1959 classes.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[24~]^^>>path:#_ftn24]](%%)
1543 1543  
1544 1544  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. 
1545 1545  
... ... @@ -1606,7 +1606,7 @@
1606 1606  
1607 1607   the values of the VTL identifiers become the values of the corresponding SDMX Dimensions, for all the observations of the set above
1608 1608  
1609 -*
1562 +*
1610 1610  ** 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)
1611 1611  ** the value of the j^^th^^ VTL measure becomes the value of the SDMX PrimaryMeasure of the j^^th^^ observation of the set
1612 1612  ** the values of the VTL Attributes become the values of the corresponding SDMX DataAttributes (in principle for all the observations of the set above)
... ... @@ -1656,15 +1656,15 @@
1656 1656  
1657 1657   The VtlMappingScheme is a container for zero or more VtlDataflowMapping (besides possible mappings to artefacts other than dataflows).
1658 1658  
1659 -=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
1612 +=== 10.3.6 Mapping dataflow subsets to distinct VTL data sets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^**~[25~]**^^>>path:#_ftn25]](%%) ===
1660 1660  
1661 1661  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
1662 1662  
1663 1663  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).
1664 1664  
1665 -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]](%%)
1618 +As a matter of fact, in some cases it can be useful to define VTL operations involving definite parts of a SDMX Dataflow instead than the whole.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[26~]^^>>path:#_ftn26]](%%)
1666 1666  
1667 -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]](%%)
1620 +Therefore, in order to make the coding of  VTL operations simpler when applied on parts of SDMX Dataflows, it is allowed to map distinct parts of a SDMX Dataflow to distinct VTL data sets according to the following rules and conventions. This kind of mapping is possible both from SDMX to VTL and from VTL to SDMX, as better explained below.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[27~]^^>>path:#_ftn27]](%%)
1668 1668  
1669 1669   Given a SDMX Dataflow and some predefined Dimensions of its
1670 1670  
... ... @@ -1676,14 +1676,14 @@
1676 1676  
1677 1677  In practice, this kind mapping is obtained like follows:
1678 1678  
1679 -* 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.
1632 +* For a given SDMX dataflow, the user (VTL definer) declares  the dimension components on which the mapping will be based, in a given order.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[28~]^^>>path:#_ftn28]](%%) Following the example above, imagine that the user declares the dimensions INDICATOR and COUNTRY.
1680 1680  * The VTL dataset is given a name using a special notation also called “ordered concatenation” and composed of the following parts: 
1681 1681  ** The reference to the SDMX dataflow (expressed according to the rules described in the previous paragraphs, i.e. URN, abbreviated
1682 1682  
1683 -URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
1636 +URN or another alias); for example DF(1.0); o a slash (“/”) as a separator; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[29~]^^>>path:#_ftn29]]
1684 1684  
1685 -*
1686 -** 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.
1638 +*
1639 +** The reference to a specific part of the SDMX dataflow above, expressed as the concatenation of the values that the SDMX dimensions declared above must have, separated by dots (“.”) and written in the order in which these dimensions are defined[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[30~]^^>>path:#_ftn30]](%%) . For example  POPULATION.USA would mean that such a VTL dataset is mapped to the SDMX observations for which the dimension  //INDICATOR// is equal to POPULATION and the dimension //COUNTRY// is equal to USA.
1687 1687  
1688 1688  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.
1689 1689  
... ... @@ -1701,7 +1701,7 @@
1701 1701  
1702 1702  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.
1703 1703  
1704 -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.
1657 +As already said, the mapping from SDMX to VTL happens when the VTL datasets are operand of VTL transformations, instead the mapping from VTL to SDMX happens when the VTL datasets are result of VTL transformations[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[31~]^^>>path:#_ftn31]](%%) and need to be treated as SDMX objects. This kind of mapping can be applied independently in the two directions and the Dimensions on which the mapping is based can be different in the two directions: these Dimensions are defined in the ToVtlSpaceKey and in the FromVtlSpaceKey classes respectively.
1705 1705  
1706 1706  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.
1707 1707  
... ... @@ -1711,7 +1711,7 @@
1711 1711  
1712 1712  //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.
1713 1713  
1714 -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 …). 
1667 +In order to obtain the data structure of these VTL datasets from the SDMX one, it is assumed that the SDMX dimensions on which the mapping is based are dropped, i.e. not maintained in the VTL data structure; this is possible because their values are fixed for each one of the invoked VTL datasets[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[32~]^^>>path:#_ftn32]](%%). After that, the mapping method from SDMX to VTL specified for the dataflow DF1(1.0) is applied (i.e. basic, pivot …). 
1715 1715  
1716 1716  In the example above, for all the datasets of the kind
1717 1717  
... ... @@ -1731,7 +1731,7 @@
1731 1731  
1732 1732  …   …   …
1733 1733  
1734 -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]]
1687 +In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX dataflow to different VTL datasets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a dataflow. [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[33~]^^>>path:#_ftn33]]
1735 1735  
1736 1736  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.
1737 1737  
... ... @@ -1754,12 +1754,12 @@
1754 1754  
1755 1755  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:
1756 1756  
1757 -* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)
1758 -* 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]]
1710 +* each part is calculated as a  VTL derived dataset, result of a dedicated VTL transformation; [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[34~]^^>>path:#_ftn34]](%%)
1711 +* the data structure of all these VTL datasets has the TIME_PERIOD identifier and does not have the INDICATOR and COUNTRY identifiers.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[35~]^^>>path:#_ftn35]]
1759 1759  
1760 -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]](%%).
1713 +Under these hypothesis, such derived VTL datasets can be mapped to DF2(1.0) by declaring the Dimensions INDICATOR and COUNTRY as mapping dimensions[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[36~]^^>>path:#_ftn36]](%%).
1761 1761  
1762 -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]]
1715 +The corresponding VTL transformations, assuming that the result needs to be persistent, would be of this kind:^^ ^^[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[37~]^^>>path:#_ftn37]]
1763 1763  
1764 1764  ‘DF2(1.0)///INDICATORvalue//.//COUNTRYvalue//’  <-  expression
1765 1765  
... ... @@ -1826,9 +1826,9 @@
1826 1826  
1827 1827  …);
1828 1828  
1829 -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.
1782 +In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent data sets are united and give the final result DF2(1.0)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[38~]^^>>path:#_ftn38]](%%), which can be mapped one-to-one to the homonymous SDMX dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
1830 1830  
1831 -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]]
1784 +Therefore, mapping different VTL datasets having the same data structure to different parts of a SDMX dataflow, i.e. in the direction from VTL to SDMX, through the ordered concatenation notation is equivalent to a proper use of the operators “calc” and “union” on such datasets. [[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[39~]^^>>path:#_ftn39]](%%)[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[40~]^^>>path:#_ftn40]]
1832 1832  
1833 1833  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).
1834 1834  
... ... @@ -1877,7 +1877,7 @@
1877 1877  
1878 1878  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). 
1879 1879  
1880 -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.
1833 +As for the mapping between VTL variables and SDMX Concepts, it should be noted that these artefacts do not coincide perfectly. In fact, the VTL variables are  represented variables, defined always on the same Value Domain (“Representation” in SDMX) independently of the data set / data structure in which they appear[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[41~]^^>>path:#_ftn41]](%%), while the SDMX Concepts can have different Representations in different DataStructures.[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[42~]^^>>path:#_ftn42]](%%) This means that one SDMX Concept can correspond to many VTL Variables, one for each representation the Concept has.
1881 1881  
1882 1882  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
1883 1883  
... ... @@ -2222,7 +2222,7 @@
2222 2222  |N|fixed number of digits used in the preceding  textual representation of the month or the day
2223 2223  | |
2224 2224  
2225 -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]](%%).
2178 +The default conversion, either standard or customized, can be used to deduce automatically the representation of the components of the result of a VTL transformation. In alternative, the representation of the resulting SDMX Dataflow can be given explicitly by providing its DataStructureDefinition. In other words, the representation specified in the DSD, if available, overrides any default conversion[[(% class="wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^~[43~]^^>>path:#_ftn43]](%%).
2226 2226  
2227 2227  === 10.4.5 Null Values ===
2228 2228