Changes for page 12 Validation and Transformation Language (VTL)
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... ... @@ -14,10 +14,8 @@ 14 14 15 15 The VTL language can be applied to SDMX artefacts by mapping the SDMX IM model artefacts to the model artefacts that VTL can manipulate{{footnote}}In this chapter, in order to distinguish VTL and SDMX model artefacts, the VTL ones are written in the Arial font while the SDMX ones in Courier New{{/footnote}}. Thus, the SDMX artefacts can be used in VTL as inputs and/or outputs of Transformations. It is important to be aware that the artefacts do not always have the same names in the SDMX and VTL IMs, nor do they always have the same meaning. The more evident example is given by the SDMX Dataset and the VTL "Data Set", which do not correspond one another: as a matter of fact, the VTL "Data Set" maps to the SDMX "Dataflow", while the SDMX "Dataset" has no explicit mapping to VTL (such an abstraction is not needed in the definition of VTL Transformations). A SDMX "Dataset", however, is an instance of a SDMX "Dataflow" and can be the artefact on which the VTL transformations are executed (i.e., the Transformations are defined on Dataflows and are applied to Dataflow instances that can be Datasets). 16 16 17 -The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of 17 +The VTL programs (Transformation Schemes) are represented in SDMX through the TransformationScheme maintainable class which is composed of Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result. 18 18 19 -Transformation (nameable artefact). Each Transformation assigns the outcome of the evaluation of a VTL expression to a result. 20 - 21 21 This section does not explain the VTL language or any of the content published in the VTL guides. Rather, this is a description of how the VTL can be used in the SDMX context and applied to SDMX artefacts. 22 22 23 23 == 12.2 References to SDMX artefacts from VTL statements == ... ... @@ -28,10 +28,8 @@ 28 28 29 29 The alias of an SDMX artefact can be its URN (Universal Resource Name), an abbreviation of its URN or another user-defined name. 30 30 31 -In any case, the aliases used in the VTL Transformations have to be mapped to the 29 +In any case, the aliases used in the VTL Transformations have to be mapped to the SDMX artefacts through the VtlMappingScheme and VtlMapping classes (see the section of the SDMX IM relevant to the VTL). A VtlMapping allows specifying the aliases to be used in the VTL Transformations, Rulesets{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 32 32 33 -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{{footnote}}See also the section "VTL-DL Rulesets" in the VTL Reference Manual.{{/footnote}} or User Defined Operators{{footnote}}The VTLMappings are used also for User Defined Operators (UDO). Although UDOs are envisaged to be defined on generic operands, so that the specific artefacts to be manipulated are passed as parameters at their invocation, it is also possible that an UDO invokes directly some specific SDMX artefacts. These SDMX artefacts have to be mapped to the corresponding aliases used in the definition of the UDO through the VtlMappingScheme and VtlMapping classes as well.{{/footnote}} to reference SDMX artefacts. A VtlMappingScheme is a container for zero or more VtlMapping. 34 - 35 35 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. 36 36 37 37 The references through the URN and the abbreviated URN are described in the following paragraphs. ... ... @@ -202,7 +202,7 @@ 202 202 203 203 === 12.3.3 Mapping from SDMX to VTL data structures === 204 204 205 - **12.3.3.1 Basic Mapping**201 +==== 12.3.3.1 Basic Mapping ==== 206 206 207 207 The main mapping method from SDMX to VTL is called **Basic **mapping. This is considered as the default mapping method and is applied unless a different method is specified through the VtlMappingScheme and VtlDataflowMapping classes. When transforming **from SDMX to VTL**, this method consists in leaving the components unchanged and maintaining their names and roles, according to the following table: 208 208 ... ... @@ -232,18 +232,11 @@ 232 232 The SDMX structures that contain a MeasureDimension are mapped as described below (this mapping is equivalent to a pivoting operation): 233 233 234 234 * A SDMX simple dimension becomes a VTL (simple) identifier and a SDMX TimeDimension becomes a VTL (time) identifier; 235 -* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a 236 - 237 -Component; 238 - 231 +* Each possible Code Cj of the SDMX MeasureDimension is mapped to a VTL Measure, having the same name as the SDMX Code (i.e. Cj); the VTL Measure Cj is a new VTL component even if the SDMX data structure has not such a Component; 239 239 * The SDMX MeasureDimension is not mapped to VTL (it disappears in the VTL Data Structure); 240 240 * The SDMX Measure is not mapped to VTL as well (it disappears in the VTL Data Structure); 241 241 * An SDMX DataAttribute is mapped in different ways according to its AttributeRelationship: 242 -** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the 243 - 244 -AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension; 245 - 246 -* 235 +** If, according to the SDMX AttributeRelationship, the values of the DataAttribute do not depend on the values of the MeasureDimension, the SDMX DataAttribute becomes a VTL Attribute having the same name. This happens if the AttributeRelationship is not specified (i.e. the DataAttribute does not depend on any DimensionComponent and therefore is at data set level), or if it refers to a set (or a group) of dimensions which does not include the MeasureDimension; 247 247 ** Otherwise, if, according to the SDMX AttributeRelationship, the values of the DataAttribute depend on the MeasureDimension, the SDMX DataAttribute is mapped to one VTL Attribute for each possible Code of the SDMX MeasureDimension. By default, the names of the VTL Attributes are obtained by concatenating the name of the SDMX DataAttribute and the names of the correspondent Code of the MeasureDimension separated by underscore. For example, if the SDMX DataAttribute is named DA and the possible Codes of the SDMX MeasureDimension are named C1, C2, …, Cn, then the corresponding VTL Attributes will be named DA_C1, DA_C2, …, DA_Cn (if different names are desired, they can be achieved afterwards by renaming the Attributes through VTL operators). 248 248 ** Like in the Basic mapping, the resulting VTL Attributes are considered as dependent on all the VTL identifiers (i.e. "at data point / observation level"), because VTL does not have the SDMX notion of Attribute Relationship. 249 249 ... ... @@ -266,10 +266,7 @@ 266 266 At observation / data point level, calling Cj (j=1, … n) the j^^th^^ Code of the MeasureDimension: 267 267 268 268 * 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 Code Cj of the SDMX MeasureDimension; 269 -* 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) 270 - 271 -Identifiers, (time) Identifier and Attributes. 272 - 258 +* 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. 273 273 * The value of the Measure of the SDMX observation belonging to the set above and having MeasureDimension=Cj becomes the value of the VTL Measure Cj 274 274 * 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 275 275 ... ... @@ -362,7 +362,7 @@ 362 362 The mapping table is the following: 363 363 364 364 (% style="width:689.294px" %) 365 -|(% style="width:344px" %)VTL|(% style="width:341px" %)SDMX 351 +|(% style="width:344px" %)**VTL**|(% style="width:341px" %)**SDMX** 366 366 |(% style="width:344px" %)(Simple) Identifier|(% style="width:341px" %)Dimension 367 367 |(% style="width:344px" %)(Time) Identifier|(% style="width:341px" %)TimeDimension 368 368 |(% style="width:344px" %)Some Measures|(% style="width:341px" %)Measure ... ... @@ -422,24 +422,17 @@ 422 422 423 423 SDMX Dataflow having INDICATOR=//INDICATORvalue //and COUNTRY=// COUNTRYvalue//. For example, the VTL dataset ‘DF1(1.0.0)/POPULATION.USA’ would contain all the observations of DF1(1.0.0) having INDICATOR = POPULATION and COUNTRY = USA. 424 424 425 -In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents 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 Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. 411 +In order to obtain the data structure of these VTL Data Sets from the SDMX one, it is assumed that the SDMX DimensionComponents 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 Data Sets{{footnote}}If these DimensionComponents would not be dropped, the various VTL Data Sets resulting from this kind of mapping would have non-matching values for the Identifiers corresponding to the mapping Dimensions (e.g. POPULATION and COUNTRY). As a consequence, taking into account that the typical binary VTL operations at dataset level (+, -, *, / and so on) are executed on the observations having matching values for the identifiers, it would not be possible to compose the resulting VTL datasets one another (e.g. it would not be possible to calculate the population ratio between USA and CANADA).{{/footnote}}. After that, the mapping method from SDMX to VTL specified for the Dataflow DF1(1.0.0) is applied (i.e. basic, pivot …). 426 426 427 -basi c, pivot…).413 +In the example above, for all the datasets of the kind ‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only. 428 428 429 -In the example above, for all the datasets of the kind 430 - 431 -‘DF1(1.0.0)///INDICATORvalue//.//COUNTRYvalue//’, the dimensions INDICATOR and COUNTRY would be dropped so that the data structure of all the resulting VTL Data Sets would have the identifier TIME_PERIOD only. 432 - 433 433 It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression: 434 434 435 435 ‘DF1(1.0.0)/POPULATION.USA’ := 436 - 437 437 DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ]; 438 438 439 439 ‘DF1(1.0.0)/POPULATION.CANADA’ := 440 - 441 441 DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ]; 442 - 443 443 … … … 444 444 445 445 In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets 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.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}} ... ... @@ -453,7 +453,6 @@ 453 453 This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//: 454 454 455 455 ‘DF1(1.0.0)/POPULATION.’ := 456 - 457 457 DF1(1.0.0) [ sub INDICATOR=“POPULATION” ]; 458 458 459 459 Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD. ... ... @@ -484,11 +484,8 @@ 484 484 ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12; 485 485 486 486 … … … 487 - 488 488 ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21; 489 - 490 490 ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22; 491 - 492 492 … … … 493 493 494 494 As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively: ... ... @@ -496,13 +496,9 @@ 496 496 VTL dataset INDICATOR value COUNTRY value 497 497 498 498 ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA 499 - 500 500 ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … … 501 - 502 502 ‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA 503 - 504 504 ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA 505 - 506 506 … … … 507 507 508 508 It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be: ... ... @@ -601,7 +601,7 @@ 601 601 [[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_e3df33ae.png||height="543" width="483"]] 602 602 603 603 (% class="wikigeneratedid" id="HFigure222013VTLDataTypes" %) 604 -Figure 22 – VTL Data Types 575 +**Figure 22 – VTL Data Types** 605 605 606 606 The VTL scalar types are in turn subdivided in basic scalar types, which are elementary (not defined in term of other data types) and Value Domain and Set scalar types, which are defined in terms of the basic scalar types. 607 607 ... ... @@ -608,7 +608,7 @@ 608 608 The VTL basic scalar types are listed below and follow a hierarchical structure in terms of supersets/subsets (e.g. "scalar" is the superset of all the basic scalar types): 609 609 610 610 611 -Figure 23 – VTL Basic Scalar Types 582 +**Figure 23 – VTL Basic Scalar Types** 612 612 613 613 ((( 614 614 ... ... @@ -636,204 +636,159 @@ 636 636 637 637 The following table describes the default mapping for converting from the SDMX data types to the VTL basic scalar types. 638 638 639 -|SDMX data type (BasicComponentDataType)|Default VTL basic scalar type 640 -|((( 610 +(% style="width:823.294px" %) 611 +|(% style="width:509px" %)**SDMX data type (BasicComponentDataType)**|(% style="width:312px" %)**Default VTL basic scalar type** 612 +|(% style="width:509px" %)((( 641 641 String 642 - 643 643 (string allowing any character) 644 -)))|string 645 -|((( 615 +)))|(% style="width:312px" %)string 616 +|(% style="width:509px" %)((( 646 646 Alpha 647 - 648 648 (string which only allows A-z) 649 -)))|string 650 -|((( 619 +)))|(% style="width:312px" %)string 620 +|(% style="width:509px" %)((( 651 651 AlphaNumeric 652 - 653 653 (string which only allows A-z and 0-9) 654 -)))|string 655 -|((( 623 +)))|(% style="width:312px" %)string 624 +|(% style="width:509px" %)((( 656 656 Numeric 657 - 658 658 (string which only allows 0-9, but is not numeric so that is can having leading zeros) 659 -)))|string 660 -|((( 627 +)))|(% style="width:312px" %)string 628 +|(% style="width:509px" %)((( 661 661 BigInteger 662 - 663 663 (corresponds to XML Schema xs:integer datatype; infinite set of integer values) 664 -)))|integer 665 -|((( 631 +)))|(% style="width:312px" %)integer 632 +|(% style="width:509px" %)((( 666 666 Integer 667 - 668 -(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 669 - 670 -(inclusive)) 671 -)))|integer 672 -|((( 634 +(corresponds to XML Schema xs:int datatype; between -2147483648 and +2147483647 (inclusive)) 635 +)))|(% style="width:312px" %)integer 636 +|(% style="width:509px" %)((( 673 673 Long 674 - 675 -(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and 676 - 677 -+9223372036854775807 (inclusive)) 678 -)))|integer 679 -|((( 638 +(corresponds to XML Schema xs:long datatype; between -9223372036854775808 and +9223372036854775807 (inclusive)) 639 +)))|(% style="width:312px" %)integer 640 +|(% style="width:509px" %)((( 680 680 Short 681 - 682 682 (corresponds to XML Schema xs:short datatype; between -32768 and -32767 (inclusive)) 683 -)))|integer 684 -|Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|number 685 -|((( 643 +)))|(% style="width:312px" %)integer 644 +|(% style="width:509px" %)Decimal (corresponds to XML Schema xs:decimal datatype; subset of real numbers that can be represented as decimals)|(% style="width:312px" %)number 645 +|(% style="width:509px" %)((( 686 686 Float 687 - 688 688 (corresponds to XML Schema xs:float datatype; patterned after the IEEE single-precision 32-bit floating point type) 689 -)))|number 690 -|((( 648 +)))|(% style="width:312px" %)number 649 +|(% style="width:509px" %)((( 691 691 Double 692 - 693 693 (corresponds to XML Schema xs:double datatype; patterned after the IEEE double-precision 64-bit floating point type) 694 -)))|number 695 -|((( 652 +)))|(% style="width:312px" %)number 653 +|(% style="width:509px" %)((( 696 696 Boolean 655 +(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of binary-valued logic: {true, false}) 656 +)))|(% style="width:312px" %)boolean 697 697 698 -(corresponds to the XML Schema xs:boolean datatype; support the mathematical concept of 699 - 700 -binary-valued logic: {true, false}) 701 -)))|boolean 702 - 703 -| |(% colspan="2" %)((( 658 +(% style="width:822.294px" %) 659 +|(% colspan="2" style="width:507px" %)((( 704 704 URI 705 - 706 706 (corresponds to the XML Schema xs:anyURI; absolute or relative Uniform Resource Identifier Reference) 707 -)))|(% colspan=" 2" %)string708 -| |(% colspan="2" %)(((662 +)))|(% colspan="1" style="width:311px" %)string 663 +|(% colspan="2" style="width:507px" %)((( 709 709 Count 710 - 711 711 (an integer following a sequential pattern, increasing by 1 for each occurrence) 712 -)))|(% colspan=" 2" %)integer713 -| |(% colspan="2" %)(((666 +)))|(% colspan="1" style="width:311px" %)integer 667 +|(% colspan="2" style="width:507px" %)((( 714 714 InclusiveValueRange 715 - 716 716 (decimal number within a closed interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 717 -)))|(% colspan=" 2" %)number718 -| |(% colspan="2" %)(((670 +)))|(% colspan="1" style="width:311px" %)number 671 +|(% colspan="2" style="width:507px" %)((( 719 719 ExclusiveValueRange 720 - 721 721 (decimal number within an open interval, whose bounds are specified in the SDMX representation by the facets minValue and maxValue) 722 -)))|(% colspan=" 2" %)number723 -| |(% colspan="2" %)(((674 +)))|(% colspan="1" style="width:311px" %)number 675 +|(% colspan="2" style="width:507px" %)((( 724 724 Incremental 725 - 726 726 (decimal number the increased by a specific interval (defined by the interval facet), which is typically enforced outside of the XML validation) 727 -)))|(% colspan=" 2" %)number728 -| |(% colspan="2" %)(((678 +)))|(% colspan="1" style="width:311px" %)number 679 +|(% colspan="2" style="width:507px" %)((( 729 729 ObservationalTimePeriod 730 - 731 731 (superset of StandardTimePeriod and TimeRange) 732 -)))|(% colspan=" 2" %)time733 -| |(% colspan="2" %)(((682 +)))|(% colspan="1" style="width:311px" %)time 683 +|(% colspan="2" style="width:507px" %)((( 734 734 StandardTimePeriod 735 - 736 -(superset of BasicTimePeriod and 737 - 738 -ReportingTimePeriod) 739 -)))|(% colspan="2" %)time 740 -| |(% colspan="2" %)((( 685 +(superset of BasicTimePeriod and ReportingTimePeriod) 686 +)))|(% colspan="1" style="width:311px" %)time 687 +|(% colspan="2" style="width:507px" %)((( 741 741 BasicTimePeriod 742 - 743 743 (superset of GregorianTimePeriod and DateTime) 744 -)))|(% colspan=" 2" %)date745 -| |(% colspan="2" %)(((690 +)))|(% colspan="1" style="width:311px" %)date 691 +|(% colspan="2" style="width:507px" %)((( 746 746 GregorianTimePeriod 747 - 748 748 (superset of GregorianYear, GregorianYearMonth, and GregorianDay) 749 -)))|(% colspan=" 2" %)date750 -| |(% colspan="2" %)GregorianYear (YYYY)|(% colspan="2" %)date751 -| |(% colspan="2" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="2" %)date752 -| |(% colspan="2" %)GregorianDay (YYYY-MM-DD)|(% colspan="2" %)date753 -| |(% colspan="2" %)(((694 +)))|(% colspan="1" style="width:311px" %)date 695 +|(% colspan="2" style="width:507px" %)GregorianYear (YYYY)|(% colspan="1" style="width:311px" %)date 696 +|(% colspan="2" style="width:507px" %)GregorianYearMonth / GregorianMonth (YYYY-MM)|(% colspan="1" style="width:311px" %)date 697 +|(% colspan="2" style="width:507px" %)GregorianDay (YYYY-MM-DD)|(% colspan="1" style="width:311px" %)date 698 +|(% colspan="2" style="width:507px" %)((( 754 754 ReportingTimePeriod 755 - 756 -(superset of RepostingYear, ReportingSemester, 757 - 758 -ReportingTrimester, ReportingQuarter, 759 - 760 -ReportingMonth, ReportingWeek, ReportingDay) 761 -)))|(% colspan="2" %)time_period 762 -| |(% colspan="2" %)((( 700 +(superset of RepostingYear, ReportingSemester, ReportingTrimester, ReportingQuarter, ReportingMonth, ReportingWeek, ReportingDay) 701 +)))|(% colspan="1" style="width:311px" %)time_period 702 +|(% colspan="2" style="width:507px" %)((( 763 763 ReportingYear 764 - 765 765 (YYYY-A1 – 1 year period) 766 -)))|(% colspan=" 2" %)time_period767 -| |(% colspan="2" %)(((705 +)))|(% colspan="1" style="width:311px" %)time_period 706 +|(% colspan="2" style="width:507px" %)((( 768 768 ReportingSemester 769 - 770 770 (YYYY-Ss – 6 month period) 771 -)))|(% colspan=" 2" %)time_period772 -| |(% colspan="2" %)(((709 +)))|(% colspan="1" style="width:311px" %)time_period 710 +|(% colspan="2" style="width:507px" %)((( 773 773 ReportingTrimester 774 - 775 775 (YYYY-Tt – 4 month period) 776 -)))|(% colspan=" 2" %)time_period777 -| |(% colspan="2" %)(((713 +)))|(% colspan="1" style="width:311px" %)time_period 714 +|(% colspan="2" style="width:507px" %)((( 778 778 ReportingQuarter 779 - 780 780 (YYYY-Qq – 3 month period) 781 -)))|(% colspan=" 2" %)time_period782 -| |(% colspan="2" %)(((717 +)))|(% colspan="1" style="width:311px" %)time_period 718 +|(% colspan="2" style="width:507px" %)((( 783 783 ReportingMonth 784 - 785 785 (YYYY-Mmm – 1 month period) 786 -)))|(% colspan="2" %)time_period 787 -| |(% colspan="2" %)ReportingWeek|(% colspan="2" %)time_period 788 -| |(% colspan="2" %) |(% colspan="2" %) 789 -| |(% colspan="2" %) |(% colspan="2" %) 790 -|(% colspan="2" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" %) | 791 -|(% colspan="2" %)((( 721 +)))|(% colspan="1" style="width:311px" %)time_period 722 +|(% colspan="2" style="width:507px" %)ReportingWeek|(% colspan="1" style="width:311px" %)time_period 723 +|(% colspan="1" style="width:507px" %)(YYYY-Www – 7 day period; following ISO 8601 definition of a week in a year)|(% colspan="2" style="width:312px" %) 724 +|(% colspan="1" style="width:507px" %)((( 792 792 ReportingDay 793 - 794 794 (YYYY-Dddd – 1 day period) 795 -)))|(% colspan="2" %)time_period |796 -|(% colspan=" 2" %)(((727 +)))|(% colspan="2" style="width:312px" %)time_period 728 +|(% colspan="1" style="width:507px" %)((( 797 797 DateTime 798 - 799 799 (YYYY-MM-DDThh:mm:ss) 800 -)))|(% colspan="2" %)date |801 -|(% colspan=" 2" %)(((731 +)))|(% colspan="2" style="width:312px" %)date 732 +|(% colspan="1" style="width:507px" %)((( 802 802 TimeRange 803 - 804 804 (YYYY-MM-DD(Thh:mm:ss)?/<duration>) 805 -)))|(% colspan="2" %)time |806 -|(% colspan=" 2" %)(((735 +)))|(% colspan="2" style="width:312px" %)time 736 +|(% colspan="1" style="width:507px" %)((( 807 807 Month 808 - 809 809 (~-~-MM; speicifies a month independent of a year; e.g. February is black history month in the United States) 810 -)))|(% colspan="2" %)string |811 -|(% colspan=" 2" %)(((739 +)))|(% colspan="2" style="width:312px" %)string 740 +|(% colspan="1" style="width:507px" %)((( 812 812 MonthDay 813 - 814 814 (~-~-MM-DD; specifies a day within a month independent of a year; e.g. Christmas is December 25^^th^^; used to specify reporting year start day) 815 -)))|(% colspan="2" %)string |816 -|(% colspan=" 2" %)(((743 +)))|(% colspan="2" style="width:312px" %)string 744 +|(% colspan="1" style="width:507px" %)((( 817 817 Day 818 - 819 819 (~-~--DD; specifies a day independent of a month or year; e.g. the 15^^th^^ is payday) 820 -)))|(% colspan="2" %)string |821 -|(% colspan=" 2" %)(((747 +)))|(% colspan="2" style="width:312px" %)string 748 +|(% colspan="1" style="width:507px" %)((( 822 822 Time 823 - 824 824 (hh:mm:ss; time independent of a date; e.g. coffee break is at 10:00 AM) 825 -)))|(% colspan="2" %)string |826 -|(% colspan=" 2" %)(((751 +)))|(% colspan="2" style="width:312px" %)string 752 +|(% colspan="1" style="width:507px" %)((( 827 827 Duration 828 - 829 829 (corresponds to XML Schema xs:duration datatype) 830 -)))|(% colspan="2" %)duration |831 -|(% colspan=" 2" %)XHTML|(% colspan="2" %)Metadata type – not applicable|832 -|(% colspan=" 2" %)KeyValues|(% colspan="2" %)Metadata type – not applicable|833 -|(% colspan=" 2" %)IdentifiableReference|(% colspan="2" %)Metadata type – not applicable|834 -|(% colspan=" 2" %)DataSetReference|(% colspan="2" %)Metadata type – not applicable|755 +)))|(% colspan="2" style="width:312px" %)duration 756 +|(% colspan="1" style="width:507px" %)XHTML|(% colspan="2" style="width:312px" %)Metadata type – not applicable 757 +|(% colspan="1" style="width:507px" %)KeyValues|(% colspan="2" style="width:312px" %)Metadata type – not applicable 758 +|(% colspan="1" style="width:507px" %)IdentifiableReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable 759 +|(% colspan="1" style="width:507px" %)DataSetReference|(% colspan="2" style="width:312px" %)Metadata type – not applicable 835 835 836 -==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ==== 761 +(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes" %) 762 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 837 837 838 838 When VTL takes in input SDMX artefacts, it is assumed that a type conversion according to the table above always happens. In case a different VTL basic scalar type is desired, it can be achieved in the VTL program taking in input the default VTL basic scalar type above and applying to it the VTL type conversion features (see the implicit and explicit type conversion and the "cast" operator in the VTL Reference Manual). 839 839 ... ... @@ -841,39 +841,32 @@ 841 841 842 842 The following table describes the default conversion from the VTL basic scalar types to the SDMX data types . 843 843 844 -|((( 845 -VTL basic 846 - 847 -scalar type 848 -)))|((( 849 -Default SDMX data type 850 - 851 -(BasicComponentDataType 852 - 853 -) 854 -)))|Default output format 855 -|String|String|Like XML (xs:string) 856 -|Number|Float|Like XML (xs:float) 857 -|Integer|Integer|Like XML (xs:int) 858 -|Date|DateTime|YYYY-MM-DDT00:00:00Z 859 -|Time|StandardTimePeriod|<date>/<date> (as defined above) 860 -|time_period|((( 770 +(% style="width:1073.29px" %) 771 +|(% style="width:207px" %)((( 772 +**VTL basic scalar type** 773 +)))|(% style="width:462px" %)((( 774 +**Default SDMX data type (BasicComponentDataType)** 775 +)))|(% style="width:402px" %)**Default output format** 776 +|(% style="width:207px" %)String|(% style="width:462px" %)String|(% style="width:402px" %)Like XML (xs:string) 777 +|(% style="width:207px" %)Number|(% style="width:462px" %)Float|(% style="width:402px" %)Like XML (xs:float) 778 +|(% style="width:207px" %)Integer|(% style="width:462px" %)Integer|(% style="width:402px" %)Like XML (xs:int) 779 +|(% style="width:207px" %)Date|(% style="width:462px" %)DateTime|(% style="width:402px" %)YYYY-MM-DDT00:00:00Z 780 +|(% style="width:207px" %)Time|(% style="width:462px" %)StandardTimePeriod|(% style="width:402px" %)<date>/<date> (as defined above) 781 +|(% style="width:207px" %)time_period|(% style="width:462px" %)((( 861 861 ReportingTimePeriod 862 - 863 863 (StandardReportingPeriod) 864 -)))|((( 784 +)))|(% style="width:402px" %)((( 865 865 YYYY-Pppp 866 - 867 867 (according to SDMX ) 868 868 ))) 869 -|Duration|Duration|((( 788 +|(% style="width:207px" %)Duration|(% style="width:462px" %)Duration|(% style="width:402px" %)((( 870 870 Like XML (xs:duration) 871 - 872 872 PnYnMnDTnHnMnS 873 873 ))) 874 -|Boolean|Boolean|Like XML (xs:boolean) with the values "true" or "false" 792 +|(% style="width:207px" %)Boolean|(% style="width:462px" %)Boolean|(% style="width:402px" %)Like XML (xs:boolean) with the values "true" or "false" 875 875 876 -==== Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types ==== 794 +(% class="wikigeneratedid" id="HFigure142013MappingsfromSDMXdatatypestoVTLBasicScalarTypes-1" %) 795 +**Figure 14 – Mappings from SDMX data types to VTL Basic Scalar Types** 877 877 878 878 In case a different default conversion is desired, it can be achieved through the CustomTypeScheme and CustomType artefacts (see also the section Transformations and Expressions of the SDMX information model). 879 879 ... ... @@ -927,7 +927,7 @@ 927 927 |N|fixed number of digits used in the preceding textual representation of the month or the day 928 928 | | 929 929 930 -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 wikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallinkwikiinternallinkwikiinternallinkwikiinternallinkwikiinternallink wikiinternallinkwikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink wikiinternallink" %)^^42^^>>path:#sdfootnote42sym||name="sdfootnote42anc"]](%%)^^.849 +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{{footnote}}The representation given in the DSD should obviously be compatible with the VTL data type.{{/footnote}}. 931 931 932 932 === 12.4.5 Null Values === 933 933 ... ... @@ -945,10 +945,8 @@ 945 945 946 946 A different format can be specified in the attribute "vtlLiteralFormat" of the CustomType artefact (see also the section Transformations and Expressions of the SDMX information model). 947 947 948 -Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL 867 +Like in the case of the conversion of NULLs described in the previous paragraph, the overriding assumption is applied, for a certain VTL basic scalar type, if a value is found for the vtlLiteralFormat attribute of the CustomType of such VTL basic scalar type. The overriding assumption is applied for all the literals of a related VTL TransformationScheme. 949 949 950 -TransformationScheme. 951 - 952 952 In case a literal is operand of a VTL Cast operation, the format specified in the Cast overrides all the possible otherwise specified formats. 953 953 954 954 {{putFootnotes/}}