Changes for page 12 Validation and Transformation Language (VTL)

Summary

• Page properties (1 modified, 0 added, 0 removed)
• Attachments (0 modified, 0 added, 1 removed)
  • 1750070288958-132.png

Details

Page properties

Content

...	...	@@ -410,14 +410,16 @@
410	410
411	411	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:
412	412
413		-> ‘DF1(1.0.0)/POPULATION.USA’ :=
414		-> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
415		->
416		-> ‘DF1(1.0.0)/POPULATION.CANADA’ :=
417		-> DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
418		->
419		-> … … …
	413	+‘DF1(1.0.0)/POPULATION.USA’ :=
420	420
	415	+DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
	416	+
	417	+‘DF1(1.0.0)/POPULATION.CANADA’ :=
	418	+
	419	+DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
	420	+
	421	+… … …
	422	+
421	421	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}}
422	422
423	423	In the direction from SDMX to VTL it is allowed to omit the value of one or more DimensionComponents 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.
...	...	@@ -426,9 +426,10 @@
426	426
427	427	This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
428	428
429		-> ‘DF1(1.0.0)/POPULATION.’ :=
430		-> DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
	431	+‘DF1(1.0.0)/POPULATION.’ :=
431	431
	433	+DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
	434	+
432	432	Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
433	433
434	434	Heterogeneous invocations of the same Dataflow are allowed, i.e. omitting different Dimensions in different invocations.
...	...	@@ -446,38 +446,41 @@
446	446
447	447	The corresponding VTL Transformations, assuming that the result needs to be persistent, would be of this kind:{{footnote}}the symbol of the VTL persistent assignment is used (<-){{/footnote}}
448	448
449		-> ‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
	452	+‘DF2(1.0.0)/INDICATORvalue.COUNTRYvalue’ <- expression
450	450
451	451	Some examples follow, for some specific values of INDICATOR and COUNTRY:
452	452
453		-> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
454		-> … … …
455		-> ‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
456		-> ‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
457		-> … … …
	456	+‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
	457	+… … …
458	458
	459	+‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
	460	+‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
	461	+… … …
	462	+
459	459	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:
460	460
461	461	VTL dataset   INDICATOR value COUNTRY value
462	462
463		-> ‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
464		-> ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
465		-> ‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
466		-> ‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
467		-> … … …
	467	+‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
	468	+‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
	469	+‘DF2(1.0.0)/POPGROWTH.USA’  POPGROWTH USA
	470	+‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
468	468
	472	+… … …
	473	+
469	469	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:
470	470
471		-> DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
472		-> DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
473		-> DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’  [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
474		-> DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
475		-> DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
476		-> DF2bis_GDPPERCAPITA_CANADA’,
477		-> … ,
478		-> DF2bis_POPGROWTH_USA’,
479		-> DF2bis_POPGROWTH_CANADA’
480		-> …);
	476	+DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
	477	+DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
	478	+DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
	479	+[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
	480	+DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
	481	+DF2(1.0) <- UNION  (DF2bis_GDPPERCAPITA_USA’,
	482	+DF2bis_GDPPERCAPITA_CANADA’,
	483	+… ,
	484	+DF2bis_POPGROWTH_USA’,
	485	+DF2bis_POPGROWTH_CANADA’
	486	+…);
481	481
482	482	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){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
483	483
...	...	@@ -489,26 +489,25 @@
489	489
490	490	With reference to the VTL “model for Variables and Value domains”, the following additional mappings have to be considered:
491	491
492		-(% style="width:706.294px" %)
493		-|(% style="width:257px" %)VTL|(% style="width:446px" %)SDMX
494		-|(% style="width:257px" %)**Data Set Component**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
495		-|(% style="width:257px" %)**Represented Variable**|(% style="width:446px" %)**Concept** with a definite Representation
496		-|(% style="width:257px" %)**Value Domain**|(% style="width:446px" %)(((
	498	+|VTL|SDMX
	499	+|**Data Set Component**|Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a Component (either a DimensionComponent or a Measure or a DataAttribute) belonging to one specific Dataflow^^43^^
	500	+|**Represented Variable**|**Concept** with a definite Representation
	501	+|**Value Domain**|(((
497	497	**Representation** (see the Structure
498	498	Pattern in the Base Package)
499	499	)))
500		-|(% style="width:257px" %)**Enumerated Value Domain / Code List**|(% style="width:446px" %)**Codelist**
501		-|(% style="width:257px" %)**Code**|(% style="width:446px" %)**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
502		-|(% style="width:257px" %)**Described Value Domain**|(% style="width:446px" %)(((
	505	+|**Enumerated Value Domain / Code List**|**Codelist**
	506	+|**Code**|**Code** (for enumerated DimensionComponent, Measure, DataAttribute)
	507	+|**Described Value Domain**|(((
503	503	non-enumerated** Representation**
504	504	(having Facets / ExtendedFacets, see the Structure Pattern in the Base Package)
505	505	)))
506		-|(% style="width:257px" %)**Value**|(% style="width:446px" %)Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
507		-|(% style="width:257px" %) |(% style="width:446px" %)to a valid **value **(for non-enumerated** **Representations)
508		-|(% style="width:257px" %)**Value Domain Subset / Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
509		-|(% style="width:257px" %)**Enumerated Value Domain Subset / Enumerated Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
510		-|(% style="width:257px" %)**Described Value Domain Subset / Described Set**|(% style="width:446px" %)This abstraction does not exist in SDMX
511		-|(% style="width:257px" %)**Set list**|(% style="width:446px" %)This abstraction does not exist in SDMX
	511	+|**Value**|Although this abstraction exists in SDMX, it does not have an explicit definition and correspond to a **Code** of a Codelist (for enumerated Representations) or
	512	+| |to a valid **value **(for non-enumerated** **Representations)
	513	+|**Value Domain Subset / Set**|This abstraction does not exist in SDMX
	514	+|**Enumerated Value Domain Subset / Enumerated Set**|This abstraction does not exist in SDMX
	515	+|**Described Value Domain Subset / Described Set**|This abstraction does not exist in SDMX
	516	+|**Set list**|This abstraction does not exist in SDMX
512	512
513	513	The main difference between VTL and SDMX relies on the fact that the VTL artefacts for defining subsets of Value Domains do not exist in SDMX, therefore the VTL features for referring to predefined subsets are not available in SDMX. These artefacts are the Value Domain Subset (or Set), either enumerated or described, the Set List (list of values belonging to enumerated subsets) and the Data Set Component (aimed at defining the set of values that the Component of a Data Set can take, possibly a subset of the codes of Value Domain).
514	514
...	...	@@ -516,10 +516,8 @@
516	516
517	517	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
518	518
519		-> DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets)
	524	+DS_c := DS_a + DS_b (where DS_a, DS_b, DS_c are VTL Data Sets) if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
520	520
521		-if the matching components in DS_a and DS_b (e.g. ref_date, geo_area, sector …) refer to the same general representation. In simpler words, DS_a and DS_b must use the same values/codes (for ref_date, geo_area, sector … ), otherwise the relevant values would not match and the result of the operation would be wrong.
522		-
523	523	As mentioned, the property above is not enforced by construction in SDMX, and different representations of the same Concept can be not compatible one another (for example, it may happen that geo_area is represented by ISO-alpha-3 codes in DS_a and by ISO alpha-2 codes in DS_b). Therefore, it will be up to the definer of VTL
524	524
525	525	Transformations to ensure that the VTL expressions are consistent with the actual representations of the correspondent SDMX Concepts.
...	...	@@ -534,9 +534,8 @@
534	534
535	535	The VTL data types are sub-divided in scalar types (like integers, strings, etc.), which are the types of the scalar values, and compound types (like Data Sets, Components, Rulesets, etc.), which are the types of the compound structures. See below the diagram of the VTL data types, taken from the VTL User Manual:
536	536
	540	+[[image:1750067055028-964.png]]
537	537
538		-[[image:1750070288958-132.png]]
539		-
540	540	**Figure 22 – VTL Data Types**
541	541
542	542	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.

1750070288958-132.png

Author

...	...	@@ -1,1 +1,0 @@
1		-xwiki:XWiki.helena

Size

...	...	@@ -1,1 +1,0 @@
1		-45.9 KB

Content