Changes for page Guidelines for SDMX Data Structure Definitions

Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -325,12 +325,20 @@
325	325
326	326	**Table 7. Data structuring approaches by level of data exchange**
327	327
328		-|(% colspan="1" rowspan="2" %)**Level of data exchange**|(% colspan="4" rowspan="1" %)**Data structuring approach**
329		-|**one DSD**|(% colspan="2" %)**master + satellite DSDs**|**multiple, indep. DSDs**
	328	+|**Level of data exchange**|**Data structuring approa one DSD**|(% colspan="2" %)(((
	329	+**ch**
	330	+
	331	+**master + satellite DSDs**
	332	+)))|**multiple, indep. DSDs**
330	330	|**within organization**|(((
331	331	best for single-domain, single-purpose can be created on the fly from structured databases
332	332	)))|(% colspan="2" %)use if harmonization is important in covered domains or purposes or if such a set of DSDs is already available at international level|easier to do than master + satellite approach each domain/purpose can maintain DSDs independently can be created on the fly from structured databases
333	333	|**between national organizations**|(% colspan="4" %)the same applies as to the “within organization” scenario
	337	+|**Level of data exchange**|(% colspan="3" %)(((
	338	+**Data structuring approach**
	339	+
	340	+**one DSD master + satellite DSDs**
	341	+)))|**multiple, indep. DSDs**
334	334	|**between int. organization and national organizations**|(% colspan="2" %)best for single domain, single purpose scenarios that are usually rather restricted with very clear specification of what needs to be exchanged|preferable over multiDSD approach in case of multi-domain and/or multi-purpose scenarios with highly correlated data flows for maintenance reasons|(((
335	335	for multi-domain and/or multipurpose scenarios; only recommended if overlap of domains/purposes is minor (e.g. just w.r.t. cross-domain concepts) equivalent to multiple “one DSD” solutions, one for each domain / purpose
336	336	)))
...	...	@@ -338,9 +338,11 @@
338	338	|**dissemination to public**|(% colspan="2" %)for single-domain, single-purpose cases in more complex cases this may be the preferable approach for data discovery tools (one data structure to find and access all data)|(% colspan="2" %)(((
339	339	in multi-purpose or –domain scenarios:
340	340
341		-* if it is relevant for the public to see the relationship between the data structures: use master + satellites approach
342		-* otherwise the multi-DSD option is preferable, although with the highest possible degree of re-use of code lists and concepts
343		-* in both cases: important to include only concepts, code lists, and codes actually available / used by the data
	349	+if it is relevant for the public to see the relationship between the data structures: use master + satellites approach
	350	+
	351	+otherwise the multi-DSD option is preferable, although with the highest possible degree of re-use of code lists and concepts
	352	+
	353	+in both cases: important to include only concepts, code lists, and codes actually available / used by the data
344	344	)))
345	345
346	346	In general, finding the “perfect” data structure is less important for bilateral data exchange. Independent, custom-tailored DSDs may do the job quite well, as harmonization and standardization are typically not of high importance. If the data exchange is just a part of a more comprehensive scenario (e.g. multi-purpose, multi-domain, gateway, or data-sharing scenarios), a master DSD with satellite DSDs is preferable.
...	...	@@ -349,17 +349,20 @@
349	349
350	350	**Table 8. Data structuring approaches by role in data exchange**
351	351
352		-|(% style="width:216px" %)**Role in data exchange**|(% style="width:1399px" %)**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
353		-|(% style="width:216px" %)**Data provider**|(% style="width:1399px" %)It is easier to set up a data submission process against a single DSD (= less initial costs) than against multiple DSDs.
354		-|(% style="width:216px" %)**Data collector**|(% style="width:1399px" %)(((
	362	+|**Role in data exchange**|**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
	363	+|**Data provider**|It is easier to set up a data submission process against a single DSD (= less initial costs) than against multiple DSDs.
	364	+|**Data collector**|(((
355	355	Data validation is easier with DSDs that only cover what needs to be collected. This is achieved via constraints in the master + satellites approach or via tailor-made independent DSDs. If a single DSD is used in a multi-domain or –purpose scenario, necessary constraints can be specified in the data flow definition or data provision agreement.
	366	+
356	356	Further processing of collected data is more flexible and easier if relations are transparent and code lists are shared as in the one DSD or master + satellite DSDs approaches. The “shared context” created through the master DSD increases harmonization and standardization and this way facilitates combined usage of data.
357	357	)))
358		-|(% style="width:216px" %)**DSD maintenance**|(% style="width:1399px" %)(((
	369	+|**Role in data exchange**|**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
	370	+|**DSD maintenance**|(((
359	359	The complexity and initial costs for developing and maintaining master + satellite DSDs are higher than for independent DSDs as this involves managing constraints and managing impacts of changes in shared code lists to all DSDs.
	372	+
360	360	In the multiple independent DSDs approach, development and maintenance efforts may be distributed. This can be seen as an advantage, but on the other hand requires coordination in case the DSDs are only partially independent (i.e. share some code lists).
361	361	)))
362		-|(% style="width:216px" %)**End user (“the public”)**|(% style="width:1399px" %)For data discovery and retrieval the user needs to know what data is actually available (instead of what might be collected/disseminated with a certain data structure). This means that the potential sparseness should be hidden from the user. A reduced DSD derived from the data structure used in the background is more useful in most cases. Whether this is done via one DSD and constraints, master + satellite DSDs, or independent DSDs does not matter that much for the user.
	375	+|**End user (“the public”)**|For data discovery and retrieval the user needs to know what data is actually available (instead of what might be collected/disseminated with a certain data structure). This means that the potential sparseness should be hidden from the user. A reduced DSD derived from the data structure used in the background is more useful in most cases. Whether this is done via one DSD and constraints, master + satellite DSDs, or independent DSDs does not matter that much for the user.
363	363
364	364	= 5 MINIMUM STRUCTURAL AND SEMANTIC REQUIREMENTS =
365	365
...	...	@@ -389,19 +389,19 @@
389	389
390	390	**Table 9. Minimum requirements for DSDs~*~***
391	391
392		-|(% style="width:205px" %)**Question**|(% style="width:272px" %)**Concept**|(% style="width:178px" %)**COG**|(% style="width:270px" %)**Code list**|(% style="width:690px" %)**Time series Cross-section**
393		-|(% style="width:205px" %)Where?|(% style="width:272px" %)reference area|(% style="width:178px" %)X|(% style="width:270px" %)revision|(% style="width:690px" %)mand. attribute or dimension
394		-|(% style="width:205px" %)What?|(% style="width:272px" %)“indicator”|(% style="width:178px" %)-|(% style="width:270px" %)domain|(% style="width:690px" %)one or multiple dimensions
395		-|(% style="width:205px" %)How?|(% style="width:272px" %)unit of measure|(% style="width:178px" %)X|(% style="width:270px" %)development|(% style="width:690px" %)mand. attribute or dimension
396		-|(% style="width:205px" %)How?|(% style="width:272px" %)unit multiplier|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:690px" %)mandatory attribute
397		-|(% style="width:205px" %)How?|(% style="width:272px" %)decimals|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:690px" %)mandatory attribute
398		-|(% style="width:205px" %)How?|(% style="width:272px" %)//adjustment//|(% style="width:178px" %)X|(% style="width:270px" %)development|(% style="width:690px" %)mand. att. not relevant
399		-|(% style="width:205px" %)When?|(% style="width:272px" %)time period|(% style="width:178px" %)X|(% style="width:270px" %)format|(% style="width:690px" %)dimension mand. att.
400		-|(% style="width:205px" %)When?|(% style="width:272px" %)time format|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:690px" %)mandatory attribute
401		-|(% style="width:205px" %)When?|(% style="width:272px" %)time period – collection|(% style="width:178px" %)X|(% style="width:270px" %)development|(% style="width:690px" %)mand. att. cond. att.
402		-|(% style="width:205px" %)When?|(% style="width:272px" %)data update – last update|(% style="width:178px" %)X|(% style="width:270px" %)time stamp|(% style="width:690px" %)mandatory attribute
403		-|(% style="width:205px" %)How often?|(% style="width:272px" %)//frequency//|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:690px" %)mand. att. or not relevant
404		-|(% colspan="2" style="width:477px" %)How much? observation value|(% style="width:178px" %)-|(% style="width:270px" %)numeric|(% style="width:690px" %)dimension measure
	405	+|**Question**|**Concept**|**COG**|**Code list**|**Time series Cross-section**
	406	+|Where?|reference area|X|revision|mand. attribute or dimension
	407	+|What?|“indicator”|-|domain|one or multiple dimensions
	408	+|How?|unit of measure|X|development|mand. attribute or dimension
	409	+|How?|unit multiplier|X|available|mandatory attribute
	410	+|How?|decimals|X|available|mandatory attribute
	411	+|How?|//adjustment//|X|development|mand. att. not relevant
	412	+|When?|time period|X|format|dimension mand. att.
	413	+|When?|time format|X|available|mandatory attribute
	414	+|When?|time period – collection|X|development|mand. att. cond. att.
	415	+|When?|data update – last update|X|time stamp|mandatory attribute
	416	+|How often?|//frequency//|X|available|mand. att. or not relevant
	417	+|(% colspan="2" %)How much? observation value|-|numeric|dimension measure
405	405
406	406	~*~*Concepts in //italics// are only relevant for time series DSDs. An “X” in the COG column means the concept is defined in the COG. Code list “development” means that the SWG will develop a code list to be recommended in the COG; “revision” means that the code list is recommended by the COG and under revision by the SWG; “format” means that a format is defined by another concept; “text”, “time stamp”, and “numeric” provide data types used for uncoded concepts.
407	407
...	...	@@ -409,19 +409,25 @@
409	409
410	410	**Table 10. Suggested additional concepts for certain scenarios~*~***
411	411
412		-|**Question**|**Concept**|**COG**|**Code list**|**TS**|**CS**|**Scenario**
	425	+|**Question**|**Concept**|**COG**|**Code list**|**TS CS**|**Scenario**
413	413	|Who?|compiling agency|X|development|(((
414		-conditional (sibling)
415		-)))|conditional (obs. level)|data provider different from data compiler
	427	+conditional conditional
	428	+
	429	+ (sibling) (obs. level)
	430	+)))|data provider different from data compiler
416	416	|Who?|(((
417		-confidentiality status – observation
418		-)))|X|available|(% colspan="2" rowspan="1" %)mandatory (obs. level)|except dissemination
419		-|How?|observation status|X|available|(% colspan="2" rowspan="1" %)conditional (obs. level)|except orig. collection
	432	+confidentiality
	433	+
	434	+status – observation
	435	+)))|X|available|mandatory (obs. level)|except dissemination
	436	+|How?|observation status|X|available|conditional (obs. level)|except orig. collection
420	420	|How much?|(((
421		-//observation pre-break value//
422		-)))|-|numeric|cond. (obs.)|not relevant|except orig. collection
423		-|What and how?|//time series title//|X|text|cond. (TS)|not relevant|dissemination
	438	+//observation pre-//
424	424
	440	+//break value//
	441	+)))|-|numeric|cond. (obs.) not relevant|except orig. collection
	442	+|What and how?|//time series title//|X|text|cond. (TS) not relevant|dissemination
	443	+
425	425	~** The legend of Table 9 applies to Table 10 as well. The suggested attachment level of attributes (if any) is provided in parentheses in the TS (time series) or CS (cross-section) columns. In case an attribute does not vary at that level in a certain use case, it should be attached at the highest possible level.
426	426
427	427	== 5.2 Attribute attachment levels and definition of groups ==