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296 296  
297 297  **Table 6. Data structuring approaches by role in data exchange**
298 298  
299 -|(% style="width:215px" %)**Role in data exchange**|(% style="width:1400px" %)**Pure vs. composite concepts approach**
300 -|(% style="width:215px" %)**Data provider**|(% style="width:1400px" %)(((
299 +|**Role in data exchange**|**Pure vs. composite concepts approach**
300 +|**Data provider**|(((
301 301  If the composition of the concepts in the data provider's production system largely differs from the one in the DSD, mapping it to a few composite concepts may be more complex than mapping it to many pure concepts. (Mapping to just one mixed concept is straightforward, though.) This is due to the need to decompose and recombine concepts in case of a “mixed concepts” DSD. If the data provider’s internal data structure is very granular or very similar to the DSD, it does not make a huge difference if the concepts in that DSD are pure or not.
302 +
302 302  For a “final” data provider disseminating data to the public, the flexibility offered by a pure data structure in terms of defining different output formats may be beneficial.
303 303  )))
304 -|(% style="width:215px" %)**Data collector**|(% style="width:1400px" %)Defining constraints for data validation is more complex for a highdimensional, pure DSD. But such a DSD provides more flexibility in terms of consumption and reuse, i.e. mapping to the data collector’s internal data model mapping easier.
305 -|(% style="width:215px" %)**DSD maintenance**|(% style="width:1400px" %)Pure concepts usually have shorter, less complex code lists and are thus easier to maintain. In contrast, the maintenance of constraints, hierarchical code lists, and derived, composite concepts (e.g. for dissemination) requires more effort.
306 -|(% style="width:215px" %)**End user (“the public”)**|(% style="width:1400px" %)Consumption and reuse are more flexible in a pure data structure, but it is more difficult to identify observation keys that actually have data because of the created sparseness. (Constraints may help in this respect.) Frequent occurrences of “non applicable” values may also make data usage cumbersome.
305 +|**Data collector**|Defining constraints for data validation is more complex for a highdimensional, pure DSD. But such a DSD provides more flexibility in terms of consumption and reuse, i.e. mapping to the data collector’s internal data model mapping easier.
306 +|**DSD maintenance**|Pure concepts usually have shorter, less complex code lists and are thus easier to maintain. In contrast, the maintenance of constraints, hierarchical code lists, and derived, composite concepts (e.g. for dissemination) requires more effort.
307 +|**End user (“the public”)**|Consumption and reuse are more flexible in a pure data structure, but it is more difficult to identify observation keys that actually have data because of the created sparseness. (Constraints may help in this respect.) Frequent occurrences of “non applicable” values may also make data usage cumbersome.
307 307  
308 308  == 4.2 Number and relations of DSDs ==
309 309  
... ... @@ -325,22 +325,36 @@
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**
329 +|**Level of data exchange**|**Data structuring approa one DSD**|(% colspan="2" %)(((
330 +**ch**
331 +
332 +**master + satellite DSDs**
333 +)))|**multiple, indep. DSDs**
330 330  |**within organization**|(((
331 -best for single-domain, single-purpose can be created on the fly from structured databases
335 +best for single-domain, single-purpose can be created on the
336 +
337 +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
340 +|**Level of data exchange**|(% colspan="3" %)(((
341 +**Data structuring approach**
342 +
343 +**one DSD master + satellite DSDs**
344 +)))|**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 -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
346 +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)
347 +
348 +equivalent to multiple “one DSD” solutions, one for each domain / purpose
336 336  )))
337 337  |**between international organizations**|(% colspan="3" %)comparable to “national to international” scenario|
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
354 +if it is relevant for the public to see the relationship between the data structures: use master + satellites approach
355 +
356 +otherwise the multi-DSD option is preferable, although with the highest possible degree of re-use of code lists and concepts
357 +
358 +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" %)(((
367 +|**Role in data exchange**|**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
368 +|**Data provider**|It is easier to set up a data submission process against a single DSD (= less initial costs) than against multiple DSDs.
369 +|**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.
371 +
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" %)(((
374 +|**Role in data exchange**|**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
375 +|**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.
377 +
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.
380 +|**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
410 +|**Question**|**Concept**|**COG**|**Code list**|**Time series Cross-section**
411 +|Where?|reference area|X|revision|mand. attribute or dimension
412 +|What?|“indicator”|-|domain|one or multiple dimensions
413 +|How?|unit of measure|X|development|mand. attribute or dimension
414 +|How?|unit multiplier|X|available|mandatory attribute
415 +|How?|decimals|X|available|mandatory attribute
416 +|How?|//adjustment//|X|development|mand. att. not relevant
417 +|When?|time period|X|format|dimension mand. att.
418 +|When?|time format|X|available|mandatory attribute
419 +|When?|time period – collection|X|development|mand. att. cond. att.
420 +|When?|data update – last update|X|time stamp|mandatory attribute
421 +|How often?|//frequency//|X|available|mand. att. or not relevant
422 +|(% 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**
430 +|**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
432 +conditional conditional
433 +
434 + (sibling) (obs. level)
435 +)))|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
437 +confidentiality
438 +
439 +status – observation
440 +)))|X|available|mandatory (obs. level)|except dissemination
441 +|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
443 +//observation pre-//
424 424  
445 +//break value//
446 +)))|-|numeric|cond. (obs.) not relevant|except orig. collection
447 +|What and how?|//time series title//|X|text|cond. (TS) not relevant|dissemination
448 +
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 ==
... ... @@ -443,8 +443,10 @@
443 443  * //ID//: a unique identifier of the message
444 444  * //Test//: a Boolean attribute that indicates whether the message is for test purposes or not
445 445  * //Prepared//: the date the message was prepared
446 -* //Sender//: the identification of the organization that is transmitting the message (recommended: code from the agency code list in the SDMX COG)
470 +* //Sender//: the identification of the organization that is transmitting the message
447 447  
472 +(recommended: code from the agency code list in the SDMX COG)
473 +
448 448  From a business perspective, the inclusion of the //Name// element is highly recommended, as it can help to understand the purpose of the exchange message. Other header elements such as //Receiver// are optional.
449 449  
450 450  = 6 STEP-BY-STEP GUIDE =
... ... @@ -455,15 +455,13 @@
455 455  
456 456  Figure 1 provides an overview of the overall process. As a first step, the context of the data exchange(s) that should be covered by the DSD(s) is defined in terms of purpose, domains, level of exchange, type of data, type of recipient, role of in data exchange, process pattern, and GSBPM phase (see Figure 2). Since reusing existing artefacts is one of the guiding principles, the second step identifies existing DSDs that may be reused (see Figure 3). In case relevant DSDs are available, their suitability in the present context is evaluated in step 3. Aspects to be taken into account are concept coverage, concept roles, attribute attachment levels, and code lists (see Figure 4). Step 4 is subject to the outcome of step 3. In case of a favorable assessment, the DSDs are simply reused. If the DSDs are partly suitable, modified versions can be derived. See section 2. for a summary of possible DSD modification scenarios. If the DSDs are not suitable or if no relevant DSDs are available at all, new DSDs will be defined as described in section 3. Finally, supporting artefacts such as data flow definitions and data provision agreements are defined (see Figure 5).
457 457  
458 -(% class="wikigeneratedid" %)
459 -[[image:1768470533088-795.png]]
460 460  
461 461  (% class="wikigeneratedid" id="HFigure1.OverviewoftheDSDdesignprocess" %)
462 462  Figure 1. Overview of the DSD design process
463 463  
488 +
464 464  Figure 2 summarizes the characteristics of the data exchange context that is defined in step 1. These characteristics affect the decision on the data structuring approach that is part of the process of defining the concepts of a new DSD (step 4.3. in Figure 1; see Figure 7 in section 2.).
465 465  
466 -[[image:1768470575978-226.png]]
467 467  
468 468  (% class="wikigeneratedid" id="HFigure2.Characteristicsofdataexchangecontext" %)
469 469  Figure 2. Characteristics of data exchange context
... ... @@ -470,23 +470,20 @@
470 470  
471 471  Figure 3 recaps the priorities given to different types of existing DSDs when searching for candidates for reuse in step 2. Global DSDs maintained by the SDMX consortium are ranked the highest. They can be found via the Global SDMX Registry.
472 472  
473 -(% class="wikigeneratedid" %)
474 -[[image:1768470596130-305.png]]
475 475  
476 476  (% class="wikigeneratedid" id="HFigure3.PriorityrankingofexistingDSDsforreuse" %)
477 477  Figure 3. Priority ranking of existing DSDs for reuse
478 478  
501 +
479 479  Figure 4 summarizes the aspects to be considered in the assessment of the suitability of existing DSDs in step 3. For a detailed description of the cases of partial unsuitability see section 2.1. above.
480 480  
481 -(% class="wikigeneratedid" %)
482 -[[image:1768470626558-321.png]]
483 483  
484 484  (% class="wikigeneratedid" id="HFigure4.AspectsofDSDsuitability" %)
485 485  Figure 4. Aspects of DSD suitability
486 486  
508 +
487 487  Figure 5 lists the most relevant artefacts required in addition to a DSD, its concept scheme, and code lists.
488 488  
489 -[[image:1768470646456-652.png]]
490 490  
491 491  Figure 5. Supporting artefacts
492 492  
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