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296 296  
297 297  **Table 6. Data structuring approaches by role in data exchange**
298 298  
299 -|**Role in data exchange**|**Pure vs. composite concepts approach**
300 -|**Data provider**|(((
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" %)(((
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 -
303 303  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.
304 304  )))
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.
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.
308 308  
309 309  == 4.2 Number and relations of DSDs ==
310 310  
... ... @@ -326,36 +326,22 @@
326 326  
327 327  **Table 7. Data structuring approaches by level of data exchange**
328 328  
329 -|**Level of data exchange**|**Data structuring approa one DSD**|(% colspan="2" %)(((
330 -**ch**
331 -
332 -**master + satellite DSDs**
333 -)))|**multiple, indep. DSDs**
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**
334 334  |**within organization**|(((
335 -best for single-domain, single-purpose can be created on the
336 -
337 -fly from structured databases
331 +best for single-domain, single-purpose can be created on the fly from structured databases
338 338  )))|(% 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
339 339  |**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**
345 345  |**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|(((
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
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
349 349  )))
350 350  |**between international organizations**|(% colspan="3" %)comparable to “national to international” scenario|
351 351  |**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" %)(((
352 352  in multi-purpose or –domain scenarios:
353 353  
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
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
359 359  )))
360 360  
361 361  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.
... ... @@ -364,20 +364,17 @@
364 364  
365 365  **Table 8. Data structuring approaches by role in data exchange**
366 366  
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**|(((
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" %)(((
370 370  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 -
372 372  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.
373 373  )))
374 -|**Role in data exchange**|**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
375 -|**DSD maintenance**|(((
358 +|(% style="width:216px" %)**DSD maintenance**|(% style="width:1399px" %)(((
376 376  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 -
378 378  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).
379 379  )))
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.
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.
381 381  
382 382  = 5 MINIMUM STRUCTURAL AND SEMANTIC REQUIREMENTS =
383 383  
... ... @@ -407,19 +407,19 @@
407 407  
408 408  **Table 9. Minimum requirements for DSDs~*~***
409 409  
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
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
423 423  
424 424  ~*~*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.
425 425  
... ... @@ -427,25 +427,19 @@
427 427  
428 428  **Table 10. Suggested additional concepts for certain scenarios~*~***
429 429  
430 -|**Question**|**Concept**|**COG**|**Code list**|**TS CS**|**Scenario**
412 +|**Question**|**Concept**|**COG**|**Code list**|**TS**|**CS**|**Scenario**
431 431  |Who?|compiling agency|X|development|(((
432 -conditional conditional
433 -
434 - (sibling) (obs. level)
435 -)))|data provider different from data compiler
414 +conditional (sibling)
415 +)))|conditional (obs. level)|data provider different from data compiler
436 436  |Who?|(((
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
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
442 442  |How much?|(((
443 -//observation pre-//
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
444 444  
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 -
449 449  ~** 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.
450 450  
451 451  == 5.2 Attribute attachment levels and definition of groups ==
... ... @@ -467,10 +467,8 @@
467 467  * //ID//: a unique identifier of the message
468 468  * //Test//: a Boolean attribute that indicates whether the message is for test purposes or not
469 469  * //Prepared//: the date the message was prepared
470 -* //Sender//: the identification of the organization that is transmitting the message
446 +* //Sender//: the identification of the organization that is transmitting the message (recommended: code from the agency code list in the SDMX COG)
471 471  
472 -(recommended: code from the agency code list in the SDMX COG)
473 -
474 474  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.
475 475  
476 476  = 6 STEP-BY-STEP GUIDE =
... ... @@ -481,13 +481,15 @@
481 481  
482 482  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).
483 483  
458 +(% class="wikigeneratedid" %)
459 +[[image:1768470533088-795.png]]
484 484  
485 485  (% class="wikigeneratedid" id="HFigure1.OverviewoftheDSDdesignprocess" %)
486 486  Figure 1. Overview of the DSD design process
487 487  
488 -
489 489  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.).
490 490  
466 +[[image:1768470575978-226.png]]
491 491  
492 492  (% class="wikigeneratedid" id="HFigure2.Characteristicsofdataexchangecontext" %)
493 493  Figure 2. Characteristics of data exchange context
... ... @@ -494,20 +494,23 @@
494 494  
495 495  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.
496 496  
473 +(% class="wikigeneratedid" %)
474 +[[image:1768470596130-305.png]]
497 497  
498 498  (% class="wikigeneratedid" id="HFigure3.PriorityrankingofexistingDSDsforreuse" %)
499 499  Figure 3. Priority ranking of existing DSDs for reuse
500 500  
501 -
502 502  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.
503 503  
481 +(% class="wikigeneratedid" %)
482 +[[image:1768470626558-321.png]]
504 504  
505 505  (% class="wikigeneratedid" id="HFigure4.AspectsofDSDsuitability" %)
506 506  Figure 4. Aspects of DSD suitability
507 507  
508 -
509 509  Figure 5 lists the most relevant artefacts required in addition to a DSD, its concept scheme, and code lists.
510 510  
489 +[[image:1768470646456-652.png]]
511 511  
512 512  Figure 5. Supporting artefacts
513 513  
... ... @@ -515,48 +515,83 @@
515 515  
516 516  Figure 6 briefly recapitulates the actions that can be taken to overcome partial unsuitability of DSDs. As far as possible, existing artefacts should be reused in this case. This means that even if a DSD cannot be reused as a whole, concepts and code lists from that DSD can be included in the new DSD by reference.
517 517  
518 -**Figure 6. DSD modification scenarios**
497 +[[image:1768470678965-391.png]]
519 519  
499 +Figure 6. DSD modification scenarios
500 +
520 520  == 6.3 Defining new DSDs ==
521 521  
522 522  In case no (suitable) DSD is available, the actual process of specifying a new DSD is started. Figure 7 depicts this process (step 4.3. in Figure 1). It encompasses the specification of concepts, code lists, and data formats. All three specification steps include the identification of already existing artefacts that could be reused or modified to satisfy the requirements at hand and the definition of new artefacts in case no suitable artefacts are detected. Several iterations of steps 1 (specification of concepts; see Figure 8) and 2 (specification of code lists; see Figure°13) may be necessary, including revisions of the decision concerning the data structuring approach. Finally all artefacts defined in the previous steps are put together into a DSD.
523 523  
524 -==== Figure 7. New DSD specification process ====
505 +(% class="wikigeneratedid" %)
506 +[[image:1768470705894-724.png]]
525 525  
508 +(% class="wikigeneratedid" id="HFigure7.NewDSDspecificationprocess" %)
509 +Figure 7. New DSD specification process
510 +
526 526  Figure 8 outlines step 4.3.1, the process of concept specification. It covers the decision on the structuring approach, the identification of relevant concepts and the assessment of their suitability, the definition of new concepts, concept roles, and attribute attachment levels.
527 527  
528 -==== Figure 8. Concept specification process ====
513 +(% class="wikigeneratedid" %)
514 +[[image:1768470729899-225.png]]
529 529  
516 +(% class="wikigeneratedid" id="HFigure8.Conceptspecificationprocess" %)
517 +Figure 8. Concept specification process
518 +
530 530  Both, the decision on reuse of existing concepts as well as the definition of new ones, may lead back to a revision of the data structuring approach. For example, it could turn out that a certain concept needs to be broken down further which may lead from a “few composite dimensions” to a “many pure dimensions” approach. Figure 9 provides the design options involved in the decision on a data structuring approach. The options are defined in terms of the number of DSDs and the number of concepts (especially dimensions). The reasonability and feasibility of these options depend on the context of the present data exchange(s) as defined in the first step of the overall design process and on the content of the data exchange with respect to concepts.
531 531  
532 -==== Figure 9. DSD design options ====
521 +(% class="wikigeneratedid" %)
522 +[[image:1768470752201-691.png]]
533 533  
524 +(% class="wikigeneratedid" id="HFigure9.DSDdesignoptions" %)
525 +Figure 9. DSD design options
526 +
534 534  In the second step of new DSD design, relevant existing concepts are identified. Figure 10 indicates potential sources of those concepts such as the SDMX COG for cross-domain concepts, global or other DSDs as already identified earlier in the process, and domain standards such as the UN's System of National Accounts Manual 2008 for domain-specific concepts.
535 535  
536 -==== Figure 10. Potential sources of concepts and definitions ====
529 +(% class="wikigeneratedid" %)
530 +[[image:1768470775109-874.png]]
537 537  
532 +(% class="wikigeneratedid" id="HFigure10.Potentialsourcesofconceptsanddefinitions" %)
533 +Figure 10. Potential sources of concepts and definitions
534 +
538 538  The definition of new concepts (step 4.3.1.4.2.) is necessary if no (suitable) concept can be reused. It entails giving each concept a name, a code, and a definition. Further details about the usage of the concepts in the DSD are specified in steps 4.3.1.5. (concept roles), 4.3.1.6. (dimension groups), and 4.3.1.7. (attribute attachment levels). Figure 11 and 12 summarize the possible concept roles and attribute attachment levels.
539 539  
540 540  The second step in the process of defining a new DSD is the specification of code lists for all coded concepts. All dimensions must be coded (with time being an exception to this rule); attributes may be coded. For uncoded concepts, a data format has to be specified. Existing formats may be reused or new ones defined. An example is the time format that is specified in the SDMX COG. Figure 13 illustrates the code list specification process. If no relevant and suitable code list exists, a new one will be defined or a partially suitable one will be adapted (see Figure 16). Suitable code lists can simply be reused via reference.
541 541  
539 +[[image:1768470796725-270.png]]
542 542  
541 +(% class="wikigeneratedid" %)
542 +Figure 11. Possible concept roles
543 +
544 +(% class="wikigeneratedid" %)
545 +[[image:1768470829131-599.png]]
546 +
547 +(% class="wikigeneratedid" %)
548 +Figure 12. Possible attribute attachment levels
549 +
550 +(% class="wikigeneratedid" %)
551 +[[image:1768470860119-204.png]]
552 +
543 543  (% class="wikigeneratedid" id="HFigure13.Codelistspecificationprocess" %)
544 544  Figure 13. Code list specification process
545 545  
546 -
556 +(% class="wikigeneratedid" %)
547 547  Figure 14 recaps the priorities given to different types of existing code lists when searching for candidates for reuse (step 4.3.2.1.). Code lists recommended by the SDMX COG (and maintained by the SDMX consortium) are ranked the highest.
548 548  
559 +[[image:1768470878394-873.png]]
549 549  
550 550  (% class="wikigeneratedid" id="HFigure14.Priorityrankingofexistingcodelistsforreuse" %)
551 551  Figure 14. Priority ranking of existing code lists for reuse
552 552  
553 -
564 +(% class="wikigeneratedid" %)
554 554  Figure 15 summarizes the aspects to be considered in the evaluation of the suitability of existing code lists (step 4.3.2.2.). Figure 16 summarizes the scenarios of adapting existing code lists that do not fully meet the specified needs (step 4.3.2.3.2). For a detailed description of the cases of partial unsuitability see section 2.1. above.
555 555  
567 +[[image:1768470896763-366.png]]
556 556  
557 557  (% class="wikigeneratedid" id="HFigure15.Aspectsofcodelistsuitability" %)
558 558  Figure 15. Aspects of code list suitability
559 559  
572 +(% class="wikigeneratedid" %)
573 +[[image:1768470911321-123.png]]
560 560  
561 561  (% class="wikigeneratedid" id="HFigure16.Codelistmodificationscenarios" %)
562 562  Figure 16. Code list modification scenarios
... ... @@ -569,8 +569,10 @@
569 569  
570 570  Figure 17 provides an overview of all steps in the DSD design process as described in the previous subsections 1. to 3. Figure 18 compiles those steps into a checklist for DSD designers to help them make sure all aspects are considered.
571 571  
586 +
572 572  Figure 17. DSD design process
573 573  
589 +[[image:1768470939545-136.png]]
574 574  
575 575  Figure 18. Checklist for DSD design process
576 576  
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