Skip to Content
Last modified by Artur K. on 2026/05/29 14:28
From version 1.21
edited by Helena K.
on 2026/01/15 13:01
Change comment: There is no comment for this version
To version 1.11
edited by Helena K.
on 2026/01/15 12:40
Change comment: There is no comment for this version

Summary

Details

Page properties
Content
... ... @@ -296,14 +296,15 @@
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  
... ... @@ -389,20 +389,19 @@
389 389  
390 390  **Table 9. Minimum requirements for DSDs~*~***
391 391  
392 -(% style="width:1308.83px" %)
393 -|(% style="width:205px" %)**Question**|(% style="width:272px" %)**Concept**|(% style="width:178px" %)**COG**|(% style="width:270px" %)**Code list**|(% style="width:290px" %)**Time series**|(% style="width:221px" %)**Cross-section**
394 -|(% style="width:205px" %)Where?|(% style="width:272px" %)reference area|(% style="width:178px" %)X|(% style="width:270px" %)revision|(% colspan="2" rowspan="1" style="width:478px" %)mand. attribute or dimension
395 -|(% style="width:205px" %)What?|(% style="width:272px" %)“indicator”|(% style="width:178px" %)-|(% style="width:270px" %)domain|(% colspan="2" rowspan="1" style="width:478px" %)one or multiple dimensions
396 -|(% style="width:205px" %)How?|(% style="width:272px" %)unit of measure|(% style="width:178px" %)X|(% style="width:270px" %)development|(% colspan="2" rowspan="1" style="width:478px" %)mand. attribute or dimension
397 -|(% style="width:205px" %)How?|(% style="width:272px" %)unit multiplier|(% style="width:178px" %)X|(% style="width:270px" %)available|(% colspan="2" rowspan="1" style="width:478px" %)mandatory attribute
398 -|(% style="width:205px" %)How?|(% style="width:272px" %)decimals|(% style="width:178px" %)X|(% style="width:270px" %)available|(% colspan="2" rowspan="1" style="width:478px" %)mandatory attribute
399 -|(% style="width:205px" %)How?|(% style="width:272px" %)//adjustment//|(% style="width:178px" %)X|(% style="width:270px" %)development|(% style="width:290px" %)mand. att.|(% style="width:221px" %) not relevant
400 -|(% style="width:205px" %)When?|(% style="width:272px" %)time period|(% style="width:178px" %)X|(% style="width:270px" %)format|(% style="width:290px" %)dimension|(% style="width:221px" %)mand. att.
401 -|(% style="width:205px" %)When?|(% style="width:272px" %)time format|(% style="width:178px" %)X|(% style="width:270px" %)available|(% colspan="2" rowspan="1" style="width:478px" %)mandatory attribute
402 -|(% style="width:205px" %)When?|(% style="width:272px" %)time period – collection|(% style="width:178px" %)X|(% style="width:270px" %)development|(% style="width:290px" %)mand. att.|(% style="width:221px" %)cond. att.
403 -|(% style="width:205px" %)When?|(% style="width:272px" %)data update – last update|(% style="width:178px" %)X|(% style="width:270px" %)time stamp|(% colspan="2" rowspan="1" style="width:478px" %)mandatory attribute
404 -|(% style="width:205px" %)How often?|(% style="width:272px" %)//frequency//|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:290px" %)mand. att. or|(% style="width:221px" %)not relevant
405 -|(% style="width:205px" %)How much?|(% style="width:272px" %)observation value|(% style="width:178px" %)-|(% style="width:270px" %)numeric|(% colspan="2" rowspan="1" style="width:290px" %) 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
406 406  
407 407  ~*~*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.
408 408  
... ... @@ -410,19 +410,25 @@
410 410  
411 411  **Table 10. Suggested additional concepts for certain scenarios~*~***
412 412  
413 -|**Question**|**Concept**|**COG**|**Code list**|**TS**|**CS**|**Scenario**
430 +|**Question**|**Concept**|**COG**|**Code list**|**TS CS**|**Scenario**
414 414  |Who?|compiling agency|X|development|(((
415 -conditional (sibling)
416 -)))|conditional (obs. level)|data provider different from data compiler
432 +conditional conditional
433 +
434 + (sibling) (obs. level)
435 +)))|data provider different from data compiler
417 417  |Who?|(((
418 -confidentiality status – observation
419 -)))|X|available|(% colspan="2" rowspan="1" %)mandatory (obs. level)|except dissemination
420 -|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
421 421  |How much?|(((
422 -//observation pre-break value//
423 -)))|-|numeric|cond. (obs.)|not relevant|except orig. collection
424 -|What and how?|//time series title//|X|text|cond. (TS)|not relevant|dissemination
443 +//observation pre-//
425 425  
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 +
426 426  ~** 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.
427 427  
428 428  == 5.2 Attribute attachment levels and definition of groups ==
... ... @@ -444,8 +444,10 @@
444 444  * //ID//: a unique identifier of the message
445 445  * //Test//: a Boolean attribute that indicates whether the message is for test purposes or not
446 446  * //Prepared//: the date the message was prepared
447 -* //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
448 448  
472 +(recommended: code from the agency code list in the SDMX COG)
473 +
449 449  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.
450 450  
451 451  = 6 STEP-BY-STEP GUIDE =
... ... @@ -456,15 +456,13 @@
456 456  
457 457  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).
458 458  
459 -(% class="wikigeneratedid" %)
460 -[[image:1768470533088-795.png]]
461 461  
462 462  (% class="wikigeneratedid" id="HFigure1.OverviewoftheDSDdesignprocess" %)
463 463  Figure 1. Overview of the DSD design process
464 464  
488 +
465 465  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.).
466 466  
467 -[[image:1768470575978-226.png]]
468 468  
469 469  (% class="wikigeneratedid" id="HFigure2.Characteristicsofdataexchangecontext" %)
470 470  Figure 2. Characteristics of data exchange context
... ... @@ -471,23 +471,20 @@
471 471  
472 472  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.
473 473  
474 -(% class="wikigeneratedid" %)
475 -[[image:1768470596130-305.png]]
476 476  
477 477  (% class="wikigeneratedid" id="HFigure3.PriorityrankingofexistingDSDsforreuse" %)
478 478  Figure 3. Priority ranking of existing DSDs for reuse
479 479  
501 +
480 480  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.
481 481  
482 -(% class="wikigeneratedid" %)
483 -[[image:1768470626558-321.png]]
484 484  
485 485  (% class="wikigeneratedid" id="HFigure4.AspectsofDSDsuitability" %)
486 486  Figure 4. Aspects of DSD suitability
487 487  
508 +
488 488  Figure 5 lists the most relevant artefacts required in addition to a DSD, its concept scheme, and code lists.
489 489  
490 -[[image:1768470646456-652.png]]
491 491  
492 492  Figure 5. Supporting artefacts
493 493  
... ... @@ -495,83 +495,48 @@
495 495  
496 496  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.
497 497  
498 -[[image:1768470678965-391.png]]
518 +**Figure 6. DSD modification scenarios**
499 499  
500 -Figure 6. DSD modification scenarios
501 -
502 502  == 6.3 Defining new DSDs ==
503 503  
504 504  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.
505 505  
506 -(% class="wikigeneratedid" %)
507 -[[image:1768470705894-724.png]]
524 +==== Figure 7. New DSD specification process ====
508 508  
509 -(% class="wikigeneratedid" id="HFigure7.NewDSDspecificationprocess" %)
510 -Figure 7. New DSD specification process
511 -
512 512  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.
513 513  
514 -(% class="wikigeneratedid" %)
515 -[[image:1768470729899-225.png]]
528 +==== Figure 8. Concept specification process ====
516 516  
517 -(% class="wikigeneratedid" id="HFigure8.Conceptspecificationprocess" %)
518 -Figure 8. Concept specification process
519 -
520 520  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.
521 521  
522 -(% class="wikigeneratedid" %)
523 -[[image:1768470752201-691.png]]
532 +==== Figure 9. DSD design options ====
524 524  
525 -(% class="wikigeneratedid" id="HFigure9.DSDdesignoptions" %)
526 -Figure 9. DSD design options
527 -
528 528  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.
529 529  
530 -(% class="wikigeneratedid" %)
531 -[[image:1768470775109-874.png]]
536 +==== Figure 10. Potential sources of concepts and definitions ====
532 532  
533 -(% class="wikigeneratedid" id="HFigure10.Potentialsourcesofconceptsanddefinitions" %)
534 -Figure 10. Potential sources of concepts and definitions
535 -
536 536  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.
537 537  
538 538  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.
539 539  
540 -[[image:1768470796725-270.png]]
541 541  
542 -(% class="wikigeneratedid" %)
543 -Figure 11. Possible concept roles
544 -
545 -(% class="wikigeneratedid" %)
546 -[[image:1768470829131-599.png]]
547 -
548 -(% class="wikigeneratedid" %)
549 -Figure 12. Possible attribute attachment levels
550 -
551 -(% class="wikigeneratedid" %)
552 -[[image:1768470860119-204.png]]
553 -
554 554  (% class="wikigeneratedid" id="HFigure13.Codelistspecificationprocess" %)
555 555  Figure 13. Code list specification process
556 556  
557 -(% class="wikigeneratedid" %)
546 +
558 558  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.
559 559  
560 -[[image:1768470878394-873.png]]
561 561  
562 562  (% class="wikigeneratedid" id="HFigure14.Priorityrankingofexistingcodelistsforreuse" %)
563 563  Figure 14. Priority ranking of existing code lists for reuse
564 564  
565 -(% class="wikigeneratedid" %)
553 +
566 566  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.
567 567  
568 -[[image:1768470896763-366.png]]
569 569  
570 570  (% class="wikigeneratedid" id="HFigure15.Aspectsofcodelistsuitability" %)
571 571  Figure 15. Aspects of code list suitability
572 572  
573 -(% class="wikigeneratedid" %)
574 -[[image:1768470911321-123.png]]
575 575  
576 576  (% class="wikigeneratedid" id="HFigure16.Codelistmodificationscenarios" %)
577 577  Figure 16. Code list modification scenarios
... ... @@ -584,11 +584,8 @@
584 584  
585 585  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.
586 586  
587 -[[image:1768471052577-528.png]]
588 -
589 589  Figure 17. DSD design process
590 590  
591 -[[image:1768470939545-136.png]]
592 592  
593 593  Figure 18. Checklist for DSD design process
594 594  
1768470533088-795.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -48.6 KB
Content
1768470575978-226.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -95.8 KB
Content
1768470596130-305.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -44.4 KB
Content
1768470611326-907.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -51.5 KB
Content
1768470626558-321.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -51.5 KB
Content
1768470646456-652.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -32.7 KB
Content
1768470678965-391.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -117.9 KB
Content
1768470705894-724.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -23.9 KB
Content
1768470729899-225.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -66.5 KB
Content
1768470752201-691.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -38.0 KB
Content
1768470775109-874.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -36.5 KB
Content
1768470796725-270.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -30.7 KB
Content
1768470829131-599.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -30.8 KB
Content
1768470860119-204.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -37.9 KB
Content
1768470878394-873.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -49.7 KB
Content
1768470896763-366.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -29.9 KB
Content
1768470911321-123.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -49.2 KB
Content
1768470939545-136.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -143.4 KB
Content
1768471052577-528.png
Author
... ... @@ -1,1 +1,0 @@
1 -xwiki:XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -97.4 KB
Content
© Semantic R&D Group, 2026