Changes for page Guidelines for SDMX Data Structure Definitions

Last modified by Artur K. on 2026/05/29 14:28

From 1.12 to 1.13 From 1.17 to 1.18

From version 1.13

edited by Helena K.
on 2026/01/15 12:41

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edited by Helena K.
on 2026/01/15 12:50

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@@ -325,20 +325,12 @@
  **Table 7. Data structuring approaches by level of data exchange**
--|**Level of data exchange**|**Data structuring approa one DSD**|(% colspan="2" %)(((
--**ch**
--
--**master + satellite DSDs**
--)))|**multiple, indep. DSDs**
++|(% colspan="1" rowspan="2" %)**Level of data exchange**|(% colspan="4" rowspan="1" %)**Data structuring approach**
++|**one DSD**|(% colspan="2" %)**master + satellite DSDs**|**multiple, indep. DSDs**
  |**within organization**|(((
  best for single-domain, single-purpose can be created on the fly from structured databases
  )))|(% 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
  |**between national organizations**|(% colspan="4" %)the same applies as to the “within organization” scenario
--|**Level of data exchange**|(% colspan="3" %)(((
--**Data structuring approach**
--
--**one DSD                        master + satellite DSDs**
--)))|**multiple, indep. DSDs**
  |**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|(((
  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
  )))
@@ -346,11 +346,9 @@
  |**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" %)(((
  in multi-purpose or –domain scenarios:
--if it is relevant for the public to see the relationship between the data structures: use master + satellites approach
--
--otherwise the multi-DSD option is preferable, although with the highest possible degree of re-use of code lists and concepts
--
--in both cases: important to include only concepts, code lists, and codes actually available / used by the data
++* if it is relevant for the public to see the relationship between the data structures: use master + satellites approach
++* otherwise the multi-DSD option is preferable, although with the highest possible degree of re-use of code lists and concepts
++* in both cases: important to include only concepts, code lists, and codes actually available / used by the data
  )))
  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.
@@ -359,20 +359,17 @@
  **Table 8. Data structuring approaches by role in data exchange**
--|**Role in data exchange**|**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
--|**Data provider**|It is easier to set up a data submission process against a single DSD (= less initial costs) than against multiple DSDs.
--|**Data collector**|(((
++|(% style="width:216px" %)**Role in data exchange**|(% style="width:1399px" %)**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
++|(% 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.
++|(% style="width:216px" %)**Data collector**|(% style="width:1399px" %)(((
  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.
--
  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.
  )))
--|**Role in data exchange**|**One DSD vs. master + satellite DSDs vs. multiple, indep. DSDs**
--|**DSD maintenance**|(((
++|(% style="width:216px" %)**DSD maintenance**|(% style="width:1399px" %)(((
  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.
--
  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).
  )))
--|**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.
++|(% 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.
  = 5 MINIMUM STRUCTURAL AND SEMANTIC REQUIREMENTS =
@@ -402,19 +402,19 @@
  **Table 9. Minimum requirements for DSDs~*~***
--|**Question**|**Concept**|**COG**|**Code list**|**Time series      Cross-section**
--|Where?|reference area|X|revision|mand. attribute or dimension
--|What?|“indicator”|-|domain|one or multiple dimensions
--|How?|unit of measure|X|development|mand. attribute or dimension
--|How?|unit multiplier|X|available|mandatory attribute
--|How?|decimals|X|available|mandatory attribute
--|How?|//adjustment//|X|development|mand. att.        not relevant
--|When?|time period|X|format|dimension       mand. att.
--|When?|time format|X|available|mandatory attribute
--|When?|time period – collection|X|development|mand. att.         cond. att.
--|When?|data update – last update|X|time stamp|mandatory attribute
--|How often?|//frequency//|X|available|mand. att. or    not relevant
--|(% colspan="2" %)How much? observation value|-|numeric|dimension measure
++|(% style="width:205px" %)**Question**|(% style="width:272px" %)**Concept**|(% style="width:178px" %)**COG**|(% style="width:270px" %)**Code list**|(% style="width:690px" %)**Time series      Cross-section**
++|(% style="width:205px" %)Where?|(% style="width:272px" %)reference area|(% style="width:178px" %)X|(% style="width:270px" %)revision|(% style="width:690px" %)mand. attribute or dimension
++|(% style="width:205px" %)What?|(% style="width:272px" %)“indicator”|(% style="width:178px" %)-|(% style="width:270px" %)domain|(% style="width:690px" %)one or multiple dimensions
++|(% 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
++|(% style="width:205px" %)How?|(% style="width:272px" %)unit multiplier|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:690px" %)mandatory attribute
++|(% style="width:205px" %)How?|(% style="width:272px" %)decimals|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:690px" %)mandatory attribute
++|(% style="width:205px" %)How?|(% style="width:272px" %)//adjustment//|(% style="width:178px" %)X|(% style="width:270px" %)development|(% style="width:690px" %)mand. att.        not relevant
++|(% style="width:205px" %)When?|(% style="width:272px" %)time period|(% style="width:178px" %)X|(% style="width:270px" %)format|(% style="width:690px" %)dimension       mand. att.
++|(% style="width:205px" %)When?|(% style="width:272px" %)time format|(% style="width:178px" %)X|(% style="width:270px" %)available|(% style="width:690px" %)mandatory attribute
++|(% 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.
++|(% 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
++|(% 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
++|(% colspan="2" style="width:477px" %)How much? observation value|(% style="width:178px" %)-|(% style="width:270px" %)numeric|(% style="width:690px" %)dimension measure
  ~*~*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.
@@ -422,25 +422,19 @@
  **Table 10. Suggested additional concepts for certain scenarios~*~***
--|**Question**|**Concept**|**COG**|**Code list**|**TS                  CS**|**Scenario**
++|**Question**|**Concept**|**COG**|**Code list**|**TS**|**CS**|**Scenario**
  |Who?|compiling agency|X|development|(((
--conditional          conditional
--
--    (sibling)          (obs. level)
--)))|data provider different from data compiler
++conditional (sibling)
++)))|conditional (obs. level)|data provider different from data compiler
  |Who?|(((
--confidentiality
--
--status – observation
--)))|X|available|mandatory (obs. level)|except dissemination
--|How?|observation status|X|available|conditional (obs. level)|except orig. collection
++confidentiality status – observation
++)))|X|available|(% colspan="2" rowspan="1" %)mandatory (obs. level)|except dissemination
++|How?|observation status|X|available|(% colspan="2" rowspan="1" %)conditional (obs. level)|except orig. collection
  |How much?|(((
--//observation pre-//
++//observation pre-break value//
++)))|-|numeric|cond. (obs.)|not relevant|except orig. collection
++|What and how?|//time series title//|X|text|cond. (TS)|not relevant|dissemination
--//break value//
--)))|-|numeric|cond. (obs.)      not relevant|except orig. collection
--|What and how?|//time series title//|X|text|cond. (TS)        not relevant|dissemination
--
  ~** 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.
  == 5.2 Attribute attachment levels and definition of groups ==
@@ -462,10 +462,8 @@
  * //ID//: a unique identifier of the message
  * //Test//: a Boolean attribute that indicates whether the message is for test purposes or not
  * //Prepared//: the date the message was prepared
--* //Sender//: the identification of the organization that is transmitting the message
++* //Sender//: the identification of the organization that is transmitting the message (recommended: code from the agency code list in the SDMX COG)
--(recommended: code from the agency code list in the SDMX COG)
--
  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.
  = 6 STEP-BY-STEP GUIDE =
@@ -476,13 +476,15 @@
  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).
++(% class="wikigeneratedid" %)
++[[image:1768470533088-795.png]]
  (% class="wikigeneratedid" id="HFigure1.OverviewoftheDSDdesignprocess" %)
  Figure 1. Overview of the DSD design process
--
  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.).
++[[image:1768470575978-226.png]]
  (% class="wikigeneratedid" id="HFigure2.Characteristicsofdataexchangecontext" %)
  Figure 2. Characteristics of data exchange context
@@ -489,20 +489,23 @@
  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.
++(% class="wikigeneratedid" %)
++[[image:1768470596130-305.png]]
  (% class="wikigeneratedid" id="HFigure3.PriorityrankingofexistingDSDsforreuse" %)
  Figure 3. Priority ranking of existing DSDs for reuse
--
  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.
++(% class="wikigeneratedid" %)
++[[image:1768470626558-321.png]]
  (% class="wikigeneratedid" id="HFigure4.AspectsofDSDsuitability" %)
  Figure 4. Aspects of DSD suitability
--
  Figure 5 lists the most relevant artefacts required in addition to a DSD, its concept scheme, and code lists.
++[[image:1768470646456-652.png]]
  Figure 5. Supporting artefacts

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