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Changes for page 10 Constraints

Last modified by Artur on 2025/09/10 11:19
From version 1.1
edited by Helena
on 2025/06/16 12:03
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To version 1.3
edited by Helena
on 2025/06/16 12:11
Change comment: There is no comment for this version

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2 2  {{toc/}}
3 3  {{/box}}
4 4  
5 -1.
6 -11. Introduction
5 +== 10.1 Introduction ==
7 7  
8 8  Constraints are used as a way to restrict what data can be reported, or to report what data exists in a given context.  There are three types of Constraint, which serve different purposes
9 9  
... ... @@ -19,8 +19,7 @@
19 19  
20 20  A Reporting Constraint is used to define the set of allowed and/or disallowed values that can be reported in a data or metadata set.
21 21  
22 -1.
23 -11. Availability Constraint
21 +== 10.2 Availability Constraint ==
24 24  
25 25  An Availability Constraint is not a maintained structure, instead it is generated dynamically as a response to the availability REST API. The purpose of the Availability Constraint is to define the distinct set of values that have data over 1 or more Dimensions.  Unlike a Data and Metadata Constraint, which can attach to multiple Constrainable structures (of the same type), an Availability Constraint can only attach to only one structure.  The attachment defines the context of the response (data exists for components in the context of).  The subset of Constrainable structures the Availability Constraint can attach to are:
26 26  
... ... @@ -27,17 +27,18 @@
27 27  * Data Structure Definition
28 28  * Dataflow
29 29  * Provision Agreement
30 -*1. Dimension Constraint
31 31  
29 +== 10.3 Dimension Constraint ==
30 +
32 32  A Dimension Constraint is a property of a Dataflow; its purpose is to explicitly list the Dimensions from the corresponding DSD that are being used by the Dataflow. 
33 33  
34 -Dimension Constraints were introduced in SDMX 3.1 and are not required for most Dataflows where the dataset must always contain the full complement of Dimensions as defined by the corresponding DSD. However, for some complex data collections, which may span long periods and where the full complement of required Dimensions are not necessarily known at design time, the DSD is subject to increasing its Dimensionality over time.  In this scenario it is possible to define the DSD as an evolving structure, this property tells the user that the DSD can have new Dimensions added without having to undergo a major version change; a DSD at version 1.0.0 for example would be able to add a new Dimension and move to version 1.1.0; a change that would not ordinarily be allowed.  A minor version change on the addition of a new Dimension is only possible if the DSD defines itself as an evolving structure.   This is a new property of the DSD introduced in version 3.1 to satisfy this use case.  The evolving structure  property is either true or false, defaulting to false if not specified.  Setting the evolving structure property to true requires a major version change, and therefore can only be introduced on an x.0.0 release (e.g. 1.0.0).  The evolving structure property can be set to false to indicate that there will be no additional Dimensions added to the Data Structure under the same major version number; setting the evolving structure property to false does not require require a major version change on the Data Structure.  
33 +Dimension Constraints were introduced in SDMX 3.1 and are not required for most Dataflows where the dataset must always contain the full complement of Dimensions as defined by the corresponding DSD. However, for some complex data collections, which may span long periods and where the full complement of required Dimensions are not necessarily known at design time, the DSD is subject to increasing its Dimensionality over time.  In this scenario it is possible to define the DSD as an evolving structure, this property tells the user that the DSD can have new Dimensions added without having to undergo a major version change; a DSD at version 1.0.0 for example would be able to add a new Dimension and move to version 1.1.0; a change that would not ordinarily be allowed.  A minor version change on the addition of a new Dimension is only possible if the DSD defines itself as an evolving structure.   This is a new property of the DSD introduced in version 3.1 to satisfy this use case.  The evolving structure  property is either true or false, defaulting to false if not specified.  Setting the evolving structure property to true requires a major version change, and therefore can only be introduced on an x.0.0 release (e.g. 1.0.0).  The evolving structure property can be set to false to indicate that there will be no additional Dimensions added to the Data Structure under the same major version number; setting the evolving structure property to false does not require require a major version change on the Data Structure.   
35 35  
36 36  When a Dataflow references a DSD, late binding on the minor release, and the DSD has the evolving structure property set to true, then the Dataflow must contain a Dimension Constraint to protect its Dimensionality from changing over time without a version change. 
37 37  
38 38  The Dimension Constraint provides the explicit list of Dimensions that the Dataflow uses from the DSD that it references.  This enables the DSD to evolve over time without breaking the compatibility of datasets against the Dataflow. 
39 39  
40 -==== Rules for a Dimension Constraint ====
39 +__**Rules for a Dimension Constraint**__
41 41  
42 42  * A Dataflow must contain a Dimension Constraint if the DSD which it uses states that it is an evolving structure and the Dataflow is late binding on the minor release (latest minor release of a given major version, e.g. 1.0+.0)
43 43  * The Dimension Constraint can only include Dimensions from the DSD that is referenced by the Dataflow.
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46 46  * When exporting data for the Dataflow, the dataset should only include the Dimensions specified by the Dimension Constraint.
47 47  * When exporting data for the DSD the dataset must contain the full set of Dimensions as specified by the DSD. The tilde ‘~~’ character is used to represent a value which is not present due to the Dimension not being included in the corresponding Dataflow.
48 48  
49 -==== Example Datasets with Evolving Structures ====
48 +__**Example Datasets with Evolving Structures**__
50 50  
51 -A dataset is built against a Data Structure Definition.  The dataset contains data for two Dataflows.  Dataflows ‘DF_POP’ uses a Dimension Constraint which fixes its Dimensions to  FREQ and REF_AREA.  Dataflow ‘DF_POP_SA’ does not reference a
50 +A dataset is built against a Data Structure Definition.  The dataset contains data for two Dataflows.  Dataflows ‘DF_POP’ uses a Dimension Constraint which fixes its Dimensions to  FREQ and REF_AREA.  Dataflow ‘DF_POP_SA’ does not reference a Dimension Constraint, and as such includes all Dimensions as specified by the DSD.  
52 52  
53 -Dimension Constraint, and as such includes all Dimensions as specified by the DSD.  
54 -
55 55  The resulting dataset contains values ‘~~’ for both the SEX and AGE Dimension for the series related to DF_POP.
56 56  
54 +(% style="width:758.294px" %)
55 +|(% style="width:119px" %)**Dataflow**|(% colspan="7" style="width:635px" %)**FREQ REF_AREA SEX AGE OBS_VALUE TIME_PERIOD UNIT**
56 +|(% style="width:119px" %)**DF_POP**|(% style="width:55px" %)A|(% style="width:103px" %)UK|(% style="width:79px" %)~~|(% style="width:92px" %)~~|(% style="width:93px" %)65|(% style="width:111px" %)2022|(% style="width:101px" %)6
57 +|(% style="width:119px" %)**DF_POP**|(% style="width:55px" %)A|(% style="width:103px" %)FR|(% style="width:79px" %)~~|(% style="width:92px" %)~~|(% style="width:93px" %)50|(% style="width:111px" %)2022|(% style="width:101px" %)6
58 +|(% style="width:119px" %)**DF_POP_SA**|(% style="width:55px" %)A|(% style="width:103px" %)UK|(% style="width:79px" %)M|(% style="width:92px" %)1|(% style="width:93px" %)1.2|(% style="width:111px" %)2022|(% style="width:101px" %)6
57 57  
58 -|**Dataflow**|(% colspan="7" %)**FREQ REF_AREA SEX AGE OBS_VALUE TIME_PERIOD UNIT**
59 -|**DF_POP**|A|UK|~~|~~|65|2022|6
60 -|**DF_POP**|A|FR|~~|~~|50|2022|6
61 -|**DF_POP_SA**|A|UK|M|1|1.2|2022|6
60 +== 10.4 Reporting Constraints ==
62 62  
63 -1.
64 -11. Reporting Constraints
65 -
66 66  A Reporting Constraint is a Maintainable Artefact which restricts the values that can be reported in a dataset or metadata set based on one or more inclusion or exclusion rules. 
67 67  
68 68  A reporting constraint is one of the following concrete types:
... ... @@ -69,9 +69,9 @@
69 69  
70 70  * Data Constraint
71 71  * Metadata Constraint
72 -*1.
73 -*11. Data Constraint
74 74  
69 +=== 10.4.1 Data Constraint ===
70 +
75 75  A Data Constraint is used to add additional restrictions to the allowable values reported in a dataset.  Data Constraints can be applied to the follow structures which are collectively known as Constrainable structures:
76 76  
77 77  * Data Structure Definition
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81 81  
82 82  **Note** regardless of the Constrainable structure, the restricted values relate to  the allowable content for the Component of the DSD to which the constrained object relates. 
83 83  
84 -1.
85 -11.
86 -111. Metadata Constraint
80 +=== 10.4.2 Metadata Constraint ===
87 87  
88 88  A Metadata Constraint is used to add additional restrictions to the allowable values reported in a metadataset.  Metadata Constraints can be applied to the follow structures which are collectively known as Constrainable structures:
89 89  
... ... @@ -94,9 +94,7 @@
94 94  
95 95  **Note** regardless of the Constrainable structure,  the restricted values relate to  the allowable content for the Component of the MSD to which the constrained object relates. 
96 96  
97 -1.
98 -11.
99 -111. Scope of a Constraint
91 +=== 10.4.3 Scope of a Constraint ===
100 100  
101 101  A Constraint is used specify the content of a data or metadata source in terms of the component values or the keys.
102 102  
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132 132  
133 133  In view of the flexibility of constraints attachment, clear rules on their usage are required. These are elaborated below.
134 134  
135 -1.
136 -11.
137 -111. Multiple Constraints
127 +=== 10.4.4 Multiple Constraints ===
138 138  
139 139  There can be many Constraints for any Constrainable Artefact (e.g., DSD), subject to the following restrictions:
140 140  
141 -**10.4.4.1 Cube Region**
131 +==== 10.4.4.1 Cube Region ====
142 142  
143 143  A Constraint can contain multiple Member Selections (e.g., Dimensions).
144 144  
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148 148  * A Member Selection may include wildcarding of values (using character ‘%’ to represent zero or more occurrences of any character), as well as cascading through hierarchic structures (e.g., parents in Codelist), or localised values (e.g., text for English only). Lack of locale means any language may match. Cascading values are mutual exclusive to localised values, as the former refer to coded values, while the latter refer to uncoded values.
149 149  * Any values included in a Member Selection for Components with an array data type (i.e., Measures, Attributes or Metadata Attributes), will be applied as single values and will not be assessed combined with other values to match all possible array values. For example, including the Code ‘A’ for an Attribute will allow any instance of the Attribute that includes ‘A’, like [‘A’, ‘B’] or [‘A’, ‘C’, ‘D’]. Similarly, if Code ‘A’ was excluded, all those arrays of values would also be excluded.
150 150  
151 -**10.4.4.2 Key Set**
141 +==== 10.4.4.2 Key Set ====
152 152  
153 153  Key Sets will be processed in the order they appear in the Constraint and wildcards can be used (e.g., any key position not reference explicitly is deemed to be "all values").
154 154  
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158 158  
159 159  Finally, a validity period may be specified per Key.
160 160  
161 -1.
162 -11.
163 -111. Versioning
151 +=== 10.4.4 Versioning ===
164 164  
165 165  When Data and Metadata Constraints are versioned, the latest version of the Constraint is used to generate the reporting restriction rules; all previous versions are for historical information only.
166 166  
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184 184  
185 185  When both versions of the Data Constraint are in a system, an observation value reported against COUNTRY FR for time period 2013 would be deemed invalid as the 1.1.0 rule would be applied.
186 186  
187 -1.
188 -11.
189 -111. Inheritance
175 +=== 10.4.6 Inheritance ===
190 190  
191 -**10.4.6.1 Attachment levels of a Constraint**
177 +==== 10.4.6.1 Attachment levels of a Constraint ====
192 192  
193 193  There are three levels of constraint attachment for which these inheritance rules apply:
194 194  
195 -• DSD/MSD – top level o Dataflow/Metadataflow – second level
181 +* DSD/MSD – top level o Dataflow/Metadataflow – second level
182 +** Provision Agreement – third level
196 196  
197 -§ Provision Agreement – third level
198 -
199 199  It is not necessary for a Constraint to be attached to a higher level artefact. e.g., it is valid to have a Constraint for a Provision Agreement where there are no constraints attached the relevant Dataflow or DSD.
200 200  
201 -**10.4.6.2 Cascade rules for processing Constraints**
186 +==== 10.4.6.2 Cascade rules for processing Constraints ====
202 202  
203 203  The processing of the constraints on either Dataflow/Metadataflow or Provision Agreement must take into account the constraints declared at higher levels. The rules for the lower-level constraints (attached to Dataflow/ Metadataflow and Provision Agreement) are detailed below.
204 204  
205 205  Note that there can be a situation where a constraint is specified at a lower level before a constraint is specified at a higher level. Therefore, it is possible that a higher-level constraint makes a lower-level constraint invalid. SDMX makes no rules on how such a conflict should be handled when processing the constraint for attachment. However, the cascade rules on evaluating constraints for usage are clear – the higher-level constraint takes precedence in any conflicts that result in a less restrictive specification at the lower level.
206 206  
207 -**10.4.6.3 Cube Region**
192 +==== 10.4.6.3 Cube Region ====
208 208  
209 209  It is not necessary to have a Constraint on the higher-level artefact (e.g., DSD referenced by the Dataflow), but if there is such a Constraint at the higher level(s) then:
210 210  
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215 215  
216 216  Note that it is possible for a Constraint at a higher level to constrain, say, four Dimensions in a single Constraint, and a Constraint at a lower level to constrain the same four in two, three, or four Constraints.
217 217  
218 -**10.4.6.4 Key Set**
203 +==== 10.4.6.4 Key Set ====
219 219  
220 220  It is not necessary to have a Constraint on the higher-level artefact (e.g., DSD referenced by the Dataflow), but if there is such a Constraint at the higher level(s) then:
221 221  
... ... @@ -236,8 +236,10 @@
236 236  11. If there are keys in the lower-level Constraint that are not inherited then the key is invalid (i.e., it is less restrictive).
237 237  111. Constraints Examples
238 238  
239 -**10.4.7.1 Data Constraint and Cascading **The following scenario is used.
224 +==== 10.4.7.1 Data Constraint and Cascading ====
240 240  
226 +The following scenario is used.
227 +
241 241  A DSD contains the following Dimensions:
242 242  
243 243  * GEO – Geography
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280 280  * Restricts the codes for the GEO Dimension to IT and its children.
281 281  ** Inherits the constraints from Dataflow CENSUS_CUBE1 for the AGE and CAS Dimensions.
282 282  
283 -
284 -
285 285  Provision Agreement CENSUS_CUBE2_IT
286 286  
287 287  * Restricts the codes for the GEO Dimension to IT and its children.