Data Structure Definition - Revision history

Vmurrell at 07:43, 6 October 2025

2025-10-06T07:43:58Z

2019-12-20T16:33:10Z

‎Multiple Measures

2019-12-20T16:32:21Z

‎Conventions

2019-12-20T16:26:23Z

‎Attribute Attachment Levels

2019-12-20T16:25:32Z

‎Attribute Attachment Levels

2019-12-20T16:24:56Z

2019-12-20T16:14:34Z

‎Non Time Series DSDs

2019-12-20T16:14:26Z

‎Time Series DSDs

2019-12-20T16:13:56Z

‎Conventions

2019-12-20T16:11:45Z

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+[[Category:RetiredFunctionality]]
 =Overview=
 <p>An SDMX Data Structure Definition (DSD) provides a template which describes the dimensionality of related datasets in terms of their dimensions, attributes and measures.</p>

@@ Line 144: / Line 144: @@
 </p>
-=Multiple Measures=
+=Data Structure Definitions with Multiple Measures=
 <p>
 </p>

@@ Line 41: / Line 41: @@
 <p>
 <strong>DSD IDs</strong><br>
-DSD IDs are conventionally written uppercase using underscores '_' as separators if required. Examples:<br>
+DSD IDs are conventionally uppercase using underscores '_' as separators if required. Examples:<br>
 {| class="wikitable"
 |-
@@ Line 54: / Line 54: @@
 | World Bank || WDI || World Development Indicators || [https://demo.metadatatechnology.com/FusionRegistry/ws/public/sdmxapi/rest/datastructure/WB/WDI/1.0 SDMX-ML]
 |}
 <strong>TIME_PERIOD</strong><br>
 For Time Series DSDs, the [[Time Dimension]] Component is conventionally given the ID 'TIME_PERIOD'.

@@ Line 128: / Line 128: @@
 | Group || A different value for the attribute can be set for a [[Group]] of series
 |}
-Example 'Demography' DSD with Attributes attached at the Series and Observation level:<br>
+Example 'Demography' DSD with Attributes attached at the Series and Observation level:<br><br>
 [[File:DSD With Attribute Attachments.PNG|500px]]
 </p>

@@ Line 129: / Line 129: @@
 |}
 Example 'Demography' DSD with Attributes attached at the Series and Observation level:<br>
-[[File:DSD With Attribute Attachments.PNG]]
+[[File:DSD With Attribute Attachments.PNG|500px]]
 </p>

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 <p>
 DSDs can be designed for non Time Series datasets by excluding the [[Time Dimension]]. This supports use cases like census statistics which, although the observations are from a fixed point in time, there's no sequence of observations over a period of time.
 </p>

@@ Line 138: / Line 138: @@
 </p>
-=Non Time Series DSDs=
+=Non Time Series=
 <p>
 DSDs can be designed for non Time Series datasets by excluding the [[Time Dimension]]. This supports use cases like census statistics which, although the observations are from a fixed point in time, there's no sequence of observations over a period of time.
 </p>

@@ Line 132: / Line 132: @@
 </p>
-=Time Series DSDs=
+=Time Series=
 <p>
 DSDs for Time Series are characterised by having an explicit [[Time Dimension]].<br>