Difference between revisions of "Series Key"
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A Series Key is the cross product of values of Dimensions uniquely identifying a series within a dataset. | A Series Key is the cross product of values of Dimensions uniquely identifying a series within a dataset. | ||
| − | + | =Overview= | |
| − | + | Consider the following Data Structure Definition: | |
| − | |||
| − | Consider | ||
{| class="wikitable" | {| class="wikitable" | ||
|- | |- | ||
| Line 24: | Line 23: | ||
| n/a || Primary Measure || Observation Value || The observation value | | n/a || Primary Measure || Observation Value || The observation value | ||
|} | |} | ||
| − | In SDMX, Series Keys are written by concatenating the Dimension values with dots (.) in the order specified in the DSD. | + | In SDMX, Series Keys are generally written by concatenating the Dimension values with dots (.) in the order specified in the DSD. |
For the DSD above, the Series Key is constructed as follows: | For the DSD above, the Series Key is constructed as follows: | ||
| Line 37: | Line 36: | ||
Attributes do not form part of the Series Key because they have no role in uniquely identifying series or observations. | Attributes do not form part of the Series Key because they have no role in uniquely identifying series or observations. | ||
| + | |||
| + | In some implementations, Series Keys use a colon (:) separator: | ||
| + | Q:S:L:A:TO1:A:5J:A:5A:U:5R:N | ||
| + | Q:S:L:A:TO1:A:5J:A:5A:U:5C:N | ||
| + | Q:S:L:A:TO1:A:5J:A:5A:U:1N:N | ||
| + | Q:S:L:A:TO1:A:5J:A:5A:U:3C:N | ||
| + | Q:S:L:A:TO1:A:5J:A:5A:U:1C:N | ||
| + | |||
| + | =Series Keys with time value= | ||
| + | A Series Key that also includes a time value uniquely identifies an observation. | ||
| + | 2015 2016 2017 2018 2019 2020 | ||
| + | ATMCO2.GRC.A 278 290 298 304 312 209 | ||
| + | TBSINDC.MDG.A 631 678 645 655 662 669 | ||
| + | |||
| + | In the above example ATMCO2.GRC.A.2015 identifies the 2015 time period with observation value 278. | ||
Latest revision as of 06:38, 25 August 2022
A Series Key is the cross product of values of Dimensions uniquely identifying a series within a dataset.
Overview
Consider the following Data Structure Definition:
| Position | Component Type | Component ID | Description |
|---|---|---|---|
| 1 | Dimension | INDICATOR | Indicator |
| 2 | Dimension | REF_AREA | Reference Area |
| 3 | Dimension | FREQUENCY | Data Frequency |
| n/a | Time Dimension | TIME_PERIOD | Observation Time |
| n/a | Attribute | UNIT_MULT | Unit Multiplier e.g. tens, thousands, millions |
| n/a | Attribute | Observation Status | Observation Status e.g. Estimated, Final |
| n/a | Primary Measure | Observation Value | The observation value |
In SDMX, Series Keys are generally written by concatenating the Dimension values with dots (.) in the order specified in the DSD.
For the DSD above, the Series Key is constructed as follows:
<INDICATOR>.<REF_AREA>.<FREQUENCY>
Examples
ATMCO2.GRC.A ATMCO2.GRC.M TBSINDC.MDG.A TBSINDC.GBR.M
Attributes do not form part of the Series Key because they have no role in uniquely identifying series or observations.
In some implementations, Series Keys use a colon (:) separator:
Q:S:L:A:TO1:A:5J:A:5A:U:5R:N Q:S:L:A:TO1:A:5J:A:5A:U:5C:N Q:S:L:A:TO1:A:5J:A:5A:U:1N:N Q:S:L:A:TO1:A:5J:A:5A:U:3C:N Q:S:L:A:TO1:A:5J:A:5A:U:1C:N
Series Keys with time value
A Series Key that also includes a time value uniquely identifies an observation.
2015 2016 2017 2018 2019 2020 ATMCO2.GRC.A 278 290 298 304 312 209 TBSINDC.MDG.A 631 678 645 655 662 669
In the above example ATMCO2.GRC.A.2015 identifies the 2015 time period with observation value 278.
