Wiki source code of 13 Structure Mapping

Version 11.2 by Helena on 2025/05/16 12:43

version	line-number	content
10.2	1	{{box title="Contents"}}
	2	{{toc/}}
	3	{{/box}}
2.1	4
	5	== 13.1 Introduction ==
	6
	7	The purpose of SDMX structure mapping is to transform datasets from one dimensionality to another. In practice, this means that the input and output datasets conform to different Data Structure Definition.
	8
	9	Structure mapping does not alter the observation values and is not intended to perform any aggregations or calculations.
	10
	11	An input series maps to:
	12
	13	1. Exactly one output series; or
	14	1. Multiple output series with different Series Keys, but the same observation values; or
	15	1. Zero output series where no source rule matches the input Component values.
	16
	17	Typical use cases include:
	18
	19	* Transforming received data into a common internal structure;
	20	* Transforming reported data into the data collector's preferred structure;
10.3	21	* Transforming unidimensional datasets{{footnote}}Unidimensional datasets are those with a single 'indicator' or 'series code' dimension.{{/footnote}} to multi-dimensional; and
2.1	22	* Transforming internal datasets with a complex structure to a simpler structure with fewer dimensions suitable for dissemination.
	23
	24	== 13.2 1-1 structure maps ==
	25
	26	1-1 (pronounced 'one to one') mappings support the simple use case where the value of a Component in the source structure is translated to a different value in the target, usually where different classification schemes are used for the same Concept.
	27
	28	In the example below, ISO 2-character country codes are mapped to their ISO 3character equivalent.
	29
10.3	30	(% style="width:666.294px" %)
	31	\|(% style="width:217px" %)Country\|(% style="width:251px" %)Alpha-2 code\|(% style="width:195px" %)Alpha-3 code
	32	\|(% style="width:217px" %)Afghanistan\|(% style="width:251px" %)AF\|(% style="width:195px" %)AFG
	33	\|(% style="width:217px" %)Albania\|(% style="width:251px" %)AL\|(% style="width:195px" %)ALB
	34	\|(% style="width:217px" %)Algeria\|(% style="width:251px" %)DZ\|(% style="width:195px" %)DZA
	35	\|(% style="width:217px" %)American Samoa\|(% style="width:251px" %)AS\|(% style="width:195px" %)ASM
	36	\|(% style="width:217px" %)Andorra\|(% style="width:251px" %)AD\|(% style="width:195px" %)AND
	37	\|(% style="width:217px" %)etc…\|(% style="width:251px" %) \|(% style="width:195px" %)
2.1	38
	39	Different source values can also map to the same target value, for example when deriving regions from country codes.
	40
10.4	41	(% style="width:674.294px" %)
11.2	42	\|(% style="width:284px" %)**Source Component:
	43	REF_AREA\|(% style="width:387px" %)Target Component:
	44	REGION**
10.4	45	\|(% style="width:284px" %)FR\|(% style="width:387px" %)EUR
	46	\|(% style="width:284px" %)DE\|(% style="width:387px" %)EUR
	47	\|(% style="width:284px" %)IT\|(% style="width:387px" %)EUR
	48	\|(% style="width:284px" %)ES\|(% style="width:387px" %)EUR
	49	\|(% style="width:284px" %)BE\|(% style="width:387px" %)EUR
2.1	50
	51	== 13.3 N-n structure maps ==
	52
	53	N-n (pronounced 'N to N') mappings describe rules where a specified combination of values in multiple source Components map to specified values in one or more target Components. For example, when mapping a partial Series Key from a highly multidimensional cube (like Balance of Payments) to a single 'Indicator' Dimension in a target Data Structure.
	54
	55	Example:
	56
10.5	57	(% style="width:760.294px" %)
	58	\|(% style="width:58px" %)Rule\|(% style="width:384px" %)Source\|(% style="width:313px" %)Target
	59	\|(% style="width:58px" %)1\|(% style="width:384px" %)(((
2.1	60	If
	61	FREQUENCY=A; and ADJUSTMENT=N; and MATURITY=L.
10.5	62	)))\|(% style="width:313px" %)(((
2.1	63	Set
	64	INDICATOR=A_N_L
	65	)))
10.5	66	\|(% style="width:58px" %)2\|(% style="width:384px" %)(((
2.1	67	If
	68	FREQUENCY=M; and ADJUSTMENT=S_A1; and MATURITY=TY12.
10.5	69	)))\|(% style="width:313px" %)(((
2.1	70	Set
	71	INDICATOR=MON_SAX_12
	72	)))
	73
	74	N-n rules can also set values for multiple source Components.
	75
10.5	76	(% style="width:757.294px" %)
	77	\|(% style="width:62px" %)Rule\|(% style="width:378px" %)Source\|(% style="width:312px" %)Target
	78	\|(% style="width:62px" %)1\|(% style="width:378px" %)(((
2.1	79	If
	80	FREQUENCY=A; and ADJUSTMENT=N; and MATURITY=L.
10.5	81	)))\|(% style="width:312px" %)(((
2.1	82	Set
10.6	83	INDICATOR=A_N_L,
	84	STATUS=QXR15,
	85	NOTE="Unadjusted".
2.1	86	)))
10.5	87	\|(% style="width:62px" %)2\|(% style="width:378px" %)(((
2.1	88	If
	89	FREQUENCY=M; and ADJUSTMENT=S_A1; and MATURITY=TY12.
10.5	90	)))\|(% style="width:312px" %)(((
2.1	91	Set
10.6	92	INDICATOR=MON_SAX_12, STATUS=MPM12,
	93	NOTE="Seasonally Adjusted"
2.1	94	)))
	95
	96	== 13.4 Ambiguous mapping rules ==
	97
	98	A structure map is ambiguous if the rules result in a dataset containing multiple series with the same Series Key.
	99
	100	A simple example mapping a source dataset with a single dimension to one with multiple dimensions is shown below:
	101
10.7	102	(% style="width:819.294px" %)
	103	\|(% style="width:240px" %)Source\|(% style="width:246px" %)Target\|(% style="width:329px" %)Output Series Key
	104	\|(% style="width:240px" %)SERIES_CODE=XMAN_Z_21\|(% style="width:246px" %)(((
2.1	105	Dimensions
	106	INDICATOR=XM
	107	FREQ=A
	108	ADJUSTMENT=N
	109	Attributes
	110	UNIT_MEASURE=_Z
	111	COMP_ORG=21
10.7	112	)))\|(% style="width:329px" %)XM:A:N
	113	\|(% style="width:240px" %)SERIES_CODE=XMAN_Z_34\|(% style="width:246px" %)(((
2.1	114	Dimensions
	115	INDICATOR=XM
	116	FREQ=A
	117	ADJUSTMENT=N
	118	Attributes
	119	UNIT_MEASURE=_Z
	120	COMP_ORG=34
10.7	121	)))\|(% style="width:329px" %)XM:A:N
2.1	122
	123	The above behaviour can be okay if the series XMAN_Z_21 contains observations for different periods of time then the series XMAN_Z_34. If however both series contain observations for the same point in time, the output for this mapping will be two observations with the same series key, for the same period in time.
	124
	125	== 13.5 Representation maps ==
	126
	127	Representation Maps replace the SDMX 2.1 Codelist Maps and are used describe explicit mappings between source and target Component values.
	128
	129	The source and target of a Representation Map can reference any of the following:
	130
	131	1. Codelist
	132	1. Free Text (restricted by type, e.g String, Integer, Boolean)
	133	1. Valuelist
	134
	135	A Representation Map mapping ISO 2-character to ISO 3-character Codelists would take the following form:
	136
10.9	137	(% style="width:763.294px" %)
	138	\|(% style="width:252px" %)CL_ISO_ALPHA2\|(% style="width:508px" %)CL_ISO_ALPHA3
	139	\|(% style="width:252px" %)AF\|(% style="width:508px" %)AFG
	140	\|(% style="width:252px" %)AL\|(% style="width:508px" %)ALB
	141	\|(% style="width:252px" %)DZ\|(% style="width:508px" %)DZA
	142	\|(% style="width:252px" %)AS\|(% style="width:508px" %)ASM
	143	\|(% style="width:252px" %)AD\|(% style="width:508px" %)AND
	144	\|(% style="width:252px" %)etc…\|(% style="width:508px" %)
2.1	145
	146	A Representation Map mapping free text country names to an ISO 2-character Codelist could be similarly described:
	147
10.9	148	(% style="width:770.294px" %)
	149	\|(% style="width:247px" %)Text\|(% style="width:520px" %)CL_ISO_ALPHA2
	150	\|(% style="width:247px" %)"Germany"\|(% style="width:520px" %)DE
	151	\|(% style="width:247px" %)"France"\|(% style="width:520px" %)FR
	152	\|(% style="width:247px" %)"United Kingdom"\|(% style="width:520px" %)GB
	153	\|(% style="width:247px" %)"Great Britain"\|(% style="width:520px" %)GB
	154	\|(% style="width:247px" %)"Ireland"\|(% style="width:520px" %)IE
	155	\|(% style="width:247px" %)"Eire"\|(% style="width:520px" %)IE
	156	\|(% style="width:247px" %)etc…\|(% style="width:520px" %)
2.1	157
	158	Valuelists, introduced in SDMX 3.0, are equivalent to Codelists but allow the maintenance of non-SDMX identifiers. Importantly, their IDs do not need to conform to IDType, but as a consequence are not Identifiable.
	159
	160	When used in Representation Maps, Valuelists allow Non-SDMX identifiers containing characters like £, $, % to be mapped to Code IDs, or Codes mapped to non-SDMX identifiers.
	161
	162	In common with Codelists, each item in a Valuelist has a multilingual name giving it a human-readable label and an optional description. For example:
	163
10.9	164	(% style="width:780.294px" %)
	165	\|(% style="width:126px" %)Value\|(% style="width:153px" %)Locale\|(% style="width:498px" %)Name
	166	\|(% style="width:126px" %)$\|(% style="width:153px" %)en\|(% style="width:498px" %)United States Dollar
	167	\|(% style="width:126px" %)%\|(% style="width:153px" %)En\|(% style="width:498px" %)Percentage
	168	\|(% style="width:126px" %) \|(% style="width:153px" %)fr\|(% style="width:498px" %)Pourcentage
2.1	169
	170	Other characteristics of Representation Maps:
	171
	172	* Support the mapping of multiple source Component values to multiple Target Component values as described in section 13.3 on n-to-n mappings; this covers also the case of mapping an Attribute with an array representation to map combinations of values to a single target value;
	173	* Allow source or target mappings for an Item to be optional allowing rules such as 'A maps to nothing' or 'nothing maps to A'; and
	174	* Support for mapping rules where regular expressions or substrings are used to match source Component values. Refer to section 13.6 for more on this topic.
	175
	176	== 13.6 Regular expression and substring rules ==
	177
	178	It is common for classifications to contain meanings within the identifier, for example the code Id 'XULADS' may refer to a particular seasonality because it starts with the letters XU.
	179
	180	With SDMX 2.1 each code that starts with XU had to be individually mapped to the same seasonality, and additional mappings added when new Codes were added to the Codelists. This led to many hundreds or thousands of mappings which can be more efficiently summarised in a single conceptual rule:
	181
	182	//If starts with 'XU' map to 'Y'//
	183
	184	These rules are described using either regular expressions, or substrings for simpler use cases.
	185
	186	=== 13.6.1 Regular expressions ===
	187
	188	Regular expression mapping rules are defined in the Representation Map.
	189
	190	Below is an example set of regular expression rules for a particular component.
	191
10.10	192	(% style="width:708.294px" %)
	193	\|(% style="width:133px" %)Regex\|(% style="width:377px" %)Description\|(% style="width:194px" %)Output
	194	\|(% style="width:133px" %)A\|(% style="width:377px" %)Rule match if input = 'A'\|(% style="width:194px" %)OUT_A
	195	\|(% style="width:133px" %)^[A-G]\|(% style="width:377px" %)Rule match if the input starts with letters A to G\|(% style="width:194px" %)OUT_B
	196	\|(% style="width:133px" %)A~\|B\|(% style="width:377px" %)Rule match if input is either 'A' or 'B'\|(% style="width:194px" %)OUT_C
2.1	197
	198	Like all mapping rules, the output is either a Code, a Value or free text depending on the representation of the Component in the target Data Structure Definition.
	199
	200	If the regular expression contains capture groups, these can be used in the definition of the output value, by specifying \//n //as an output value where //n// is the number of the capture group starting from 1. For example
	201
10.10	202	(% style="width:720.294px" %)
	203	\|(% style="width:199px" %)Regex\|(% style="width:126px" %)Target output\|(% style="width:192px" %)Example Input\|(% style="width:200px" %)Example Output
	204	\|(% style="width:199px" %)(((
	205	([0-9]{4})[0-9]([0-9]{1})
	206	)))\|(% style="width:126px" %)\1-Q\2\|(% style="width:192px" %)200933\|(% style="width:200px" %)2009-Q3
2.1	207
	208	As regular expression rules can be used as a general catch-all if nothing else matches, the ordering of the rules is important. Rules should be tested starting with the highest priority, moving down the list until a match is found.
	209
	210	The following example shows this:
	211
10.10	212	(% style="width:725.294px" %)
	213	\|(% style="width:198px" %)Priority\|(% style="width:148px" %)Regex\|(% style="width:212px" %)Description\|(% style="width:164px" %)Output
	214	\|(% style="width:198px" %)1\|(% style="width:148px" %)A\|(% style="width:212px" %)Rule match if input = 'A'\|(% style="width:164px" %)OUT_A
	215	\|(% style="width:198px" %)2\|(% style="width:148px" %)B\|(% style="width:212px" %)Rule match if input = 'B'\|(% style="width:164px" %)OUT_B
	216	\|(% style="width:198px" %)3\|(% style="width:148px" %)[A-Z]\|(% style="width:212px" %)Any character A-Z\|(% style="width:164px" %)OUT_C
2.1	217
	218	The input 'A' matches both the first and the last rule, but the first takes precedence having the higher priority. The output is OUT_A.
	219
	220	The input 'G' matches on the last rule which is used as a catch-all or default in this example.
	221
	222	=== 13.6.2 Substrings ===
	223
	224	Substrings provide an alternative to regular expressions where the required section of an input value can be described using the number of the starting character, and the length of the substring in characters. The first character is at position 1.
	225
	226	For instance:
	227
10.10	228	(% style="width:742.294px" %)
	229	\|(% style="width:191px" %)Input String\|(% style="width:154px" %)Start\|(% style="width:211px" %)Length\|(% style="width:182px" %)Output
	230	\|(% style="width:191px" %)ABC_DEF_XYZ\|(% style="width:154px" %)5\|(% style="width:211px" %)3\|(% style="width:182px" %)DEF
	231	\|(% style="width:191px" %)XULADS\|(% style="width:154px" %)1\|(% style="width:211px" %)2\|(% style="width:182px" %)XU
2.1	232
	233	Sub-strings can therefore be used for the conceptual rule //If starts with 'XU' map to Y// as shown in the following example:
	234
10.11	235	(% style="width:740.294px" %)
	236	\|(% style="width:194px" %)Start\|(% style="width:151px" %)Length\|(% style="width:208px" %)Source\|(% style="width:183px" %)Target
	237	\|(% style="width:194px" %)1\|(% style="width:151px" %)2\|(% style="width:208px" %)XU\|(% style="width:183px" %)Y
2.1	238
	239	== 13.7 Mapping non-SDMX time formats to SDMX formats ==
	240
	241	Structure mapping allows non-SDMX compliant time values in source datasets to be mapped to an SDMX compliant time format.
	242
	243	Two types of time input are defined:
	244
	245	a. Pattern based dates – a string which can be described using a notation like dd/mm/yyyy or is represented as the number of periods since a point in time, for example: 2010M001 (first month in 2010), or 2014D123 (123^^rd^^ day in 2014); and b. Numerical based datetime – a number specifying the elapsed periods since a fixed point in time, for example Unix Time is measured by the number of milliseconds since 1970.
	246
	247	The output of a time-based mapping is derived from the output Frequency, which is either explicitly stated in the mapping or defined as the value output by a specific Dimension or Attribute in the output mapping. If the output frequency is unknown or if the SDMX format is not desired, then additional rules can be provided to specify the output date format for the given frequency Id. The default rules are:
	248
10.11	249	(% style="width:771.294px" %)
	250	\|(% style="width:187px" %)Frequency\|(% style="width:159px" %)Format\|(% style="width:422px" %)Example
	251	\|(% style="width:187px" %)A\|(% style="width:159px" %)YYYY\|(% style="width:422px" %)2010
	252	\|(% style="width:187px" %)D\|(% style="width:159px" %)YYYY-MM-DD\|(% style="width:422px" %)2010-01-01
	253	\|(% style="width:187px" %)I\|(% style="width:159px" %)YYYY-MM-DDThh:mm:ss\|(% style="width:422px" %)2010-01T20:22:00
	254	\|(% style="width:187px" %)M\|(% style="width:159px" %)YYYY-MM\|(% style="width:422px" %)2010-01
	255	\|(% style="width:187px" %)Q\|(% style="width:159px" %)YYYY-Qn\|(% style="width:422px" %)2010-Q1
	256	\|(% style="width:187px" %)S\|(% style="width:159px" %)YYYY-Sn\|(% style="width:422px" %)2010-S1
	257	\|(% style="width:187px" %)T\|(% style="width:159px" %)YYYY-Tn\|(% style="width:422px" %)2010-T1
	258	\|(% style="width:187px" %)W\|(% style="width:159px" %)YYYY-Wn\|(% style="width:422px" %)YYYY-W53
2.1	259
	260	In the case where the input frequency is lower than the output frequency, the mapping defaults to end of period, but can be explicitly set to start, end or mid-period.
	261
	262	There are two important points to note:
	263
	264	1. The output frequency determines the output date format, but the default output can be redefined using a Frequency Format mapping to force explicit rules on how the output time period is formatted.
	265	1. To support the use case of changing frequency the structure map can optionally provide a start of year attribute, which defines the year start date in MM-DD format. For example: YearStart=04-01.
	266
	267	=== 13.7.1 Pattern based dates ===
	268
	269	Date and time formats are specified by date and time pattern strings based on Java's Simple Date Format. Within date and time pattern strings, unquoted letters from 'A' to 'Z' and from 'a' to 'z' are interpreted as pattern letters representing the components of a date or time string. Text can be quoted using single quotes (') to avoid interpretation. "''" represents a single quote. All other characters are not interpreted; they're simply copied into the output string during formatting or matched against the input string during parsing.
	270
10.11	271	Due to the fact that dates may differ per locale, an optional property, defining the locale of the pattern, is provided. This would assist processing of source dates, according to the given locale{{footnote}}Unidimensional datasets are those with a single 'indicator' or 'series code' dimension.{{/footnote}}. An indicative list of examples is presented in the following table:
2.1	272
10.11	273	(% style="width:772.294px" %)
	274	\|(% style="width:190px" %)English (en)\|(% style="width:230px" %)Australia (AU)\|(% style="width:348px" %)en-AU
	275	\|(% style="width:190px" %)English (en)\|(% style="width:230px" %)Canada (CA)\|(% style="width:348px" %)en-CA
	276	\|(% style="width:190px" %)English (en)\|(% style="width:230px" %)United Kingdom (GB)\|(% style="width:348px" %)en-GB
	277	\|(% style="width:190px" %)English (en)\|(% style="width:230px" %)United States (US)\|(% style="width:348px" %)en-US
	278	\|(% style="width:190px" %)Estonian (et)\|(% style="width:230px" %)Estonia (EE)\|(% style="width:348px" %)et-EE
	279	\|(% style="width:190px" %)Finnish (fi)\|(% style="width:230px" %)Finland (FI)\|(% style="width:348px" %)fi-FI
	280	\|(% style="width:190px" %)French (fr)\|(% style="width:230px" %)Belgium (BE)\|(% style="width:348px" %)fr-BE
	281	\|(% style="width:190px" %)French (fr)\|(% style="width:230px" %)Canada (CA)\|(% style="width:348px" %)fr-CA
	282	\|(% style="width:190px" %)French (fr)\|(% style="width:230px" %)France (FR)\|(% style="width:348px" %)fr-FR
	283	\|(% style="width:190px" %)French (fr)\|(% style="width:230px" %)Luxembourg (LU)\|(% style="width:348px" %)fr-LU
	284	\|(% style="width:190px" %)French (fr)\|(% style="width:230px" %)Switzerland (CH)\|(% style="width:348px" %)fr-CH
	285	\|(% style="width:190px" %)German (de)\|(% style="width:230px" %)Austria (AT)\|(% style="width:348px" %)de-AT
	286	\|(% style="width:190px" %)German (de)\|(% style="width:230px" %)Germany (DE)\|(% style="width:348px" %)de-DE
2.1	287
10.12	288	(% style="width:773.294px" %)
	289	\|(% style="width:190px" %)German (de)\|(% style="width:234px" %)Luxembourg (LU)\|(% style="width:345px" %)de-LU
	290	\|(% style="width:190px" %)German (de)\|(% style="width:234px" %)Switzerland (CH)\|(% style="width:345px" %)de-CH
	291	\|(% style="width:190px" %)Greek (el)\|(% style="width:234px" %)Cyprus (CY)\|(% style="width:345px" %)el-CY__([[*>>https://www.oracle.com/java/technologies/javase/jdk8-jre8-suported-locales.html#cldrlocale]])__
	292	\|(% style="width:190px" %)Greek (el)\|(% style="width:234px" %)Greece (GR)\|(% style="width:345px" %)el-GR
	293	\|(% style="width:190px" %)Hebrew (iw)\|(% style="width:234px" %)Israel (IL)\|(% style="width:345px" %)iw-IL
	294	\|(% style="width:190px" %)Hindi (hi)\|(% style="width:234px" %)India (IN)\|(% style="width:345px" %)hi-IN
	295	\|(% style="width:190px" %)Hungarian (hu)\|(% style="width:234px" %)Hungary (HU)\|(% style="width:345px" %)hu-HU
	296	\|(% style="width:190px" %)Icelandic (is)\|(% style="width:234px" %)Iceland (IS)\|(% style="width:345px" %)is-IS
	297	\|(% style="width:190px" %)Indonesian (in)\|(% style="width:234px" %)Indonesia (ID)\|(% style="width:345px" %)in-ID__([[*>>https://www.oracle.com/java/technologies/javase/jdk8-jre8-suported-locales.html#cldrlocale]])__
	298	\|(% style="width:190px" %)Irish (ga)\|(% style="width:234px" %)Ireland (IE)\|(% style="width:345px" %)ga-IE__([[*>>https://www.oracle.com/java/technologies/javase/jdk8-jre8-suported-locales.html#cldrlocale]])__
	299	\|(% style="width:190px" %)Italian (it)\|(% style="width:234px" %)Italy (IT)\|(% style="width:345px" %)it-IT
2.1	300
	301	Examples
	302
	303	22/06/1981 would be described as dd/MM/YYYY, with locale en-GB
	304
	305	2008-mars-12 would be described as YYYY-MMM-DD, with locale fr-FR
	306
	307	22 July 1981 would be described as dd MMMM YYYY, with locale en-US
	308
	309	22 Jul 1981 would be described as dd MMM YYYY
	310
	311	2010 D62 would be described as YYYYDnn (day 62 of the year 2010)
	312
	313	The following pattern letters are defined (all other characters from 'A' to 'Z' and from 'a' to 'z' are reserved):
	314
10.12	315	(% style="width:896.294px" %)
10.13	316	\|(% style="width:133px" %)Letter\|(% style="width:414px" %)Date or Time Component\|(% style="width:157px" %)Presentation\|(% style="width:172px" %)Examples
	317	\|(% style="width:133px" %)G\|(% style="width:414px" %)Era designator\|(% style="width:157px" %)Text\|(% style="width:172px" %)AD
	318	\|(% style="width:133px" %)yy\|(% style="width:414px" %)Year short (upper case is Year of Week{{footnote}}yyyy represents the calendar year while YYYY represents the year of the week, which is only relevant for 53 week years{{/footnote}})\|(% style="width:157px" %)Year\|(% style="width:172px" %)96
	319	\|(% style="width:133px" %)yyyy\|(% style="width:414px" %)Year Full (upper case is Year of Week)\|(% style="width:157px" %)Year\|(% style="width:172px" %)1996
	320	\|(% style="width:133px" %)MM\|(% style="width:414px" %)Month number in year starting with 1\|(% style="width:157px" %)Month\|(% style="width:172px" %)07
	321	\|(% style="width:133px" %)MMM\|(% style="width:414px" %)Month name short\|(% style="width:157px" %)Month\|(% style="width:172px" %)Jul
	322	\|(% style="width:133px" %)MMMM\|(% style="width:414px" %)Month name full\|(% style="width:157px" %)Month\|(% style="width:172px" %)July
	323	\|(% style="width:133px" %)ww\|(% style="width:414px" %)Week in year\|(% style="width:157px" %)Number\|(% style="width:172px" %)27
	324	\|(% style="width:133px" %)W\|(% style="width:414px" %)Week in month\|(% style="width:157px" %)Number\|(% style="width:172px" %)2
	325	\|(% style="width:133px" %)DD\|(% style="width:414px" %)Day in year\|(% style="width:157px" %)Number\|(% style="width:172px" %)189
	326	\|(% style="width:133px" %)dd\|(% style="width:414px" %)Day in month\|(% style="width:157px" %)Number\|(% style="width:172px" %)10
	327	\|(% style="width:133px" %)F\|(% style="width:414px" %)Day of week in month\|(% style="width:157px" %)Number\|(% style="width:172px" %)2
	328	\|(% style="width:133px" %)E\|(% style="width:414px" %)Day name in week\|(% style="width:157px" %)Text\|(% style="width:172px" %)Tuesday; Tue
	329	\|(% style="width:132px" %)U\|(% style="width:414px" %)Day number of week (1 = Monday, ..., 7 = Sunday)\|(% style="width:157px" %)Number\|(% style="width:217px" %)1
	330	\|(% style="width:132px" %)HH\|(% style="width:414px" %)Hour in day (0-23)\|(% style="width:157px" %)Number\|(% style="width:217px" %)0
	331	\|(% style="width:132px" %)kk\|(% style="width:414px" %)Hour in day (1-24)\|(% style="width:157px" %)Number\|(% style="width:217px" %)24
	332	\|(% style="width:132px" %)KK\|(% style="width:414px" %)Hour in am/pm (0-11)\|(% style="width:157px" %)Number\|(% style="width:217px" %)0
	333	\|(% style="width:132px" %)hh\|(% style="width:414px" %)Hour in am/pm (1-12)\|(% style="width:157px" %)Number\|(% style="width:217px" %)12
	334	\|(% style="width:132px" %)mm\|(% style="width:414px" %)Minute in hour\|(% style="width:157px" %)Number\|(% style="width:217px" %)30
	335	\|(% style="width:132px" %)ss\|(% style="width:414px" %)Second in minute\|(% style="width:157px" %)Number\|(% style="width:217px" %)55
	336	\|(% style="width:132px" %)S\|(% style="width:414px" %)Millisecond\|(% style="width:157px" %)Number\|(% style="width:217px" %)978
	337	\|(% style="width:132px" %)n\|(% style="width:414px" %)Number of periods, used after a SDMX Frequency Identifier such as M, Q, D (month, quarter, day)\|(% style="width:157px" %)Number\|(% style="width:217px" %)12
2.1	338
	339	The model is illustrated below:
	340
	341	[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_295af259.jpg\|\|height="265" width="477"]]
	342
	343	==== Figure 24 showing the component map mapping the SOURCE_DATE Dimension to the TIME_PERIOD dimension with the additional information on the component map to describe the time format ====
	344
	345	[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_a3215c79.jpg\|\|height="265" width="480"]]
	346
	347	==== Figure 25 showing an input date format, whose output frequency is derived from the output value of the FREQ Dimension ====
	348
	349	=== 13.7.2 Numerical based datetime ===
	350
	351	Where the source datetime input is purely numerical, the mapping rules are defined by the Base as a valid SDMX Time Period, and the Period which must take one of the following enumerated values:
	352
	353	* day
	354	* second
	355	* millisecond
	356	* microsecond
	357	* nanosecond
	358
10.14	359	(% style="width:573.294px" %)
	360	\|(% style="width:276px" %)Numerical datetime systems\|(% style="width:117px" %)Base\|(% style="width:177px" %)Period
	361	\|(% style="width:276px" %)(((
2.1	362	Epoch Time (UNIX)
	363	Milliseconds since 01 Jan 1970
10.14	364	)))\|(% style="width:117px" %)1970\|(% style="width:177px" %)millisecond
	365	\|(% style="width:276px" %)(((
2.1	366	Windows System Time
	367	Milliseconds since 01 Jan 1601
10.14	368	)))\|(% style="width:117px" %)1601\|(% style="width:177px" %)millisecond
2.1	369
	370	The example above illustrates numerical based datetime mapping rules for two commonly used time standards.
	371
	372	The model is illustrated below:
	373
	374	[[image:SDMX 3-0-0 SECTION 6 FINAL-1.0_en_ab51b44a.jpg\|\|height="113" width="485"]]
	375
	376	Figure 26 showing the component map mapping the SOURCE_DATE Dimension to the
	377
	378	==== TIME_PERIOD Dimension with the additional information on the component map to describe the numerical datetime system in use ====
	379
	380	=== 13.7.3 Mapping more complex time inputs ===
	381
	382	VTL should be used for more complex time inputs that cannot be interpreted using the pattern based on numerical methods.
	383
	384	== 13.8 Using TIME_PERIOD in mapping rules ==
	385
	386	The source TIME_PERIOD Dimension can be used in conjunction with other input Dimensions to create discrete mapping rules where the output is conditional on the time period value.
	387
	388	The main use case is setting the value of Observation Attributes in the target dataset.
	389
10.14	390	(% style="width:786.294px" %)
	391	\|(% style="width:92px" %)Rule\|(% style="width:377px" %)Source\|(% style="width:315px" %)Target
	392	\|(% style="width:92px" %)1\|(% style="width:377px" %)(((
2.1	393	If
	394	INDICATOR=XULADS; and TIME_PERIOD=2007.
10.14	395	)))\|(% style="width:315px" %)(((
2.1	396	Set
	397	OBS_CONF=F
	398	)))
10.14	399	\|(% style="width:92px" %)2\|(% style="width:377px" %)(((
2.1	400	If
	401	INDICATOR=XULADS; and TIME_PERIOD=2008.
10.14	402	)))\|(% style="width:315px" %)(((
2.1	403	Set
	404	OBS_CONF=F
	405	)))
10.14	406	\|(% style="width:92px" %)3\|(% style="width:377px" %)(((
2.1	407	If
	408	INDICATOR=XULADS; and TIME_PERIOD=2009.
10.14	409	)))\|(% style="width:315px" %)(((
2.1	410	Set
	411	OBS_CONF=F
	412	)))
10.14	413	\|(% style="width:92px" %)4\|(% style="width:377px" %)(((
2.1	414	If
	415	INDICATOR=XULADS; and TIME_PERIOD=2010.
10.14	416	)))\|(% style="width:315px" %)(((
2.1	417	Set
	418	OBS_CONF=C
	419	)))
	420
	421	In the example above, OBS_CONF is an Observation Attribute.
	422
	423	== 13.9 Time span mapping rules using validity periods ==
	424
	425	Creating discrete mapping rules for each TIME_PERIOD is impractical where rules need to cover a specific span of time regardless of frequency, and for high-frequency data.
	426
	427	Instead, an optional validity period can be set for each mapping.
	428
	429	By specifying validity periods, the example from Section 13.8 can be re-written using two rules as follows:
	430
10.15	431	(% style="width:808.294px" %)
	432	\|(% style="width:93px" %)Rule\|(% style="width:385px" %)Source\|(% style="width:328px" %)Target
	433	\|(% style="width:93px" %)1\|(% style="width:385px" %)(((
2.1	434	If
	435	INDICATOR=XULADS.
	436	Validity Period start period=2007 end period=2009
10.15	437	)))\|(% style="width:328px" %)(((
2.1	438	Set
	439	OBS_CONF=F
	440	)))
10.15	441	\|(% style="width:93px" %)2\|(% style="width:385px" %)(((
2.1	442	If
	443	INDICATOR=XULADS.
	444	Validity Period start period=2010
10.15	445	)))\|(% style="width:328px" %)(((
2.1	446	Set
	447	OBS_CONF=F
	448	)))
	449
	450	In Rule 1, start period resolves to the start of the 2007 period (2007-01-01T00:00:00), and the end period resolves to the very end of 2009 (2009-12-31T23:59:59). The rule will hold true regardless of the input data frequency. Any observations reporting data for the Indicator XULADS that fall into that time range will have an OBS_CONF value of F.
	451
	452	In Rule 2, no end period is specified so remains in effect from the start of the period (2010-01-01T00:00:00) until the end of time. Any observations reporting data for the Indicator XULADS that fall into that time range will have an OBS_CONF value of C.
	453
	454	== 13.10 Mapping examples ==
	455
	456	=== 13.10.1 Many to one mapping (N-1) ===
	457
10.18	458	[[image:1747377208446-496.png]]
2.1	459
	460	The bold Dimensions map from source to target verbatim. The mapping simply specifies:
	461
	462	FREQ => FREQ
	463
	464	REF_AREA=> REF_AREA
	465
	466	COUNTERPART_AREA=> COUNTERPART _AREA
	467
	468	No Representation Mapping is required. The source value simply copies across unmodified.
	469
	470	The remaining Dimensions all map to the Indicator Dimension. This is an example of many Dimensions mapping to one Dimension. In this case a Representation Mapping is required, and the mapping first describes the input 'partial key' and how this maps to the target indicator:
	471
	472	N:S1:S1:B:B5G => IND_ABC
	473
	474	Where the key sequence is based on the order specified in the mapping (i.e ADJUSTMENT, REF_SECTOR, etc will result in the first value N being taken from ADJUSTMENT as this was the first item in the source Dimension list.
	475
	476	Note: The key order is NOT based on the Dimension order of the DSD, as the mapping needs to be resilient to the DSD changing.
	477
	478	=== 13.10.2 Mapping other data types to Code Id ===
	479
	480	In the case where the incoming data type is not a string and not a code identifier i.e. the source Dimension is of type Integer and the target is Codelist. This is supported by the RepresentationMap. The RepresentationMap source can reference a Codelist, Valuelist, or be free text, the free text can include regular expressions.
	481
	482	The following representation mapping can be used to explicitly map each age to an output code.
	483
	484	(((
10.16	485	(% style="width:669.294px" %)
	486	\|(% style="width:218px" %)Source Input Free Text\|(% style="width:448px" %)Desired Output Code Id
	487	\|(% style="width:218px" %)0\|(% style="width:448px" %)A
	488	\|(% style="width:218px" %)1\|(% style="width:448px" %)A
	489	\|(% style="width:218px" %)2\|(% style="width:448px" %)A
	490	\|(% style="width:218px" %)3\|(% style="width:448px" %)B
	491	\|(% style="width:218px" %)4\|(% style="width:448px" %)B
2.1	492	)))
	493
10.19	494	If this mapping takes advantage of regular expressions it can be expressed in two rules:
2.1	495
	496	(((
10.16	497	(% style="width:675.294px" %)
10.19	498	\|(% style="width:219px" %)(((
	499	Regular Expression
	500	)))\|(% style="width:453px" %)Desired Output
10.16	501	\|(% style="width:219px" %)[0-2]\|(% style="width:453px" %)A
	502	\|(% style="width:219px" %)[3-4]\|(% style="width:453px" %)B
10.19	503
	504	(% style="color:inherit; font-family:inherit; font-size:max(21px, min(23px, 17.4444px + 0.462963vw))" %)13.10.3 Observation Attributes for Time Period
2.1	505	)))
	506
	507	This use case is where a specific observation for a specific time period has an attribute 3468 value.
	508
	509	(((
10.16	510	(% style="width:689.294px" %)
	511	\|(% style="width:220px" %)Input INDICATOR\|(% style="width:223px" %)Input TIME_PERIOD\|(% style="width:243px" %)Output OBS_CONF
	512	\|(% style="width:220px" %)XULADS\|(% style="width:223px" %)2008\|(% style="width:243px" %)C
	513	\|(% style="width:220px" %)XULADS\|(% style="width:223px" %)2009\|(% style="width:243px" %)C
	514	\|(% style="width:220px" %)XULADS\|(% style="width:223px" %)2010\|(% style="width:243px" %)C
2.1	515	)))
	516
	517	__Or using a validity period on the Representation Mapping__:
	518
10.16	519	Input INDICATOR Valid From/ Valid To Output OBS_CONF XULADS 2008/2010 C
2.1	520
	521	=== 13.10.4 Time mapping ===
	522
	523	This use case is to create a time period from an input that does not respect SDMXTime Formats.
	524
	525	The Component Mapping from SYS_TIME to TIME_PERIOD specifies itself as a time mapping with the following details:
	526
	527	(((
10.17	528	(% style="width:763.294px" %)
	529	\|(% style="width:163px" %)Source Value\|(% style="width:219px" %)Source Mapping\|(% style="width:198px" %)Target Frequency\|(% style="width:180px" %)Output
	530	\|(% style="width:163px" %)18/07/1981\|(% style="width:219px" %)dd/MM/yyyy\|(% style="width:198px" %)A\|(% style="width:180px" %)1981
2.1	531	)))
	532
	533	When the target frequency is based on another target Dimension value, in this example __the value of the FREQ Dimension in the tar__get DSD.
	534
	535
	536	(((
	537	\|Source Value\|Source Mapping\|Target Frequency Output Dimension
	538
10.2	539	\|18/07/1981 dd/MM/yyyy\|FREQ\| \|1981-07-18 (when FREQ=D)
2.1	540	\|(% rowspan="2" %)(((
	541	__When the source is a numerical form__at
	542
	543	Source Value Start Period Interv
10.2	544	)))\| \| \|
2.1	545	\|al\|(((
	546	Target
	547
	548	FREQ
	549	)))\|Output
	550	\|(% colspan="2" %)1589808220 1970 millisecond\|M\|2020-05
	551	)))
	552
	553	When the source frequency is lower than the target frequency additional information 3485 can be provided for resolve to start of period, end of period, or mid period, as shown 3486 in the following example:
	554
	555	Source Value Source Mapping Target Frequency Output
	556
	557	Dimension
	558
10.18	559	1981 yyyy D – End of Period 1981-12-31
2.1	560
	561	When the start of year is April 1^^st^^ the Structure Map has YearStart=04-01:
	562
	563	Source Value Source Mapping Target Frequency Output
	564
	565	Dimension
	566
	567	1981 yyyy D – End of Period 1982-03-31
10.3	568
	569	{{putFootnotes/}}