{"id":"A","name":"Normal value","description":"To be used as default value if no value is provided or when no special coded qualification is assumed. Usually, it can be assumed that the source agency assigns sufficient confidence to the provided observation and/or the value is not expected to be dramatically revised.","name_locale":"en","description_locale":"en"}
{"id":"B","name":"Time series break","description":"Observations are characterised as such when different content exists or a different methodology has been applied to this observation as compared with the preceding one (the one given for the previous period).","name_locale":"en","description_locale":"en"}
{"id":"D","name":"Definition differs","description":"Used to indicate slight deviations from the established methodology (footnote-type information); these divergences do not imply a break in time series.","name_locale":"en","description_locale":"en"}
{"id":"E","name":"Estimated value","description":"Observation obtained through an estimation methodology (e.g. to produce back-casts) or based on the use of a limited amount of data or ad hoc sampling and through additional calculations (e.g. to produce a value at an early stage of the production stage while not all data are available). It may also be used in case of experimental data (e.g. in the context of a pilot ahead of a full scale production process) or in case of data of (anticipated/assessed) low quality. If needed, additional information can be provided through free text using the COMMENT_ObS attribute at the observation level or at a higher level. This code is to be used when the estimation is done by a sender agency. When the imputation is carried out by a receiver agency in order to replace or fill gaps in reported data series, the flag to use is I \"Value imputed by a receiving agency\".","name_locale":"en","description_locale":"en"}
{"id":"F","name":"Forecast value","description":"Value deemed to assess the magnitude which a quantity will assume at some future point of time (as distinct from \"estimated value\" which attempts to assess the magnitude of an already existent quantity).","name_locale":"en","description_locale":"en"}
{"id":"G","name":"Experimental value","description":"Data collected on the basis of definitions or (alternative) collection methods under development. Data not of guaranteed quality as normally expected from provider.","name_locale":"en","description_locale":"en"}
{"id":"I","name":"Value imputed by a receiving agency","description":"Observation imputed by a receiving agency to replace or fill gaps in reported data series. This code is intended to cover all cases where a receiving agency publishes data about a sending agency that do not come from an official source in the sender agency's reporting framework. When the estimation is done by the sender agency, the flag to use is E \"Estimated value\".","name_locale":"en","description_locale":"en"}
{"id":"K","name":"Data included in another category","description":"This code is used when data for a given category are missing and are included in another category, sub-total or total. Generally where code \"K\" is used there should be a corresponding code \"W - Includes data from another category\" assigned to the over-covered category. Implementers and data reporters should use the COMMENT_ObS observation-level attribute to specify under which category the data are included.","name_locale":"en","description_locale":"en"}
{"id":"W","name":"Includes data from another category","description":"This code is used when data include another category, or go beyond the scope of the data collection and are therefore over-covered. Generally, where code \"W\" is used there should be a corresponding code \"K - Data included in another category\" assigned to the category which is under-covered. Implementers and data reporters should use the COMMENT_ObS observation-level attribute to specify which additional data are included.","name_locale":"en","description_locale":"en"}
{"id":"O","name":"Missing value","description":"This code is to be used when no breakdown is made between the reasons why data are missing. Data can be missing due to many reasons: data cannot exist, data exist but are not collected (e.g. because they are below a certain threshold or subject to a derogation clause), data are unreliable, etc.","name_locale":"en","description_locale":"en"}
{"id":"M","name":"Missing value; data cannot exist","description":"Used to denote empty cells resulting from the impossibility to collect a statistical value (e.g. a particular education level or type of institution may be not applicable to a given country's education system).","name_locale":"en","description_locale":"en"}
{"id":"P","name":"Provisional value","description":"An observation is characterised as \"provisional\" when the source agency - while it bases its calculations on its standard production methodology - considers that the data, almost certainly, are expected to be revised.","name_locale":"en","description_locale":"en"}
{"id":"S","name":"Strike and other special events","description":"Special circumstances (e.g. strike) affecting the observation or causing a missing value.","name_locale":"en","description_locale":"en"}
{"id":"L","name":"Missing value; data exist but were not collected","description":"Used, for example, when some data are not reported/disseminated because they are below a certain threshold.","name_locale":"en","description_locale":"en"}
{"id":"H","name":"Missing value; holiday or weekend","description":"Used in some daily data flows.","name_locale":"en","description_locale":"en"}
{"id":"Q","name":"Missing value; suppressed","description":"Used, for example, when data are suppressed due to statistical confidentiality considerations.","name_locale":"en","description_locale":"en"}
{"id":"J","name":"Derogation","description":"Clause in an agreement (e.g. legal act, gentlemen's agreement) stating that some provisions in the agreement are not to be implemented by designated parties; these derogations may affect the observation or cause a missing value. In general, derogations are limited in time.","name_locale":"en","description_locale":"en"}
{"id":"N","name":"Not significant","description":"Used to indicate a value which is not a \"real\" zero (e.g. a result of 0.0004 rounded to zero).","name_locale":"en","description_locale":"en"}
{"id":"U","name":"Low reliability","description":"This indicates existing observations, but for which the user should also be aware of the low quality assigned.","name_locale":"en","description_locale":"en"}
{"id":"V","name":"Unvalidated value","description":"Observation as received from the respondent without further evaluation of data quality.","name_locale":"en","description_locale":"en"}