"dataset_code","var_name","id","name","count","Description","RelatedItem"
"turnover_recorded_music","freq","A","Annual",570,"To be used for data collected or disseminated every year","[{""RelatedItem"":""ISO 8601 date and time format (correspondence table)"",""relationType"":""Cites"",""relatedItemIdentifier"":""https://www.iso.org/iso-8601-date-and-time-format.html"",""relatedItemIdentifierType"":""URL""},{""RelatedItem"":""SDMX Code List for Frequency"",""relationType"":""IsDocumentedBy"",""relatedItemIdentifier"":""https://sdmx.org/?page_id=3215/"",""relatedItemIdentifierType"":""URL""}]"
"turnover_recorded_music","geo","AT","Austria",15,"Observation related to Austria",""
"turnover_recorded_music","geo","BA","Bosnia and Herzegovina",12,"Observation related to Bosnia and Herzegovina",""
"turnover_recorded_music","geo","BE","Belgium",15,"Observation related to Belgium",""
"turnover_recorded_music","geo","BG","Bulgaria",15,"Observation related to Bulgaria",""
"turnover_recorded_music","geo","CH","Switzerland",15,"Observation related to Switzerland",""
"turnover_recorded_music","geo","CY","Cyprus",15,"Observation related to Cyprus",""
"turnover_recorded_music","geo","CZ","Czechia",15,"Observation related to Czechia",""
"turnover_recorded_music","geo","DE","Germany (until 1990 former territory of the FRG)",15,"Observation related to Germany (until 1990 former territory of the FRG)",""
"turnover_recorded_music","geo","DK","Denmark",15,"Observation related to Denmark",""
"turnover_recorded_music","geo","EE","Estonia",13,"Observation related to Estonia",""
"turnover_recorded_music","geo","EL","Greece",15,"Observation related to Greece",""
"turnover_recorded_music","geo","ES","Spain",15,"Observation related to Spain",""
"turnover_recorded_music","geo","EU27_2007","European Union - 27 countries (2007-2013)",7,"Observation related to European Union - 27 countries (2007-2013)",""
"turnover_recorded_music","geo","EU27_2020","European Union - 27 countries (from 2020)",12,"Observation related to European Union - 27 countries (from 2020)",""
"turnover_recorded_music","geo","EU28","European Union - 28 countries (2013-2020)",12,"Observation related to European Union - 28 countries (2013-2020)",""
"turnover_recorded_music","geo","FI","Finland",15,"Observation related to Finland",""
"turnover_recorded_music","geo","FR","France",15,"Observation related to France",""
"turnover_recorded_music","geo","HR","Croatia",12,"Observation related to Croatia",""
"turnover_recorded_music","geo","HU","Hungary",15,"Observation related to Hungary",""
"turnover_recorded_music","geo","IE","Ireland",10,"Observation related to Ireland",""
"turnover_recorded_music","geo","IS","Iceland",8,"Observation related to Iceland",""
"turnover_recorded_music","geo","IT","Italy",15,"Observation related to Italy",""
"turnover_recorded_music","geo","LT","Lithuania",15,"Observation related to Lithuania",""
"turnover_recorded_music","geo","LU","Luxembourg",15,"Observation related to Luxembourg",""
"turnover_recorded_music","geo","LV","Latvia",15,"Observation related to Latvia",""
"turnover_recorded_music","geo","MK","North Macedonia",10,"Observation related to North Macedonia",""
"turnover_recorded_music","geo","MT","Malta",7,"Observation related to Malta",""
"turnover_recorded_music","geo","NL","Netherlands",15,"Observation related to Netherlands",""
"turnover_recorded_music","geo","NO","Norway",15,"Observation related to Norway",""
"turnover_recorded_music","geo","PL","Poland",15,"Observation related to Poland",""
"turnover_recorded_music","geo","PT","Portugal",15,"Observation related to Portugal",""
"turnover_recorded_music","geo","RO","Romania",15,"Observation related to Romania",""
"turnover_recorded_music","geo","RS","Serbia",7,"Observation related to Serbia",""
"turnover_recorded_music","geo","SE","Sweden",15,"Observation related to Sweden",""
"turnover_recorded_music","geo","SI","Slovenia",15,"Observation related to Slovenia",""
"turnover_recorded_music","geo","SK","Slovakia",15,"Observation related to Slovakia",""
"turnover_recorded_music","geo","TR","Turkey",6,"Observation related to Turkey",""
"turnover_recorded_music","geo","UK","United Kingdom",15,"Observation related to United Kingdom",""
"turnover_recorded_music","geo_units_reduced","gain","Information gain",4,"Geo units in the largest subset of the  observatory dataset (gained.)",""
"turnover_recorded_music","geo_units_reduced","gain_pct","Information gain (% increase)",0.181818181818182,"Geo units in the largest subset of the  observatory dataset (% increase.)",""
"turnover_recorded_music","geo_units_reduced","observatory","Observatory (processed) dataset",26,"Geo units in the largest subset of the  observatory (processed) dataset.",""
"turnover_recorded_music","geo_units_reduced","source","Source dataset",22,"Geo units in the largest subset of the  source dataset.",""
"turnover_recorded_music","method","A","Actual values",344,"No method applied.","[{""RelatedItem"":""Retrieval and Analysis of Eurostat Open Data with the eurostat Package "",""relatedItemType"":""Software"",""relationType"":""isCompiledBy"",""relatedItemIdentifier"":""https://ropengov.github.io/eurostat/"",""relatedItemIdentifierType"":""URL""}]"
"turnover_recorded_music","method","approx","Linear Approximation",7,"Replacing each missing item with interpolated values.","[{""RelatedItem"":""zoo: S3 Infrastructure for Regular and Irregular Time Series"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""DOI"",""relatedItemIdentifier"":""10.18637/jss.v014.i06""}]"
"turnover_recorded_music","method","Backcast ETS(A,A,N)","Exponential smoothing Backcast (A,A,N)",6,"Exponential smoothing with Holt’s linear method with additive errors.","[{""RelatedItem"":""{forecast}: Forecasting functions for time series and linear models"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""URL"",""relatedItemIdentifier"":""https://pkg.robjhyndman.com/forecast/""}]"
"turnover_recorded_music","method","Backcast ETS(A,N,N)","Exponential smoothing Backcast (A,N,N)",46,"Exponential smoothing (Additive trend, no seasonal component).","[{""RelatedItem"":""{forecast}: Forecasting functions for time series and linear models"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""URL"",""relatedItemIdentifier"":""https://pkg.robjhyndman.com/forecast/""}]"
"turnover_recorded_music","method","Backcast ETS(M,A,N)","Exponential smoothing Backcast (M,A,N)",2,"Exponential smoothing with the additive Holt’s linear method with multiplicative errors.","[{""RelatedItem"":""{forecast}: Forecasting functions for time series and linear models"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""URL"",""relatedItemIdentifier"":""https://pkg.robjhyndman.com/forecast/""}]"
"turnover_recorded_music","method","Backcast ETS(M,N,N)","Exponential smoothing Backcast (M,N,N)",22,"Exponential smoothing with simple exponential smoothing with multiplicative errors.","[{""RelatedItem"":""{forecast}: Forecasting functions for time series and linear models"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""URL"",""relatedItemIdentifier"":""https://pkg.robjhyndman.com/forecast/""}]"
"turnover_recorded_music","method","Forecast ETS(A,A,N)","Exponential smoothing Forecast (A,A,N)",6,"Exponential smoothing with Holt’s linear method with additive errors.","[{""RelatedItem"":""{forecast}: Forecasting functions for time series and linear models"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""URL"",""relatedItemIdentifier"":""https://pkg.robjhyndman.com/forecast/""}]"
"turnover_recorded_music","method","Forecast ETS(A,N,N)","Exponential smoothing Forecast (A,N,N)",32,"Exponential smoothing (Additive trend, no seasonal component).","[{""RelatedItem"":""{forecast}: Forecasting functions for time series and linear models"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""URL"",""relatedItemIdentifier"":""https://pkg.robjhyndman.com/forecast/""}]"
"turnover_recorded_music","method","Forecast ETS(M,N,N)","Exponential smoothing Forecast (M,N,N)",38,"Exponential smoothing with simple exponential smoothing with multiplicative errors.","[{""RelatedItem"":""{forecast}: Forecasting functions for time series and linear models"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""URL"",""relatedItemIdentifier"":""https://pkg.robjhyndman.com/forecast/""}]"
"turnover_recorded_music","method","nocb","Next Observation Carry Backwards",3,"Replacing each missing item with the next non-missing prior after it.","[{""RelatedItem"":""zoo: S3 Infrastructure for Regular and Irregular Time Series"",""relationType"":""isCompiledBy"",""relatedItemIdentifierType"":""DOI"",""relatedItemIdentifier"":""10.18637/jss.v014.i06""}]"
"turnover_recorded_music","method","O","Missing values",64,"No method applied.","[{""RelatedItem"":""dataobservaotry"",""relatedItemType"":""Software"",""relationType"":""isCompiledBy"",""relatedItemIdentifier"":""10.5281/zenodo.5034752"",""relatedItemIdentifierType"":""DOI""}]"
"turnover_recorded_music","obs_status","A","Normal value",344,"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.","[{""RelatedItem"":""SDMX Code List for Observation Status"",""relationType"":""IsDocumentedBy"",""relatedItemIdentifier"":""https://sdmx.org/?sdmx_news=new-version-of-code-list-for-observation-status-version-2-2/"",""relatedItemIdentifierType"":""URL""}]"
"turnover_recorded_music","obs_status","E","Estimated value",162,"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”.","[{""RelatedItem"":""SDMX Code List for Observation Status"",""relationType"":""IsDocumentedBy"",""relatedItemIdentifier"":""https://sdmx.org/?sdmx_news=new-version-of-code-list-for-observation-status-version-2-2/"",""relatedItemIdentifierType"":""URL""}]"
"turnover_recorded_music","obs_status","O","Missing value",64,"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.","[{""RelatedItem"":""SDMX Code List for Observation Status"",""relationType"":""IsDocumentedBy"",""relatedItemIdentifier"":""https://sdmx.org/?sdmx_news=new-version-of-code-list-for-observation-status-version-2-2/"",""relatedItemIdentifierType"":""URL""}]"
"turnover_recorded_music","observations_actual","gain","Information gain",0,"Actual observations in the  observatory dataset (gained.)",""
"turnover_recorded_music","observations_actual","gain_pct","Information gain (% increase)",0,"Actual observations in the  observatory dataset (% increase.)",""
"turnover_recorded_music","observations_actual","observatory","Observatory (processed) dataset",344,"Actual observations in the  observatory (processed) dataset.",""
"turnover_recorded_music","observations_actual","source","Source dataset",344,"Actual observations in the  source dataset.",""
"turnover_recorded_music","observations_estimated","gain","Information gain",162,"Estimated observations in the observatory dataset (gained.)",""
"turnover_recorded_music","observations_estimated","gain_pct","Information gain (% increase)",Inf,"Estimated observations in the observatory dataset (% increase.)",""
"turnover_recorded_music","observations_estimated","observatory","Observatory (processed) dataset",162,"Estimated observations in the observatory (processed) dataset.",""
"turnover_recorded_music","observations_estimated","source","Source dataset",0,"Estimated observations in the source dataset.",""
"turnover_recorded_music","observations_missing","gain","Information gain",-10,"Number of missing observations in the  observatory dataset (gained.)",""
"turnover_recorded_music","observations_missing","gain_pct","Information gain (% increase)",-0.135135135135135,"Number of missing observations in the  observatory dataset (% increase.)",""
"turnover_recorded_music","observations_missing","observatory","Observatory (processed) dataset",64,"Number of missing observations in the  observatory (processed) dataset.",""
"turnover_recorded_music","observations_missing","source","Source dataset",74,"Number of missing observations in the  source dataset.",""
"turnover_recorded_music","observations_reduced","gain","Information gain",148,"Total observations in the largest subset of the  observatory dataset (gained.)",""
"turnover_recorded_music","observations_reduced","gain_pct","Information gain (% increase)",0.611570247933884,"Total observations in the largest subset of the  observatory dataset (% increase.)",""
"turnover_recorded_music","observations_reduced","observatory","Observatory (processed) dataset",390,"Total observations in the largest subset of the  observatory (processed) dataset.",""
"turnover_recorded_music","observations_reduced","source","Source dataset",242,"Total observations in the largest subset of the  source dataset.",""
"turnover_recorded_music","time_periods_reduced","gain","Information gain",4,"Time periods in the largest subset of the  observatory dataset (gained.)",""
"turnover_recorded_music","time_periods_reduced","gain_pct","Information gain (% increase)",0.363636363636364,"Time periods in the largest subset of the  observatory dataset (% increase.)",""
"turnover_recorded_music","time_periods_reduced","observatory","Observatory (processed) dataset",15,"Time periods in the largest subset of the  observatory (processed) dataset.",""
"turnover_recorded_music","time_periods_reduced","source","Source dataset",11,"Time periods in the largest subset of the  source dataset.",""
"turnover_recorded_music",NA,"",NA,15,"Measured in na",""
"turnover_recorded_music",NA,"",NA,12,"Measured in na",""
"turnover_recorded_music",NA,"",NA,13,"Measured in na",""
"turnover_recorded_music",NA,"",NA,10,"Measured in na",""
"turnover_recorded_music",NA,"",NA,8,"Measured in na",""
"turnover_recorded_music",NA,"",NA,7,"Measured in na",""
"turnover_recorded_music",NA,"",NA,6,"Measured in na",""