With the adoption of the European Statistics Code of Practice (in 2005) Eurostat and the statistical authorities of the EU Member States have committed themselves to an encompassing approach towards high quality statistics. The Code builds upon a common definition of quality (which was developed and accepted within the European Statistical System) and targets all relevant areas: institutional environment, statistical processes and statistical outputs. .
The Code is nowadays a recommendation which should be followed as much as possible; Member States and Eurostat should regularly report on implementation to the European Commission. The first report for 2005 was done in the form of a self-assessment questionnaire. As the next step towards the implementation of the Code, Eurostat organised peer reviews to complement the self-assessments. They are considered a vital element for the implementation of the Code in practice given their capacity to encourage the sharing of best practice and to contribute to better transparency of the whole statistical system. The peer review reports from all countries are available on Eurostat's website.
Data Quality Components
SORS adopted the Eurostat’s common quality definition. According to this definition the quality of statistical data is composed of the following six components:
- Relevance.Relevance is the degree to which statistics meet current and potential user needs. It refers to whether all statistics that are needed are produced and the extent to which concepts used (definitions, classifications, etc.) reflect user needs.
- Accuracy. In the general statistical sense this concept denotes the closeness of computations or estimates to the (unknown) exact or true values. Statistical data are namely not equal to the true values because of variability (values vary due to random effects/errors that appear at the implementation of the survey) and bias (values vary due to systematic effects/errors that appear at the implementation of the survey).
- Timeliness and punctuality. Timeliness of publication reflects the length of time between the period when the statistical phenomenon was observed and the release date of data. Punctuality refers to the time lag between the announced date of publication (for example in the release calendar) and the actual release date of data.
- Comparability. Used concepts should be harmonized, so that the obtained data and information are comparable over time, between geographical areas and between domains.
- Coherence. Coherence of statistics is their adequacy to be reliably combined in different ways and for various uses. The problems with coherence can occur when data originate from different sources or from different statistical surveys, where the used concepts, classifications and methodological standards are not harmonized.
- Accessibility and clarity. Accessibility refers to the physical conditions for users to access the statistical data: where and how it is possible to order data, delivery time, how much it costs (clear pricing policy), access to microdata and metadata, availability in various formats. Clarity refers to the environment in which the data are presented: are data accompanied by appropriate metadata, by graphical presentations, by information on their quality and by information about the extent to which additional assistance is provided by the national statistical institute.
Besides the mentioned quality components, SORS also adds a seventh component, costs and burdens. This component measures the cost efficiency of statistical surveys and the burden of reporting units (data providers) when they report the demanded data for statistical purposes.
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