ANNEX I
STRUCTURE AND CONTENTS OF THE QUALITY REPORTS
The quality reports shall contain quality-related data and metadata in line with the following quality criteria and statistical concepts. If a particular statistical concept is not relevant to a statistical operation, the concept should remain in the quality report accompanied by the words ‘Not applicable’ and a short explanation.
Statistical presentation
Description of the disseminated data.
This concept includes the following sub-concepts:
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Data description
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Classification system
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Sector coverage
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Statistical concepts and definitions
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Statistical unit
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Statistical population
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Reference area
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Time coverage
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Base period
Unit of measure
The unit in which the data values are measured.
Reference period
The period of time or point in time to which the measured observation is intended to refer.
Institutional mandate
Law, set of rules or other formal set of instructions assigning responsibility as well as the authority to an organisation for the collection, processing and dissemination of statistics.
This concept includes the following sub-concepts:
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Legal acts and other agreements
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Data sharing
Confidentiality
A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.
This concept includes the following sub-concepts:
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Confidentiality – policy
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Confidentiality – data treatment
Release policy
Rules for disseminating statistical data to all interested parties.
This concept includes the following sub-concepts:
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Release calendar
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Release calendar access
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User access
Frequency of dissemination
The time interval at which the statistics are disseminated over a given time period.
Accessibility and clarity
The conditions and modalities by which users can access, use and interpret data.
This concept includes the following sub-concepts:
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News release
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Publications
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Online database
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Other
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Documentation on methodology
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Metadata completeness – rate
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Quality documentation
Quality management
Systems and frameworks in place within an organisation to manage the quality of statistical products and processes.
This concept includes the following sub-concepts:
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Quality assurance
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Quality assessment
Relevance
The degree to which statistical information meets current and potential needs of users.
This concept includes the following sub-concepts:
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User needs
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User satisfaction
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Completeness
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Data completeness – rate for producers
Accuracy and reliability
Accuracy of data is the closeness of computations or estimates to the exact or true values that the statistics were intended to measure.
Reliability of the data is the closeness of the initial estimated value to the subsequent estimated value.
Timeliness and punctuality
Timeliness is the length of time between the event or phenomenon the data describe and the availability of the data.
Punctuality is the time lag between the target date when data should have been delivered and the actual delivery of the data.
This concept includes the following sub-concepts:
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Timeliness
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Time lag – first results for producers
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Punctuality – delivery and publication for users
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Punctuality – delivery and publication for producers
Coherence and comparability
The adequacy of statistics to be reliably combined in different ways and for various uses and the extent to which differences between statistics can be attributed to differences between the true values of the statistical characteristics.
This concept includes the following sub-concepts:
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Comparability – geographical
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Comparability – over time and length of comparable time series for users
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Length of comparable time series for producers
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Coherence – cross-domain
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Coherence – sub-annual and annual statistics
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Coherence – National Accounts
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Coherence – internal
Cost and burden
Cost associated with the collection and production of a statistical product and burden on respondents.
Data revision
Any change in a value of a statistic released to the public.
This concept includes the following sub-concepts:
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Data revision – policy
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Data revision – practice
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Data revision – average absolute size
Statistical processing
This concept includes the following sub-concepts:
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Source data
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Frequency of data collection
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Data collection
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Data validation
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Data compilation
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Adjustment