COMMISSION IMPLEMENTING DECISION (EU) 2022/2413
of 5 December 2022
on the mechanism and the procedures for carrying out quality checks and appropriate requirements for data quality compliance, and the specification of quality standards pursuant to Regulation (EC) No 767/2008 of the European Parliament and of the Council
Article 1
Scope
Article 2
Definitions
Article 3
Data-quality compliance mechanism and procedures
Article 4
Special provisions for blocking rules and for soft rules
Article 5
General requirements for ensuring data quality compliance
Article 6
Reports on data quality compliance
Article 7
Maintenance of data quality mechanism and procedures
Article 8
Entry into force and applicability
ANNEX
1.
Data-quality compliance mechanism for data to be entered
2.
Data-quality indicators for data to be entered
Indicators |
Description |
Main scope of applicability |
Unit of measurement |
Completeness |
Means the degree to which the input data has values for all the expected attributes and related requirements in a specific context of use. Measures whether all the mandatory data are provided. |
Mandatory data fields (alphanumeric and biometric) |
Data completeness rate: ratio of the number of data cells provided to the number of data cells required |
Accuracy |
Means the degree to which the input data represents closeness of estimates to the unknown true values. |
Alphanumeric and biometric data |
Sampling error rates, unit non-response rate, item non-response rate, data capture error rates, etc. |
Consistency |
Means the degree to which the input data has attributes that are free from contradiction and are coherent with other data in a specific context of use. Measures the degree to which a set of data satisfies defined business rules applying to those data across them, means the absence of a conflict of data content. |
Alphanumeric data |
Percentage |
Timeliness |
Means the degree to which the input data is provided within a predefined date or time that condition the validity of the data or its context of use. Measures how up-to-date the data is, and whether the data required can be provided by the required time. |
Alphanumeric and biometric data |
Time lag -final: number of days from the last day of the reference to the day the input data is provided |
Uniqueness |
Means the degree to which two separate records will not be identical based on all fields. |
Alphanumeric and biometric data |
Percentage of data units which are not identical |