COMMISSION IMPLEMENTING REGULATION (EU) 2021/2225
of 16 November 2021
laying down the details of the automated data quality control mechanisms and procedures, the common data quality indicators and the minimum quality standards for storage of data, pursuant to Article 37(4) of Regulation (EU) 2019/817 of the European Parliament and of the Council
Article 1
Scope and subject matter
Article 2
Definitions
Article 3
Automated data quality control mechanisms and procedures
Article 4
Automated data quality control mechanisms for data entered and stored
Article 5
Procedures governing the data quality control indicators, standards and mechanisms
Article 6
Reports on automated data quality control mechanisms and procedures and common data quality indicators pursuant to Article 37(3) of Regulation (EU) 2019/817
Article 7
Entry into force
ANNEX
SECTION 1
Automated data quality control mechanism for data to be entered
SECTION 2
General considerations on the common data quality indicators and minimum quality standards for data to be entered
Indicator |
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 is provided and the database (or sectoral) listings meet the set demands. |
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. It can be either or both among data regarding one entity and across similar data for comparable entities |
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. It can be either or both among data regarding one entity and across similar data for comparable entities. |
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 the input data is not duplicated in the same EU information system or interoperability component. |
Mandatory data fields (alphanumeric and biometric) |
Percentage of data units which are not duplicated |