ISO/IEC 5259

ISO/IEC 5259 describes a data quality model for data analytics and artificial intelligence based on machine learning (ML).

This standard is based on the ISO/IEC 25012 model, and like ISO/IEC 25012 differentiates between two types of characteristics: inherent and system-dependent, to which it adds a new category of additional characteristics.

Inherent Data Quality

The degree to which data has attributes that correctly represent the true value of the intended attribute of a concept or event in a specific context of use.
It has two main aspects:

• Syntactic Accuracy: Syntactic accuracy is defined as the closeness of the data values to a set of values defined in a domain considered syntactically correct.
• Semantic Accuracy: Semantic accuracy is defined as the closeness of the data values to a set of values defined in a domain considered semantically correct.

The degree to which subject data associated with an entity has values for all expected attributes and related entity instances in a specific context of use.

The degree to which data has attributes that are free from contradiction and are coherent with other data in a specific context of use. It can be either or both among data regarding one entity and across similar data for comparable entities.

The degree to which data has attributes that are regarded as true and believable by users in a specific context of use. Credibility includes the concept of authenticity (the truthfulness of origins, attributions, commitments).