Reasonability
The degree to which a data pattern meets expectations.
Referential integrity
The degree to which data values of the primary key of one data file and data values of the foreign key of another data file are equal.
Granularity (Attributes)
The degree to which a single characteristic is subdivided in attributes.
Ability to represent null values
The degree to which a format allows null values in an attribute.
Portability (Data)
The degree to which data can be installed, replaced or moved from one system to another while preserving the existing quality.
Redundancy
The degree to which logically identical data are stored more than once.
Validity
The degree to which data values comply with rules.
Reputation
The degree to which data are trusted or highly regarded in terms of their source or content.
Clarity
The ease with which data consumers can understand the metadata.
Completeness (Attributes)
The degree to which all required attributes in the dataset are present.
Access security
The degree to which access to datasets is restricted.
Value
The degree to which data provide advantages from their use.
Recoverability
The degree to which datasets are preserved in the event of incident.
Consistency (Across Datasets)
The degree to which data values of two sets of attributes between datasets comply with a rule.
Equivalence
The degree to which attributes stored in multiple datasets are conceptually equal.
Availability
The degree to which data can be consulted or retrieved by data consumers or a process.
Completeness (Data files)
The degree to which all required data files are present.
Credibility
The degree to which data values are regarded as true and believable by data consumers.
Retention period
The period that datasets are available until they can or must be deleted.
Reproducibility
The degree to which a dataset can be recreated with the same data values.
Portability (Format)
The degree to which a format can be applied in a wide range of situations.
Linkability
The degree to which records of one data file can be correctly coupled with records of another data file.
Punctuality
The degree to which the period between the actual and target point of time of availability of a dataset is appropriate.
Integrity
The degree of absence of data value loss or corruption.
Obtainability
The degree to which the data can be acquired.
Uniqueness (Objects)
The degree to which objects (of the real world) occur only once as a record in a data file.
Volatility
The degree to which data values change over time.
Relevance
The degree to which the composition of datasets meets the needs of the data consumer.
Traceability
The degree to which data lineage is available.
Plausibility
The degree to which data values match knowledge of the real world.
Precision (1 - Recording Accuracy)
The degree of accuracy with which data values are recorded or classified.
Consistency (Cross-Record)
The degree to which data values of two sets of attributes between records comply with a rule.
Consistency (Record-Level)
The degree to which data values of two sets of attributes within a record comply with a rule.
Coherence
The degree to which datasets can be combined.
Comparability of populations
The degree to which data values representing two populations have the same definition and are measured in the same way.
Confidentiality
The degree to which disclosure of data should be restricted to authorized data consumers.
Uniqueness (Records)
The degree to which records occur only once in a data file.
Variety
The degree to which data are available from different data sources.
Naturalness
The degree to which the composition of datasets is aligned with the real-world objects that they represent.
Appropriateness
The degree to which the format is suitable for use.
Completeness (Metadata)
The degree to which the metadata are fully described.
Granularity (Records)
The degree to which objects are aggregated to records.
Completeness (Data values)
The degree to which all required data values are present.
Compliance with laws, regulations, or standards (Composition of datasets)
The degree to which the composition of datasets is in accordance with laws, regulations, or standards.
Consistency (Temporal)
The degree to which the data values of a set of attributes of a dataset at different points in time comply with a rule.
Consistency (Data values)
The degree to which data values of two sets of attributes comply with a rule.
Completeness (Records)
The degree to which all required records in the dataset are present.
Interpretability
The degree to which data are in an appropriate language and units of measure.
Completeness (Data values of an attribute)
The degree to which all required data values of an attribute are present.
Compliance with laws, regulations, or standards (Data)
The degree to which data is in accordance with laws, regulations, or standards.