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. 2015 Nov 5;2015:1937–1946.

Table 2:

Data Quality Ontology - Measure Detail

Concept Definition References / Synonyms
CorrectnessMeasure
RepresentationIntegrity Aspects of the Representation that reassure that data was not corrupted or subject to data entry errors. Correctness: Credibility of source6, Accuracy: …free of error11, Integrity18, Repeatability18, Structural Consistency23
RelativeCorrectness Assesses the quality of a Representation by comparing it to its counterpart in another Dataset which is a “relative standard”, computed as PPV. Accuracy: …conformity with actual value6, Correctness13, Believability11, Validity13,19, Comparability20,21, Accuracy10,13,18,23, Corrections made13, Errors13, Misleading13, PPV13, Quality13
RepresentationCorrectness A correct Representation has high accuracy and is complete. Correctness: …accuracy and completeness6, Accuracy20,21
Reliability The data is correct and suitable for the Task. Reliability6,1820, Accuracy: Measurement Error22
ConsistencyMeasure
RepresentationConsistency The data is a valid value and format for its Data Value Type and all of the Representations for the same information have the same values. Consistency: …values and physical representation of data6, Concordance13, Format11, Internal Consistency18, Consistency13, Precision20, Format11,20, Reliability13, Variation13, Accuracy: Edit and Imputation22, Representational Consistency10
DomainConsistency Concepts in the Domain are represented in the data and the data satisfies syntactic and semantic rules. Constraints for the Domain are satisfied. Accuracy: Refers to values and representation6, Correctness: …format and types are valid6, Plausibility13, Believability10,13, Relational Integrity Rules11, Consistency1820, Measure validity21, Accuracy13, Trustworthiness13, Validity13,23
CodingConsistency Representations that are of coded text data type must be correctly mapped to an enumerated list or a terminology. Consistency: …codes/terms…mapped to a reference terminology6, Valid values11, Comparability: Equivalency22, Semantic Consistency23
DomainMetadata Meta-data exists to describe the Domain and it is logically consistent. Methodological Clarity19, Metadata Documentation18, Comparability: Data dictionary standards22, Interpretability10
CompletenessMeasure
RepresentationComplete Domain independent extent to which data is not missing. Completeness: …information is not missing6, Completion19, Completeness18,21, Accuracy: Item Non-22
DomainComplete The extent to which information is present or absent as expected. Appropriate amount of data: Data are present or absent as expected13, Optionality11, Content20
RelativeCompleteness The extent to which a truth about the world is represented in the data. This is computed as sensitivity relative to another Dataset. Completeness: Is a truth…in the EHR?13, Accessibility10,13,19, Accuracy13, Availability13, Missingness13, Omission13, Presence13, Quality13, Rate of Recording13, Sensitivity13, Validity13
Sufficiency The data has sufficient Representations along a given dimension (i.e. time, patient, encounter) to perform the Task. Completeness: …sufficient breadth and depth for the task6, Appropriate amount of data11, Representativeness18, Sufficiency20, Accuracy: Coverage22, Granularity11,18, Continuity11, Level of Detail20, Completeness10,23, Precision23
DomainCoverage The data can represent the values and concepts required by the Domain. Completeness: …represent every meaningful state of the […] real world6, Completeness: All values for a variable are recorded6, Coverage19, Completeness20
TaskCoverage The data contains all of the information required by the Task. Completeness: …depict every possible state of the task6, Usableness18,20, Usability18, Utility18, Importance20, Usefulness20, Value-added10
Flexibility The extent to which the data is sufficient to be used by many Tasks. Consistency: …information…appl[ies] to different tasks6, Flexibility10,20, Relevance: Adaptability22
Relevance The data is sufficient for the Task and conforms to the Domain. Relevance6,18,20,23, Relevance: Value22, Relevancy10
CurrencyMeasure
RepresentationCurrent Calculation for time difference between when an observation was made and when it was entered into the system. Timeliness: delay between a change of the real-world state and…the information system6, Currency13,18,23, Timeliness13,18,20, Up-datedness18, Recency13
DatasetCurrent Time difference between when a Dataset was updated and when it was made available. For example, periodic updates to a repository. Timeliness: …availability of output is on time6, Opportunity19, Periodicity18, Currency11,20, Timeliness: Data currency22, Timeliness10
TaskCurrency The Data is sufficiently up-to-date for the requirements of the Task. Timeliness: …information is up to date for task6, Timeliness: …age of the data is appropriate for the task11, Timeliness (external)20