Availability and Accessability |
Currency |
Reliability and Credibility |
Usability and Interpretability |
Semantic consistency
Compare with other Characteristic
Characteristic Name: | Semantic consistency |
Definition: | Data is semantically consistent |
Dimension: | Consistency |
Granularity: | Element |
Characteristic Type: | Declarative |
Implementation Form: | Rule-based approach |
Verification Metric:
The number of semantically inconsistent data reported per thousand records |
Validation Metric:
To what extent required rules have been identified and implemented to maintain the declarative characteristic in concern. |
BackgroundGuidelines
The original definitions given below formed the basis of the consolidated definition of the characteristic.
Definition: | Source: |
---|---|
Data about an object or event in one data store is semantically Equivalent to data about the same object or event in another data store. | ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing. More from this source |
Data is consistent if it doesn’t convey heterogeneity, neither in contents nor in form – anti examples: Order.Payment. Type = ‘Check’; Order. Payment. CreditCard_Nr = 4252… (inconsistency in contents); Order.requested_by: ‘European Central Bank’;Order.delivered_to: ‘ECB’ (inconsistency in form,because in the first case the customer is identified by the full name, while in the second case the customer’s acronym is used). | KIMBALL, R. & CASERTA, J. 2004. The data warehouse ETL toolkit: practical techniques for extracting. Cleaning, Conforming, and Delivering, Digitized Format, originally published. More from this source |
The extent of consistency in using the same values (vocabulary control) and elements to convey the same concepts and meanings in an information object. This also includes the extent of semantic consistency among the same or different components of the object. | STVILIA, B., GASSER, L., TWIDALE, M. B. & SMITH, L. C. 2007. A framework for information quality assessment. Journal of the American Society for Information Science and Technology, 58, 1720-1733. More from this source |
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
Guidelines: | Scenario: |
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Ensure that semantics of data is consistent within/across applications | (1) All orders placed by the customers are called “Sales order” in all tables/databases. (2) Anti-example: Payment type ( Check) Payment Details (Card type, Card number) |
Maintenance of data dictionary or standard vocabularies of data semantics | (1) Data dictionary provides technical data as well as semantics of data |
Availability and Accessability |
Currency |
Reliability and Credibility |
Usability and Interpretability |
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