Precision

Precision

Compare with other Characteristic

Characteristic Name: Precision
Definition: Attribute values should be accurate as per linguistics and granularity
Dimension: Accuracy
Granularity: Element
Characteristic Type: Declarative
Implementation Form: Rule-based approach

Verification Metric:

The number of tasks failed or under performed due to lack of data precision
The number of complaints received due to lack of data precision

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 values are correct to the right level of detail or granularity, such as price to the penny or weight to the nearest tenth of a gram. ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing. More from this source
Data is correct if it conveys a lexically, syntactically and semantically correct statement – e.g.,the following pieces of information are not correct:“Germany is an African country” (semantically wrong);Book.title: ‘De la Mancha Don Quixote’ (syntactically wrong); UK’s Prime Minister: ‘Toni Blair’ (lexically wrong). 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 set S should be sufficiently precise to distinguish among elements in the domain that must be distinguished by users. This dimension makes clear why icons and colors are of limited use when domains are large. But problems can and do arise for the other formats as well, because many formats are not one-to-one functions. For example, if the domain is infinite (the rational numbers, for example), then no string format of finite length can represent all possible values. The trick is to provide the precision to meet user needs. LOSHIN, D. 2001. Enterprise knowledge management: The data quality approach, Morgan Kaufmann Pub. More from this source
Is the information to the point, void of unnecessary elements? LOSHIN, D. 2006. Monitoring Data quality Performance using Data Quality Metrics. Informatica Corporation. More from this source
The degree of precision of the presentation of an attribute’s value should reasonably match the degree of precision of the value being displayed. The user should be able to see any value the attributer may take and also be able to distinguish different values. REDMAN, T. C. 1997. Data quality for the information age, Artech House, Inc. More from this source
The granularity or precision of the model or content values of an information object according to some general-purpose IS-A ontology such as WordNet. 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:
Ensure the data values are correct to the right level of detail or granularity (1) Price to the penny or weight to the nearest tenth of a gram.
(2) precision of the values of an attribute according to some general-purpose IS-A ontology such as WordNet
Ensure that data is legitimate or valid according to some stable reference source like dictionary/thesaurus/code. (1) Spellings and syntax of a description is correct as per the dictionary/thesaurus/Code (e.g. NYSIIS Code)
(2) Address is consistent with global address book
Ensure that the user interfaces provide the precision required by the task (1) if the domain is infinite (the rational numbers, for example), then no string format of finite length can represent all possible values.
Ensure the data values are lexically, syntactically and semantically correct (1) “Germany is an African country” (semantically wrong); Book.title: ‘De la Mancha Don Quixote’ (syntactically wrong); UK’s Prime Minister: ‘Toni Blair’ (lexically wrong)

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