Accuracy to reality

Accuracy to reality

Compare with other Characteristic

Characteristic Name: Accuracy to reality
Definition: Data should truly reflect the real world
Dimension: Accuracy
Granularity: Record
Characteristic Type: Usage
Implementation Form: Process-based approach

Verification Metric:

The number of tasks failed or under performed due to lack of accuracy to reality
The number of complaints received due to lack of accuracy to reality

BackgroundGuidelines

The original definitions given below formed the basis of the consolidated definition of the characteristic.

Add your own reference

Definition: Source:
Determines the extent to which data objects correctly represent the real-world values for which they were designed. For example, the sales orders for the Northeast region must be assigned a Northeast sales representative. D. McGilvray, “Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information”, Morgan Kaufmann Publishers, 2008. More from this source
The data value correctly reflects the real-world condition. B. BYRNE, J. K., D. MCCARTY, G. SAUTER, H. SMITH, P WORCESTER 2008. The information perspective of SOA design Part 6:The value of applying the data quality analysis pattern in SOA. IBM corporation. More from this source
The data correctly reflects the Characteristics of a Real-World Object or Event being described. Accuracy and Precision represent the highest degree of inherent Information Quality possible. ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing. More from this source
Is the information precise enough and close enough to reality? EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. More from this source
1) Each identifiable data unit maps to the correct real-world phenomenon.

2) Non-identifying (i.e. non-key) attribute values in an identifiable data unit match the property values for the represented real-world phenomenon.

3) Each identifiable data unit represents at least one specific real-world phenomenon.

4) Each identifiable data unit represents at most one specific real-world phenomenon.

 PRICE, R. J. & SHANKS, G. Empirical refinement of a semiotic information quality framework. System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual Hawaii International Conference on, 2005. IEEE, 216a-216a. More from this source
1) The degree to which an information object correctly represents another information object, process, or phenomenon in the context of a particular activity or culture.

2) Closeness of agreement between a property value and the true value (value that characterizes a characteristic perfectly defined in the conditions that exists when the characteristic is considered.

3) The extent to which the correctness of information is verifiable or provable in the context of a particular activity.

 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:
Continuously evaluate if the existing data model is sufficient to represent the real world as required by the organisational need and do the necessary amendments to the data model if needed. (1) A student who received a concession travel card is not eligible for a concession fare if he terminates his candidature before completion of the course. Hence the data model should have an extra attribute as "current status of candidature"
Perform regular audits on mission critical data to verify that every record has a meaningful existence in the reality which is useful for the organisation (1) All customers existing in the customer master file actually a customer in the customer space open for the organisation. (non customers are not in the customer file) (2) "Greg Glass" is recorded as a glass work company but in fact they are opticians
(3) A person's personal details taken from his educational profile may not be a correct reality for his insurance profile even though the information is
Perform regular audits on mission critical data to verify that every record has a unique existence in the reality (1) It is difficult to find out that the professor "Andrew" is from Colombia university or from the university of Queensland
Ensure that Information available in the system is accurate in the context of a particular activity or event (1) The driver details taken from vehicle registration may not be accurate in the case of finding the real person who drive the vehicle when an accident is caused

 

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