Objectivity

Objectivity

Compare with other Characteristic

Characteristic Name: Objectivity
Definition: Data are unbiased and impartial
Dimension: Reliability and Credibility
Granularity: Information object
Characteristic Type: Usage
Implementation Form: Process-based approach

Verification Metric:

The number of tasks failed or under performed due to biased and partial data
The number of complaints received due to biased or partial data

Validation Metric:

To what extent required capabilities and skills have been implemented to improve the data usage of a task

BackgroundGuidelines

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

Definition: Source:
The degree to which Information is presented without bias, enabling the Knowledge Worker to understand the meaning and significance without misinterpretation. 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 free of distortion, bias, or error? EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. More from this source
1) Data are unbiased and impartial

2) Objectivity is the extent to which data are unbiased (unprejudiced) and impartial.

WANG, R. Y. & STRONG, D. M. 1996. Beyond accuracy: What data quality means to data consumers. Journal of management information systems, 5-33. 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:
Identify all the factors that make a particular data/information biased for the intended use and take preventive actions to eliminate them (1) A written questionnaire is better than a face to face interviews in getting sensitive personal data
Design and execute preventive actions for all possible information distortions (malfunctioning or personal biases) which may cause by information /data collectors Perform a duel coder approach to code qualitative data.
Design and execute preventive actions for all possible information distortions (malfunctioning or personal biases) which may cause by information /data transmitters (1) After a survey is performed, each participant is contacted individually by a party (other than the person who conducted the survey) and randomly verify if the participants real responses have been marked properly.

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