// Workers AI · dad joke modeWhy did InfoQ go to therapy? It had too much info to queue.
Information quality (InfoQ) is the extent to which a data set can help achieve a specific scientific or practical goal when it is used with a particular empirical analysis method.
Definition
[edit]InfoQ is often expressed as InfoQ = U(X,f|g), where X is the data, f is the analysis method, g is the goal, and U is the utility function. In simpler terms, it describes how useful a given set of data is for answering a particular question with a particular method. InfoQ is related to both data quality and analysis quality, but it is not the same as either one; it depends on the quality of the data, the suitability of the analysis, and how well the data, method, and goal fit together.
InfoQ has been applied in fields including healthcare, customer surveys, data science programmes, advanced manufacturing, and Bayesian network applications.
Kenett and Shmueli (2014) proposed eight dimensions to help assess InfoQ and various methods for increasing InfoQ: data resolution, data structure, data integration, temporal relevance, chronology of data and goal, generalization, operationalization, and communication. [1] [2] [3]
References
[edit]- ↑ Kenett, Ron S.; Shmueli, Galit (19 December 2016). Information Quality: The Potential of Data and Analytics to Generate Knowledge. John Wiley & Sons. pp. 9–. ISBN 978-1-118-87444-8.
- ↑ Kenett, Ron S.; Shmueli, Galit (2014). "On information quality". Journal of the Royal Statistical Society. Series A (Statistics in Society). 177 (1): 3–38. doi:10.1111/rssa.12007. ISSN 0964-1998. S2CID 62901580.
- ↑ Kenett, Ron S. (2016). "On generating high InfoQ with Bayesian networks". Quality Technology & Quantitative Management. 13 (3): 309–332. doi:10.1080/16843703.2016.1189182. ISSN 1684-3703. S2CID 63700188.
 | This statistics-related article is a stub. You can help Wikipedia by adding missing information. |