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'''Information quality (InfoQ)''' is the potential of a dataset to achieve a specific (scientific or practical) goal using a given empirical analysis method. | |||
InfoQ is different from ] and ], but is dependent on these components and on the relationship between them. Formally, the definition is InfoQ = U(X,f|g) where X is the data, f the analysis method, g the goal and U the utility function. | |||
There are various statistical methods for increasing InfoQ at the study-design and post-data-collection stages—how are these related to InfoQ? | |||
Kenett and Shmueli (2014) proposed eight dimensions to help assess InfoQ and various methods for increasing InfoQ: | |||
1) Data resolution | |||
2) ] | |||
3) Data integration | |||
4) Temporal relevance | |||
5) Chronology of data and goal | |||
6) ] | |||
7) ] | |||
8) Communication. | |||
Formalizing the concept of InfoQ increases the value of statistical analysis and data mining, both methodologically and practically | |||
The topic of information quality (InfoQ), as presented in this entry, has been applied in a wide range of domains. There are now publications on such applications in the context of healthcare, customer surveys, data science programs, advanced manufacturing and Bayesian network applications, to name a few. The topic is of special importance in the context of data science programs mostly driven by computer science perspectives. It brings in a complementary perspective that emphasizes a wide application perspective. | |||
A detailed introduction to InfoQ with examples from healthcare, education, official statistics, customer surveys and risk management is available in the book by Kenett and Shmueli, , John Wiley and Sons, 2016. | |||
==References== | |||
{{reflist}} | |||
* , Kenett, R.S. and Shmueli, G., John Wiley and Sons, 2016. | |||
* , Shmueli, G. and Kenett, R.S., Proceedings of the 3rd International Workshop on Intelligent Data Analysis and Management, Kaohsiung, Taiwan, Springer Proceedings in Complexity, Eds. L Uden, L SL Wang, T-P Hong, H-C Yang and I-H Ting, pp. 1–13, 2013 | |||
* Chapter 1: The Role of Statistical Methods in Modern Industry and Services, in Kenett, R.S. and Zacks, S., , Second Edition, John Wiley and Sons, 2014 | |||
* Chapter 1: Risk management: a general view, in Kenett, R.S. and Raanan, Y., , John Wiley and Sons, 2011 | |||
* From Data to Information to Knowledge, Kenett, R.S., Six Sigma Forum Magazine, 2008 | |||
* , Kenett, R.S. and Salini, S., John Wiley and Sons, 2011 | |||
* , Kenett, R.S. and Salini, S., Applied Stochastic Models in Business and Industry, 2011 | |||
* , Cugnata, F., Kenett R.S. and Salini S., Procedia Economics and Finance, 2014 | |||
* , Kenett, R.S., Quality Engineering, 2015 http://ssrn.com/abstract=2315556 | |||
* , Kenett, R.S. and Shmueli, G., Nature Methods, Vol. 12(8), p 699, 2015 | |||
* , Dalla Valle L. and Kenett R.S., Quality and Reliability Engineering International, 2015 | |||
* , Kenett, R.S. and Shmueli, G., Journal of the Royal Statistical Society, Series A, vol 177 issue 1, pp. 3–38, 2014, http://ssrn.com/abstract=2128547 | |||
* , Kenett, R.S., Quality Technology and Quantitative Management, 2016 | |||
* , Kenett R.S. and Shmueli G., Journal of the International Association for Official Statistics, 2016 | |||
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