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{{Short description|Potential of a data set}}
{{multiple issues|
{{For|quality of information in a more general sense|Information quality}}
{{dead end|date=August 2016}}
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{{technical|date=September 2018}}
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'''Information quality''' ('''InfoQ''') is the potential of a [[data set]] to achieve a specific (scientific or practical) goal using a given [[Empirical research|empirical analysis method]].
{{orphan|date=August 2016}}
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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 data quality and analysis quality, 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) Data structure
3) Data integration
4) Temporal relevance
5) Generalizability
6) Chronology of data and goal
7) Operationalization
8) Communication.
Formalizing the concept of InfoQ increases the value of statistical analysis and data mining, both methodologically and practically
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, [http://www.wiley.com/go/information_quality Information Quality: The Potential of Data and Analytics to Generate Knowledge], John Wiley and Sons, 2016.
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==References==
⚫
{{reflist}}
⚫
* [http://www.wiley.com/go/information_quality Information Quality: The Potential of Data and Analytics to Generate Knowledge], Kenett, R.S. and Shmueli, G., John Wiley and Sons, 2016.
* [http://link.springer.com/chapter/10.1007/978-94-007-7293-9_1#page-1 An Information Quality (InfoQ) Framework for Ex-Ante and Ex-Post Evaluation of Empirical Studies], Shmueli, G. and Kenett, R.S., Proceeding 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., [http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1118456068.html Modern Industrial Statistics: with applications in R, MINITAB and JMP], Second Edition, John Wiley and Sons, 2014
* Chapter 1: Risk management: a general view, in Kenett, R.S. and Raanan, Y., [http://eu.wiley.com/WileyCDA/WileyTitle/productCd-047074748X.html Operational Risk Management: A Practical Approach to Intelligent Data Analysis], John Wiley and Sons, 2011
* From Data to Information to Knowledge, Kenett, R.S., Six Sigma Forum Magazine, 2008
* [http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470971282.html Modern Analysis of Customer Surveys with Applications using R], Kenett, R.S. and Salini, S., John Wiley and Sons, 2011
* [http://onlinelibrary.wiley.com/doi/10.1002/asmb.927/full Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis], Kenett, R.S. and Salini, S., Applied Stochastic Models in Business and Industry, 2011
* [http://www.sciencedirect.com/science/article/pii/S2212567114008715 Bayesian Network Applications to Customer Surveys and InfoQ], Cugnata, F., Kenett R.S. and Salini S., Procedia Economics and Finance, 2014
* [http://www.tandfonline.com/doi/abs/10.1080/08982112.2015.968054?journalCode=lqen20 Statistics: A Life Cycle View], Kenett, R.S., Quality Engineering, 2015 http://ssrn.com/abstract=2315556
* [http://www.nature.com/nmeth/journal/v12/n8/full/nmeth.3489.html Clarifying the terminology that describes scientific reproducibility], Kenett, R.S. and Shmueli, G., Nature Methods, Vol. 12(8), p 699, 2015
* [http://onlinelibrary.wiley.com/doi/10.1002/qre.1859/abstract Official Statistics Data Integration for Enhanced Information Quality], Dalla Valle L. and Kenett R.S., Quality and Reliability Engineering International, 2015
* [http://onlinelibrary.wiley.com/doi/10.1111/rssa.12007/abstract On Information Quality], 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
* [http://www.tandfonline.com/doi/full/10.1080/16843703.2016.1189182 On Generating High InfoQ with Bayesian Networks], Kenett, R.S., Quality Technology and Quantitative Management, 2016
* [http://content.iospress.com/articles/statistical-journal-of-the-iaos/sji967 Helping Reviewers Ask the Right Questions: The InfoQ Framework for Reviewing Applied Research], Kenett R.S. and Shmueli G., Journal of the International Association for Official Statistics, 2016


== Definition ==
Formally, the definition is <code>InfoQ = U(X,f|g)</code> where X is the data, f the analysis method, g the goal and U the utility function. InfoQ is different from [[data quality]] and [[Efficiency (statistics)|analysis quality]], but is dependent on these components and on the relationship between them.
⚫
InfoQ has been applied in a wide range of domains like healthcare, customer surveys, data science programs, advanced manufacturing and Bayesian network applications.


Kenett and [[Galit Shmueli|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]], Communication.
<ref>{{cite book
| first1=Ron S.
| last1=Kenett
| first2=Galit
| last2=Shmueli
| author2-link= Galit Shmueli
⚫
| title=Information Quality: The Potential of Data and Analytics to Generate Knowledge
| date=19 December 2016
| publisher=John Wiley & Sons
| pages=9–
| isbn=978-1-118-87444-8}}</ref>
<ref>{{cite journal
| first1=Ron S.
| last1=Kenett
| first2=Galit
| last2=Shmueli
| title=On information quality
| journal=Journal of the Royal Statistical Society. Series A (Statistics in Society)
| volume=177
| issue=1
| year=2014
| pages=3–38
| issn=0964-1998
| doi=10.1111/rssa.12007| s2cid=62901580
| doi-access=free
}}</ref>
<ref>{{cite journal
| last1=Kenett
| first1=Ron S.
| title=On generating high InfoQ with Bayesian networks
| journal=Quality Technology & Quantitative Management
| volume=13
| issue=3
| year=2016
| pages=309–332
| issn=1684-3703
| doi=10.1080/16843703.2016.1189182| s2cid=63700188
}}</ref>

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==References==
⚫
{{reflist}}


[[Category:Data]] [[Category:Statistics]][[Category:Research methods]][[Category:Information]]
[[Category:Data]]
[[Category:Research methods]]
[[Category:Statistical analysis]]
[[Category:Information]]


{{statistics-stub}}
{{improve categories|date=August 2016}}

Latest revision as of 21:22, 8 November 2023

For quality of information in a more general sense, see Information quality.

Information quality (InfoQ) is the potential of a data set to achieve a specific (scientific or practical) goal using a given empirical analysis method.

Definition

[edit]

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. InfoQ is different from data quality and analysis quality, but is dependent on these components and on the relationship between them.

InfoQ has been applied in a wide range of domains like healthcare, customer surveys, data science programs, 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, Communication. [1] [2] [3]

References

[edit]
  1. ^ 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.
  2. ^ 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.
  3. ^ 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.
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