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Optimization, Control, and Applications in the Information AgeThree Aspects of the Research Impact by a Scientist: Measurement Methods and an Empirical Evaluation

Optimization, Control, and Applications in the Information Age: Three Aspects of the Research... [Three different approaches for evaluation of the research impact by a scientist are considered. Two of them are conventional ones, scoring the impact over (a) citation metrics and (b) merit metrics. The third one relates to the level of results. It involves a taxonomy of the research field, that is, a hierarchy representing its composition. The impact is evaluated according to the taxonomy ranks of the subjects that have emerged or have been crucially transformed due to the results by the scientist under consideration Mirkin (Control Large Syst Spec Issue 44:292–307, 2013). To aggregate criteria in approaches (a) and (b) we use an in-house automated criteria weighting method oriented towards as tight a representation of the strata as possible Orlov (Bus Inf, 2014). To compare the approaches empirically, we use publicly available data of about 30 scientists in the areas of data analysis and machine learning. As our taxonomy of the field, we invoke a corresponding part of the ACM Computing Classification System 2012 and slightly modify it to better reflect results by the scientists in our sample. The obtained ABC stratifications are rather far each other. This supports the view that all the three approaches (citations, merits, taxonomic rank) should be considered as different aspects, and, therefore, a good method for scoring research impact should involve all the three.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Optimization, Control, and Applications in the Information AgeThree Aspects of the Research Impact by a Scientist: Measurement Methods and an Empirical Evaluation

Part of the Springer Proceedings in Mathematics & Statistics Book Series (volume 130)
Editors: Migdalas, Athanasios; Karakitsiou, Athanasia

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References (29)

Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2015
ISBN
978-3-319-18566-8
Pages
233 –259
DOI
10.1007/978-3-319-18567-5_12
Publisher site
See Chapter on Publisher Site

Abstract

[Three different approaches for evaluation of the research impact by a scientist are considered. Two of them are conventional ones, scoring the impact over (a) citation metrics and (b) merit metrics. The third one relates to the level of results. It involves a taxonomy of the research field, that is, a hierarchy representing its composition. The impact is evaluated according to the taxonomy ranks of the subjects that have emerged or have been crucially transformed due to the results by the scientist under consideration Mirkin (Control Large Syst Spec Issue 44:292–307, 2013). To aggregate criteria in approaches (a) and (b) we use an in-house automated criteria weighting method oriented towards as tight a representation of the strata as possible Orlov (Bus Inf, 2014). To compare the approaches empirically, we use publicly available data of about 30 scientists in the areas of data analysis and machine learning. As our taxonomy of the field, we invoke a corresponding part of the ACM Computing Classification System 2012 and slightly modify it to better reflect results by the scientists in our sample. The obtained ABC stratifications are rather far each other. This supports the view that all the three approaches (citations, merits, taxonomic rank) should be considered as different aspects, and, therefore, a good method for scoring research impact should involve all the three.]

Published: Apr 22, 2015

Keywords: Evaluation of research impact; Citation index; Merit metrics; Aggregate criteria; Linstrat method; Multicriteria analysis

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