Model validation: A bibliometric analysis of the literature

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/87010 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/87010 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/87010 archive 353 disk0/00/01/58/11 2019-03-26 09:18:44 2021-08-27 17:31:34 2019-03-26 09:18:44 article show Eker S. 2173 0000-0003-2264-132X Rovenskaya E. 8206 0000-0002-2761-3443 Langan S. 2125 0000-0003-0742-3658 Obersteiner M. 7255 0000-0001-6981-2769 Model validation: A bibliometric analysis of the literature pub prog_asa prog_eep prog_esm prog_wat Model validation; Model evaluation; Model testing; Citation analysis; Text-mining analysis Validation is a crucial step in environmental and economic modeling that establishes the reliability of models to be used in decision-making contexts. It is often said that validation approaches proposed in the literature are not widely adopted, and different modeling fields do not benefit from each other. This study analyses a broad academic literature on model validation, mainly in environmental and decision sciences, by using an innovative combination of bibliometric and text-mining tools. The results show that a data-driven validation practice is prevalent. Although most publications in the studied dataset resemble each other, the most-cited ones tend to be different from the rest in terms of their abstracts’ content. Furthermore, the validation practices in different modeling areas are distinct, and do not extensively cite each other. In future, validation approaches can extend beyond data-oriented reliability for a wider acceptance of modeling in decision-making, and can synthesize the methods and views from various fields. 2019-07 published Elsevier 10.1016/j.envsoft.2019.03.009 2953 260 2691 219 public Environmental Modelling & Software 117 43-54 TRUE 1873-6726 FALSE no info:eu-repo/semantics/article