Model validation: A bibliometric analysis of the literature

Eker, S. ORCID: https://orcid.org/0000-0003-2264-132X, Rovenskaya, E. ORCID: https://orcid.org/0000-0002-2761-3443, Langan, S. ORCID: https://orcid.org/0000-0003-0742-3658, & Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769 (2019). Model validation: A bibliometric analysis of the literature. Environmental Modelling & Software 117 43-54. 10.1016/j.envsoft.2019.03.009.

Preview

Text 1-s2.0-S1364815218312763-main.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (5MB) | Preview

Abstract

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.

Actions (login required)

View Item