Bibliometric review of measurement uncertainty: Research classification and future tendencies

This paper highlights the importance of measurement uncertainty in science, engineering, and technology, to ensure accurate and reliable measurements. A bibliometric analysis that examines current trends, challenges, and future research directions in measuring uncertainty, based on the analysis of selected papers published between 2011 and 2022 sourced from the Scopus database, has been conducted. This study also classifies the papers based on the different approaches identified and the different methods of calculating uncertainty used by the authors. From the results of co-occurrence keyword analysis of the filtered 406 papers, six clusters corresponding to six research themes were obtained. Although the Law of Propagation of Uncertainty (LPU) method is still the most widely used method, it is also the most frequently criticised for its limitations, prompting many authors to compare it with other methods or propose improvements. This review also concludes that the Monte Carlo method (MCM) is a method for evaluating measurement uncertainty other than LPU whose use has increased significantly in the last decade.