Analysis of Gross Methodological Errors in Webometrics Ranking Data (July 2025) Using Yemeni Universities as a Case Study

This paper presents a critical analysis of the dataset for the Webometrics Ranking of World Universities, July 2025 edition, as published by Aguillo (2025) . Focusing on Yemeni universities as a case study, the analysis reveals multiple patterns of gross errors in the assignment of Research Organization Registry (ROR) identifiers. The study documents "chained errors," where identifiers are incorrectly swapped among several universities, in addition to cases of complete omission of universities or the failure to assign their correct, existing identifiers. All findings presented herein are based on the published data from the specified source. These profound methodological flaws raise fundamental doubts about the data validation mechanisms of the Webometrics ranking and directly impact the fairness and credibility of its results.