Assessing research productivity in addiction datasets using OpenAlex

Abstract

The Open Science model has fostered new communication and archiving processes, supported by information technology. Within this framework, the open deposit of health-related datasets and their use in evaluating researchers and institutions are encouraged, with emerging information systems offering open alternatives to traditional databases. This study aims to analyse OpenAlex as a tool for retrieving research-derived datasets in a pilot study in the field of addictive substances, to determine whether it serves to automatically evaluate researchers and institutions inherent in the retrieved datasets. Results show that four repositories accounted for 85.8% of the 2782 datasets related to the addictive substances, being 30% of the records properly datasets followed by Comments on scientific investigation (21.4%), Monographs (15.1%) and Periodical publications (7.6%). In addition, missing information such as author identification (30.2%) or affiliation (69%) in the source repositories and data aggregators have been detected. Consequently, the assessment of researchers and institutions through datasets retrieved by OpenAlex would be improved by subsequently curating the information records. In conclusion, OpenAlex is a powerful tool in the Open Science medical ecosystem, and its accuracy could be enhanced by verifying the datasets collected via research information management infrastructures as well as by training professionals.