Biblans: an application for managing, sharing, representing and interpreting article data for bibliometric studies

Introduction: Bibliometric studies have gained popularity with the increase in scientific publications. However, there is no software that effectively manages all the data and allows its analysis, representation and interpretation. Objective: to design an application to collect, share, represent and interpret article data in bibliometric studies. Method: a technological development research was carried out in August 2024. The application was designed in Ubuntu 14.04 using Python 3.12, C++17 and MySQL. Pandas and MatPlotLib were used for data processing, FastAPI for the backend, and QtCreator for the interface. The application was converted into a Windows executable with auto-py-to-exe. Results: the application created despite running completely offline requires an initial connection to load user and license data, and to enable the collaborative sharing mode of users affiliated to the projects. Its article part detection system with the Grobid artificial intelligence model coupled with the scraping system of GoogleScholar, Mendeley and others was a strong point in the creation of the project database. It allows data analysis using the speed potential of C++ and representation using the versatility of Python libraries. Conclusions: The application is a useful tool for managing, sharing, representing and interpreting bibliometric data. It integrates powerful technologies such as Grobid, proving to be effective in its purpose.