PROBLEMS OF BIBLIOGRAPHICAL MANAGERS FOR SCIENCE AUTOMATIZATION: APPROACH TO SOLVE AND ONTOLOGICAL VEIWPOINT

Abstract

This paper explores the functionalities and limitations of major reference manager systems, focusing on their role in solving the author identification problem in academic research. It critically analyzes the features of popular reference managers like Zotero, EndNote, Mendeley, SciWheel, and Paperpile, assessing their capabilities in reference management and their approaches to author identification. The study reveals that while these systems offer robust reference management functionalities, including citation generation, bibliography management, and collaborative tools, they fall short in integrating advanced author identification mechanisms, such as ORCID. The lack of such features highlights a significant gap in current reference management solutions, impacting the accuracy and efficiency of scholarly communication. The paper emphasizes the need for enhanced features in reference managers to address author identification challenges effectively, particularly in the context of Open Science and FAIR data management principles. This study contributes to the understanding of current limitations in reference managers and underscores the importance of developing advanced features for accurate author attribution in the digital era of academic research. It focuses on using additional integrational data about the authors by using ORCID as the main identifier. This solution is crucial for countries with non-Latin alphabet, including Cyrillic.