A LONGITUDINAL STUDY OF CONTENT DUPLICATION TRENDS IN OPEN ACCESS SCIENCE AND TECHNOLOGY DATABASES (2000-2023)

Abstract

This paper presents a comprehensive longitudinal analysis of content duplication trends in open access (OA) science and technology databases from 2000 to 2023. Open access publishing has significantly expanded, providing unrestricted access to scientific knowledge and accelerating research dissemination. However, the proliferation of OA publications has also led to concerns about content duplication, including self-plagiarism, duplicate publications, and salami slicing. This study aims to identify and analyze these trends using a combination of advanced content similarity detection tools and statistical methods. Data were collected from prominent OA databases, including PubMed Central, arXiv, DOAJ, SciELO, and IEEE Xplore Open Access. Our findings indicate an initial increase in duplication rates from 2000 to 2010, followed by a peak and plateau phase from 2011 to 2015, and a gradual decline from 2016 to 2023. Duplication rates varied significantly across disciplines, with biomedical sciences showing the highest rates and mathematics the lowest. Key factors influencing these trends included technological advancements in detection tools, policy changes by academic publishers, and the growth of preprint servers. The study highlights the effectiveness of current detection measures and suggests the need for ongoing efforts to maintain the integrity of scientific literature.