Abstract

This study investigated the adoption of machine learning technologies in the digital preservation and archiving practices in academic libraries, focusing specifically on university libraries in Rivers State, Nigeria.  A descriptive survey design was adopted, targeting all professional librarians in university libraries in Rivers State. The population consisted of 36 Librarians, (7 staff from Rivers State University Central Library ,19 staff from Donald Ekong Library, University of Port Harcourt and 10 staff from Dame Jonathan Automated Library, Ignatius Ajuru University of Education). The entire population was studied using census method due to the manageable size of the population. A self-structured online questionnaire was used to collect data, which was analyzed using mean scores and standard deviation.  The result revealed that university libraries in River State are fully automated. The result also showed that digitalization, saving in multiple copies and institutional repository were the most used methods for preserving digital resources in university libraries in Rivers State. The study also revealed that high cost of high cost of implementation, data management issues, Infrastructure and technological limitation were identified as the major challenges hindering the adoption of Machine learning for digital preservation and archiving and proposes machine learning digital driven solutions to enhance efficiency, accuracy and sustainability in digital preservation efforts.

Keywords: Machine Learning Technologies, Automated Digital Preservation, Archive.