Strengthening Scholarly Publishing at the University of Zambia: Custom OJS Plugins for Metadata Accuracy, DOI Management, and Repository Integration

Abstract

The growing demand for accurate, interoperable, and easily discoverable scholarly outputs necessitates enhanced publication workflows in institutional repositories and journal management systems. At the University of Zambia, where scholarly publishing is completely reliant on digital platforms, Open Journal Systems (OJS) has emerged as a central tool for journal hosting. However, limitations in automated metadata compliance, DOI integration, and repository deposition pose persistent challenges.  This paper is guided by a quantitative data mining approach and presents the conceptualization, development, and deployment of three interlinked OJS plugins designed to enhance the publication pipeline: (1) an Automated Metadata Verification Plugin that validates journal article metadata against institutional and international standards (2) a DOI Deposition Plugin that streamlines Crossref DOI registration and metadata syncing in real time; and (3) a DSpace Export Plugin that packages OJS-published content into DSpace-ready simple archive bundles(e.g ZIP) for seamless repository ingestion. The proposed system is to be implemented and tested within selected UNZA-hosted journals especially under the JABS editorial workflow. Preliminary results from an empirical analysis show substantial improvements in metadata completeness, cross-platform visibility, and compliance with repository requirements. Additionally, the plugins promote FAIR (Findable, Accessible, Interoperable, Reusable) principles by ensuring structured and verified data flows across platforms. By automating routine tasks, reducing human error, and bridging siloed scholarly infrastructure, this plugin suite represents a scalable model for institutions seeking to align with international open access standards. The paper concludes with insights on customization for multilingual metadata, and roadmap plans for integration with institutional repositories