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Corresponding Author ORCID Identifer

Jiaheng Lu https://orcid.org/0000-0003-2067-454X

Section

Regular Issue

Abstract

In the domain of academic publishing, publishers must establish an efficient editorial workflow for managing their publication schedule while producing quality content, as these two processes will ultimately provide a good experience to readers. Many independent publishers utilizing Open Journal Systems (OJS) rely on a manual compilation of "pre-pages" (front matter), including the Issue Cover, the Editorial Board List, and the Table of Contents (TOC), through a manual workflow that is labourintensive and prone to formatting and metadata errors. This study presents a web-based Pre-Pages Generator and Visualiser that automates the pre-publishing process, developed using Python and the Streamlit framework. The system utilizes a 5-step Wizard workflow to accomplish the entire pre-publishing process by integrating web scraping to extract existing editorial data from the target journal's website, cleansing the data, and leveraging template-driven rendering to populate Word templates with the appropriate OJS submission data. In addition, the Editorial Intelligence Dashboard provides an overview of issue composition and editorial insights into content trends across issues of the publication by transforming raw bibliometric data. Validation using Journal of Informatics and Web Engineering (JIWE) live production and five historical issues showed 100% formatting compliance across 154 papers, with no manual formatting corrections required. For a 24-paper issue, preparation time was reduced from approximately 90 minutes to 5 minutes (94%). These results demonstrate the practical value of the framework for reducing metadata risk and improving editorial efficiency for non-technical users.

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