In academic publications, the automation of full-text eXtensible Markup Language (XML) is increasingly essential, as generating full-text XML for article distribution is a complex and time-consuming process that requires metadata extraction from a relational database and transformation into hierarchical structures such as Journal Article Tag Suite (JATS). The lack of automation in this transformation process may cause inconsistencies and inaccuracies and may cause errors due to human error. The primary aim is to develop an automation system for transforming metadata from a relational database to full-text XML by reducing errors and speeding the process of generating full-text XML. This is crucial since the demand for automation has been increasing year by year. Furthermore, the motivation behind this research is the growing adoption of the Open Journal System (OJS), one of the popular platforms for managing scholarly journals. It supports a relational database to store the metadata and article information. Therefore, developing an automated system is essential for transforming this structured metadata to full-text XML. To address this issue, various techniques for mapping will be explored to enable the transformation of relational database structures into full-text XML formats. The proposed method involves metadata extraction, mapping logic, and various validation mechanisms to ensure the XML is structured and the accuracy of it. The preliminary result indicates that the metadata has been successfully mapped from a relational database to XML. However, the JATS-specific tagging has not yet been implemented and will be addressed in future work. This research is significant to the publication community, as it brings convenience by reducing some manual work and ensuring metadata standardization.
Ling et al. (Tue,) studied this question.