Development of Digital Twins for Library Information System Simulation

Abstract

The creation of digital twins for Library Information Systems (LIS) simulation models provides new insights into the automation, management, efficiency, and user experience of modern-day libraries. A digital twin captures metrics from its real-world counterpart in real time, enabling analysis, monitoring, and optimization. The research is focused on LIS digital twin designs and implementations within the context of IoT, data analytics, and machine learning. Digital twins can simulate user behavior, resource usage, and subsystem interactions, offering great potential to enhance cataloging, circulation, space management, and personal service delivery, thereby augmenting advanced services. The research presents a schema that corresponds to the tangible assets within the library, including books and users, along with the infrastructure for their virtual representations. This enables predictive maintenance of the assets, automated inventory monitoring, and scenario testing. The development supports changing interface elements and user-operated control recommendation systems based on real-time usage data. Initial simulation results suggest improvements in library service delivery and decision-making capabilities within the library ecosystem. This paper addresses major concerns in data harmonization, vulnerability, privacy, and strategies for achieving effective twin deployment. The findings explain how the application of the digital twin disrupts library systems to provide responsive and user-centered information services.