Empowering Reading Engagement through Big Data Analytics in Taiwan

This study explores how the National Central Library in Taiwan leverages a big data service platform to empower public libraries, enabling them to enhance reader participation through data‐driven decisions. The platform systematically processes de‐identified circulation data through comprehensive cleaning, integration, and standardization procedures, enabling libraries to gain actionable insights through advanced visualization tools. This data empowerment initiative reflects the evolution of Taiwan's libraries towards Library 4.0, where analytics capabilities enable libraries to transform from passive information providers to active service innovators, providing personalized, differentiated reader experiences. The platform strengthens public libraries' capacity to promote reading engagement by providing detailed metrics and trend reports, facilitating evidence‐based policy making and service improvements. Through continuous data analysis and visualization, libraries can better understand their communities' reading preferences and adapt their services accordingly. In addition to basic statistical analysis, the platform incorporates and develops data mining techniques to analyze reading behaviors across demographics, offering deeper insights into reader interests and preferences. Furthermore, the study investigates the application of these data mining techniques to facilitate reader resource recommendations, ultimately enhancing library services and promoting a more engaged reading community.