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Libraries of all sizes are daunted by taking on a major collection review project, especially conducting the process in an efficient manner. This case study discusses a medium-sized government library’s successful data-driven weeding project. It explains how we planned the project, established goals, and created and executed workflows, all while considering the unique characteristics of our collection. Our project used two innovative and interconnected components: (1) a process using various criteria to systematically remove from consideration the titles we needed to keep, and (2) a data-driven process using different inputs and automation strategies that ensured we made high-quality decisions efficiently.

Data-Driven Monographic Weeding Project for a Medium-Sized Government Library: A Case Study