Purpose & Goals
Weeding an academic library is a complex and labor-intensive process and poses challenges for designing a uniform approach that accommodates subject-specific review criteria and workflows. In 2022, subject librarians and Collection Services personnel at Western Washington University developed an ambitious and cyclical plan for reviewing the general collection of roughly 500,000 items every four years, something that had not systematically been done for decades. The Collection Management and Assessment (CMA) department was tasked with designing and facilitating the data-informed collection evaluation process. This poster explores how the CMA department collaborated with subject librarians and other Collections personnel to identify relevant data points to inform withdrawal decisions, methods for collecting and compiling data from multiple sources, and the evolution of decision support tools to respond to disciplinary needs and librarian preferences. Discussions about the relevance of different data points across disciplines and strategies for collection review between subject librarians and Collections personnel also led to increased understanding and alignment of Collection Services and subject librarian goals and priorities for the project.

Practical Implications & Value
This project adds to the research on subject-specific monograph assessment criteria and workflows and introduces strategies for collaborating on data-informed weeding between Collections personnel and subject librarians. The presenters will share their methodologies for collecting and integrating data from disparate systems into decision support tools to assist in making withdrawal recommendations, and the process of iteration based on reviewer feedback and disciplinary needs. They will discuss strategies they employed to collaborate across library departments, and opportunities they identified for reducing subject librarian workload related to the project. Viewers will come away with an understanding of the benefits and drawbacks of how two different decision support tools are used in the Humanities and STEM. 

View Poster (PDF)