Data-Driven Deselection: Multiple Point Data Using a Decision Support Tool in an Academic Library

Circulation statistics are a traditional starting point for selecting books to withdraw. Rules-based weeding, based on multipoint data, enables librarians to make better-informed choices about the collection. Using a decision support tool forced Olin librarians to make weeding decisions based on multiple data points such as rarity, statewide repository candidates, or inclusion on recommended lists for college libraries. This article summarizes retention criteria rationale, consortial implications of weeding, and quantitative differences between single and multipoint data.