Every project that uses numbers to make sense of literature seems to teach us again that in digital analysis we create more data than we can ever fully use and therefore understand. And yet, with each new project we produce more. In the Community Resource Guide to Digital Humanities Curation, Julia Flanders and Trevor Muñoz define research data as the “raw and abstracted material created as part of research processes and which may be used again as the input to further research.” Computational analysis of large corpora is a time- consuming process, and a lot of analysis ends up on the cutting room floor (or on the blog, or in a footnote or an appendix). We need to make better use of that discarded data—the detritus other people shed on the way to an answer. Think of it as data recycling to combat data waste.