An interesting little book that examines annotation as a genre. I typically think of, and am interested in, annotation as an aspect of a close reading of written text that extends from the history of exegesis of sacred text and literature. But this book explores annotation from a far wider scope to include the digital labeling of data sets for training machine learning algorithms and as a tool for fact checking or civic advocacy and improvement. I found it a bit dry at times but found myself later making connections to the book when reading articles about Google deep learning networks annotating brain scans or when using an automated citation manager that needs to be checked to ensure labels are accurate. I have also started using Hypothesis, an open source annotation software that works pretty seamless as an overlay in a web browser. Annotation is much more deeply interwoven and embedded in our social, technological, and academic culture than we may be aware!