Botany and Natural History specimen collections represent an unparalleled source of knowledge and research, and yet they are often inaccessible and underutilized due to their specialized nature. Descriptive metadata and identifications for these collections can be labor-intensive and time-consuming to generate, and often relies on the individual knowledge of subject matter specialists. While digitizing these collections allows the global scientific community ready access for study, Artificial Intelligence (AI) and Optical Character Recognition (OCR) can provide even deeper insights into these collections.

