Downloading images from GBIF: Licenses, citation and link rot

Abstract

Downloading images of preserved specimens in bulk is becoming increasingly important for many research projects, especially those connected with machine learning and image analysis. A useful source of images is the standard biodiversity aggregator, the Global Biodiversity Information Facility (GBIF). Here we identify four major issues connected to GBIF image downloads, distinct from those associated with text downloads. These are (1) license considerations, (2) citation issues, (3) restricting to specific providers for project reasons or cybersecurity concerns, and, finally, (4) attempting to use links that are no longer functioning (often referred to as “link rot” or “data rot”). We suggest an incremental approach to downloading and suggest techniques for improved image download. We provide an implementation of our suggestions in Python (gbifimage-downloader).