Guidelines and best practices for the scientific use of global iNaturalist data

Abstract iNaturalist data are increasingly used in scientific research, yet researchers often lack clear guidance on how to access, handle, and properly attribute these data. Here, we provide a practical guide for the effective use of iNaturalist data in biodiversity research. We begin with an overview of key data concepts, including taxonomy, geoprivacy, location accuracy, and data availability. We then outline methods for acquiring biodiversity observation data, data summaries, and media, and provide example code in R and Python. We discuss key analytical considerations, including observer bias, the presence-only nature of the data, and appropriate modeling approaches. Finally, we highlight best practices for ensuring reproducibility through proper attribution, versioning, and transparent reporting; and we identify emerging research frontiers. This guide aims to support the responsible and effective use of iNaturalist data to further accelerate biodiversity research.