Jupyter notebooks are increasingly being used in the computational sciences, for data analysis and storytelling, but they can also be an invaluable tool for working with PIDs in libraries. Interacting with services such as ORCID and Zenodo, Jupyter’s step-by-step process offers an iterative approach to exploring and analyzing these datasets for reporting and curation purposes. In addition, the notebooks can be shared, allowing workflows to be reproduced, analysis remixed and shared again. This talk will demonstrate Jupyter notebok-PID uses in the library context.
