Take a moment and consider your name. Do you have a name so unique that you are the only person with that name publishing in your field? I do—there are very few Helenmarys in the world to begin with. But if you cut my first name down to “Helen,” suddenly I could be one of a dozen authors working in my area. Reduce it further to “H,” and I’ve vanished among the crowd. Uniqueness is no match for the sheer ubiquity of names in the online scholarly publishing record.
What I need is a PID: a persistent identifier that refers to me and only me, and would still refer to me if I changed my name. For names, that’s easy: I have an ORCID iD, a sixteen-digit alphanumeric string that I can connect to my research output and take with me wherever I go. But what if I were not a person but a dataset, an article, or a piece of software? All of those can get PIDs too, as can far stranger objects, the breadth of which was the focus of January’s all-online, still-available, free PIDapalooza festival.
Though the virtual festival ran in January, video recordings of all sessions are now available in an official YouTube playlist with slides and other session materials available on Zenodo. For example: how many rare diseases has medicine identified? A talk by Alice Meadows and Melissa Haendel addresses the uniqueness problem in rare disease research and how PIDs are an essential component of disease definition. Researchers who use analysis software may be interested in a discussion led by Daniel S. Katz and Morane Gruenpeter: how can we reference and identify software code that doesn’t have a formal citation and may change over time, or be restricted by its creators? Finally, anyone who works with data in a research or professional capacity might appreciate a “no-nonsense, practical guide to implementing effective data practices,” presented by Maria Praetzellis, Judy Ruttenberg, Cynthia Hudson Vitale, and John Chodacki.
If you’re curious about PIDs (including DOIs), or about other ways to make your research objects more persistent and identifiable, the HSLS Data Services team can help. Contact us at HSLSDATA@pitt.edu to schedule a consultation, and help your data stand out.