Just a quick one; first of all as a sign of life, I know I’ve been quiet of late, and second of all, to put out something that might be of use (albeit to a niche audience).

DOIs, or Digital Object Identifiers, are persistent identifiers for digital object for all sorts of things on the internet. Typically these are published documents, but they may also be things like datasets, workflows, images, etc.

I deal with these a fair amount at The Day Job, and often need to resolve these strings into something that returns metadata (title, author etc). Nice to be able to do this over an API.

Datacite, Crossref etc, who deal in DOIs, do provide their own resolution APIs, but only for items minted in their own namespaces, not the canonical set. DOI.org do provide a proxy, in order to resolve a doi to a location, but no obvious way of extracting metadata.

As it happens, there is a way of getting this data, with a little bit of Accept header witchcraft.

Anyway, to make it easier for you (and me), I wrote a library. Enjoy!

» Visit the project on Github...

Last week I gave a talk at the FREYA project wrap up meeting, part of the EOSC life symposium, on PIDs and how we (as part of my day job) were looking at using them to reproduce scientific research. This was one of the prize winners for the end of project award.

The basic concept is as follows:

  1. When a researcher visits an institution we create a PID identifying their “session”
  2. As an experiment is performed, we mint PIDs for each relevant asset, and “cite” the session identifier. Assets should include everything relevant for reproducing the science (this includes things you might not think of such as beam line or microscope configuration settings)
  3. When a research output is produced (research paper, protein in the protein database), all these sessions are tied together with another PID and a link is established between that bundle and the final output
  4. Using the PID Graph it is possible to unpack this.

If you’re interested, you can watch the presentation, or read more in the paper below.