In 2021, Crossref will start to support the collection of ROR IDs in the metadata we collect, to help with the reliable identification and downstream use of affiliation data connected to research outputs.
“Author affiliations, and the ability to link them to publications and other scholarly outputs, are vital for numerous stakeholders across the research landscape. ROR is completely open, specifically focused on identifying affiliations, and collaboratively developed by, with, and for key stakeholders in scholarly communications.”" - Maria Gould, Lead RORganizer
What is ROR?
ROR is the Research Organization Registry––open, noncommercial, community-led infrastructure for research organization identifiers. The registry currently includes globally-unique persistent identifiers and associated metadata for more than 98,000 research organizations.
ROR IDs are specifically designed to be implemented in any system that captures institutional affiliations and to enable connections (via persistent identifiers and networked research infrastructure) between research organizations, research outputs, and researchers. ROR IDs are interoperable with those in other identifier registries, including GRID (which provided the seed data that ROR launched with), Crossref Funder Registry, ISNI, and Wikidata. ROR data is available under a CC0 waiver and can be accessed via a public API and data dump.
Who is ROR?
ROR is operated as a joint initiative by Crossref, DataCite, and California Digital Library, and was launched with seed data from GRID in collaboration with Digital Science. These organizations have invested resources into building an open registry of research organization identifiers that can be embedded in scholarly infrastructure to effectively link research to organizations.
Unique, persistent identifiers for affiliations are a key piece of Crossref metadata that has been missing, but will soon be supported in the Crossref metadata schema. This means that content registered with Crossref can be associated with a ROR IDs to enable better tracking and discovery of research and other publication outputs by institution. Up to this point, Crossref has had a field to collect affiliation metadata, but this has only collected free-text strings and is only being provided by a small number of members.
For example, a search for UC Berkeley returns multiple variants of the university’s name:
- University of California, Berkeley
- University of California-Berkeley
- University of California Berkeley
- UC Berkeley
- And likely more…
While it isn’t too difficult for a human to guess that “UC Berkeley,” “University of California, Berkeley,” and “University of California at Berkeley” are all referring to the same university, a machine interpreting this information wouldn’t necessarily make the same connections. If you are trying to easily find all of the publications associated with UC Berkeley, you would need to run and reconcile multiple searches at best, or miss data completely at worst. This is where an affiliation identifier comes in: a single, unambiguous, standardized identifier that will always stay the same (for UC Berkeley, that would be https://ror.org/01an7q238.
In terms of the collection of ROR IDs by publishers so that they can be sent to Crossref alongside other publication information, ROR can be implemented by manuscript tracking systems to identify the affiliations of submitting authors and co-authors. This can be done via a simple institution lookup that connects to the ROR API. Authors choose their affiliation from a dropdown list populated from ROR; they do not have to provide a ROR ID or even know that a ROR ID is being collected.
If the submission system you use does not yet support ROR, or you don’t use one, you’ll still be able to provide ROR IDs in your Crossref metadata. We’ll start to support the deposit of ROR IDs via our helper tools. There’s also an OpenRefine reconciler that can map your internal identifiers to ROR identifiers.
ROR IDs for affiliations stand to transform the usability of Crossref metadata. While it’s crucial to have IDs for affiliations, it’s equally important that the affiliation data can be easily used. The ROR dataset is CC0, so ROR IDs and associated affiliation data can be freely and openly used and reused without any restrictions.
The ROR IDs registered by members in their Crossref metadata will be also made available via Crossref’s open APIs so that it can be reused by tools, services and anyone interested in this information. For example; institutions need to monitor and measure their research output by the articles their researchers have published. Funders need to be able to discover and track the research and researchers they have supported. Academic librarians need to easily find all of the publications associated with their campus. Journals need to know where authors are affiliated so they can determine eligibility for institutionally sponsored publishing agreements. The inclusion of ROR IDs in Crossref metadata will help all these communities make all of these connections much more easily.
Get ready to ROR 🦁!
ROR is already working with publishers and service providers that are planning to integrate ROR in their systems, map their affiliation data to ROR IDs, and/or include ROR IDs in publication metadata.
In addition to publishers, libraries and repositories and other stakeholders are building in support for ROR. There’s a growing list of active and in-progress ROR integrations.
For information on how ROR IDs will be supported in the Crossref metadata, you can take a look at this .xsd file (under the ‘institution’ element) or in this journal article example XML.
Get in touch with ROR if you have questions or want to be more involved in the project. If you have questions about adding ROR iDs to your Crossref metadata, get in touch with our support specialists.