The second blog post about metadata matching by ROR’s Adam Buttrick and Crossref’s Dominika Tkaczyk describes some basic matching-related terminology and the components of a matching process, then poses some typical product questions to consider when developing or integrating matching solutions.
ROR Curation Lead Adam Buttrick has been working with Crossref Head of Strategic Initiatives Dominika Tkaczyk to explore improvements in automatic metadata matching strategies that can result in better metadata for everyone.
Following on the announcement that Crossref’s Open Funder Registry will be merging with ROR after 2024, we’d like to do a deep dive into the specifics of the evidence that ROR is ready to take on the important work that the Open Funder Registry has been doing: identifying research funders in a clean, consistent, comprehensive, and interoperable way.
One common question we receive about ROR registry records is whether they reflect organizational hierarchy and relationships between organizations – yes, they do!
The ROR registry includes unique IDs and associated metadata records for 100,000+ research organizations. Each one of these organizations has at least one name.
Some of the most frequent questions ROR receives are about what it means when an organization is in ROR, and how organizations end up in the registry in the first place.
The Research Organization Registry is a cross-organizational and multi-stakeholder initiative. ROR is run by a small group of steering organizations in collaboration with a broad network of community advisors and supporters.
Version 4.3 of the DataCite Metadata Schema released during August, 2019 included (among other things), the capability to provide persistent identifiers for affiliated organizations in the metadata (Dasler and deSmaele, Identify your affiliation with Metadata Schema 4.
ROR launched in January 2019 with records for nearly 100,000 research organizations, all with unique IDs and associated metadata. ROR data is useful for a variety of reasons and for a variety of users, including both humans and machines.