Participation in this workshop is free to registered participants of the FORCE2019 meeting, but required. Please indicate your workshop preferences
via this form no later than October 4. Register for the #FORCE2019 meeting
here.
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ROR (Research Organization Registry) is a community-led project to develop an open, sustainable, usable, and unique identifier for every research organization in the world. ROR is a collaborative effort by four organizations—California Digital Library, Crossref, DataCite, and Digital Science—in conjunction with a growing group of stakeholders across the scholarly communication landscape, including librarians, data repositories, publishers, funders, metadata experts, and platform providers. The scope of ROR is the affiliation use case—to unambiguously identify which organizations are affiliated with which research outputs. In this way, ROR specifically aims to fill a gap in the scholarly community ecosystem: the lack of open, community-governed infrastructure for research organization identifiers, and associated metadata that can uniquely identify research outputs and connect them to the institutions where research is produced. We believe that institutions and libraries should not have to pay to collect and access information about what and where their researchers are publishing.
The ROR MVR (minimum viable registry) launched in January 2019 and approximately 95,000 organizations around the world now have unique ROR IDs, which are interoperable with other identifiers like GRID, Crossref Funder ID, and Wikidata. What can we do with all of this open data? The ROR project team is looking to the broader community for ideas about integrations, use cases and add-on services, which will help to connect research, researchers, institutions, outputs, funding and data. In this interactive workshop, we will explore the free, open ROR API and OpenRefine reconciler. Attendees will work in small groups to generate ideas and kick off mini projects that focus on using the ROR dataset to get useful information about research outputs and affiliations.
